Before television shows like
The Office
and
Parks and Recreation
cemented the mockumentary in the minds of millions, there was Christopher Guest. He didn’t invent the genre, but he’s widely recognized as one of its most influential practitioners, and for my money, there’s none better. I’ve watched
Waiting for Guffman
and
Best in Show
more times than I can count. But the one that has stuck with me the most, the one I quote at the slightest provocation, is
This Is Spinal Tap
.
If you’ve seen it you already know where this is going (and if you haven’t, you now have weekend plans). The film is a fictional documentary about an aging English rock band named Spinal Tap, whose members are everything we picture when we picture over-the-top rock stars. In one of its more memorable scenes, the guitarist (Nigel) gives the filmmaker (Marty) a tour of his most prized gear, in particular showing off an amplifier unlike any other: its dials don’t stop at ten. That leads to what might be the single most quoted exchange in the entire movie:
Nigel:
“You see, most blokes, you know, will be playing at ten. You’re on ten here, all the way up, all the way up, all the way up, you’re on ten on your guitar. Where can you go from there? Where?”
Marty:
“I don’t know.”
Nigel:
“Nowhere. Exactly. What we do is, if we need that extra push over the cliff, you know what we do?”
Marty:
“Put it up to eleven?”
Nigel:
“Eleven. Exactly. One louder.”
This is .NET 11. It’s one louder, with another year’s worth of performance work
having gone into making the runtime and libraries that much faster. Of course, the premise of Nigel’s special amplifier is ludicrous, as is exemplified in the subsequent few lines of dialog:
Marty:
“Why don’t you just make ten louder and make ten be the top number and make that a little louder?”
Nigel:
(pauses) “…these go to eleven.”
In contrast, .NET 11 is actually one higher, one louder. The sections that follow are full of real improvements. A bounds check removed, an allocation that no longer happens, a lock that isn’t taken, a loop that runs in fewer cycles than it did a year ago, a comparison folded to a constant here, a redundant check hoisted out of a loop there, a couple of instructions fused into one, a syscall sidestepped, an array copy handed off to SIMD, and on and on. That’s how real performance work goes, accumulating gain after gain, each compounding on the last, until the whole thing is measurably, provably louder. And so, in this post, as I’ve done in past years with
.NET 10
,
.NET 9
,
.NET 8
,
.NET 7
,
.NET 6
,
.NET 5
,
.NET Core 3.0
,
.NET Core 2.1
, and
.NET Core 2.0
before it, we’ll take an unhurried tour through hundreds of them.
This is a long one. It’s meant to be. Grab your hot beverage of choice, settle in, and let’s turn it up.
Benchmarking Setup
As in previous years, the post is chock full of micro-benchmarks that demonstrate the individual improvements. Almost all of them use
BenchmarkDotNet
, and each is written to be self-contained so you can try it out yourself.
Start by ensuring you have both
.NET 10
and
.NET 11
installed (most of the benchmarks compare the same code running on both versions) and create a new console project in a fresh
benchmarks
directory:
dotnet new console -o benchmarks
cd benchmarks
Replace the contents of the generated
benchmarks.csproj
with the following, which multi-targets both versions so that BenchmarkDotNet can build for each:
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net11.0;net10.0</TargetFrameworks>
<LangVersion>preview</LangVersion>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
<ServerGarbageCollection>true</ServerGarbageCollection>
<SystemPackageVersion Condition="'$(TargetFramework)' == 'net10.0'">10.0.12</SystemPackageVersion>
<SystemPackageVersion Condition="'$(TargetFramework)' == 'net11.0'">11.0.0-rc.1.26425.128</SystemPackageVersion>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="BenchmarkDotNet" Version="0.16.0-preview.1" />
<PackageReference Include="System.IO.Hashing" Version="$(SystemPackageVersion)" />
<PackageReference Include="System.Runtime.Caching" Version="$(SystemPackageVersion)" />
<PackageReference Include="System.Numerics.Tensors" Version="$(SystemPackageVersion)" />
</ItemGroup>
</Project>
For a given benchmark to test, copy its complete contents over everything in
Program.cs
and then run it. Each benchmark includes as a comment at the top the exact command to use. In most cases, it’s:
dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
which builds in Release and runs the benchmark against both .NET 10 and .NET 11, emitting a side-by-side comparison. The other common form, used when a benchmark is comparing two coding approaches on a single runtime (rather than the same code across two runtimes) is:
dotnet run -c Release -f net11.0 --filter "*"
The usual disclaimer applies: these are micro-benchmarks, many measuring operations so short that a blink would miss them. Your results will vary with your hardware, OS, runtime configuration, what else your machine happens to be doing at that exact moment, and whether Mercury is in retrograde.
Every line of managed code ultimately ends up at the just-in-time compiler, so let’s start there.
JIT
Of all the places to improve .NET’s performance, few have as broad an impact as the just-in-time (JIT) compiler. C#, F#, and Visual Basic are typically compiled first to intermediate language (IL), and the JIT ultimately turns that IL into the native instructions the CPU executes. A JIT improvement can therefore benefit application and library code wherever the optimized pattern occurs, often with no source changes or recompilation of the application itself. Even removing a single instruction or proving one check unnecessary can add up when the code is on a very hot path.
Deabstraction
We as developers love our abstractions. They let us write clean, reusable, object-oriented code, but we don’t want to pay for every abstraction at run time. The runtime can often undo an abstraction when it proves the effects aren’t observable. It can look at a virtual call and determine which concrete method it’ll invoke, look at a heap allocation and recognize that the object never leaves the current stack frame, or look at an interface cast and reuse a type fact already established earlier in the method. This process is called “deabstraction.” .NET has improved steadily in this area for years, and that continues in .NET 11.
Every time you write
interface
in C#, you’re creating a contract, a promise that any type implementing that interface can be substituted for any other. That flexibility is enormously valuable because, for example, it’s what lets us write
IEnumerable<T>
and have it work equally well over arrays, lists, other collections, LINQ, custom iterators, and so on. But the CPU doesn’t know anything about these contracts; it just knows how to execute instructions. Turning “call whatever method this interface reference points to” into actual machine instructions requires special machinery. Consider this example:
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Animal _animal = Environment.TickCount >= 0 ? new Dog() : new Cat();
[Benchmark]
public int Speak() => _animal.Speak();
public abstract class Animal
{
public abstract int Speak();
}
private sealed class Dog : Animal
{
[MethodImpl(MethodImplOptions.NoInlining)]
public override int Speak() => 1;
}
private sealed class Cat : Animal
{
[MethodImpl(MethodImplOptions.NoInlining)]
public override int Speak() => 2;
}
}
At compile time, all else equal, the JIT doesn’t know whether
_animal
is a
Dog
or a
Cat
. It generates code that loads the instance’s “method table pointer” (its object type handle), sometimes called a “vtable pointer”, stored at the beginning of every .NET object, indexes into the method table at the known slot for
Speak
, and calls the function pointer found there:
; x64
mov rcx, [rcx+8] ; load _animal
mov rax, [rcx] ; load method table
mov rax, [rax+40] ; load vtable chunk
call qword ptr [rax+20]
For this one call to
Speak
, we pay three dependent memory dereferences and an indirect call because the processor doesn’t know for certain in advance where the call is going (it might guess, or “speculatively execute”, but it has to be prepared for the possibility it was wrong), and because the call target is indirect, the JIT can’t inline the callee. Whatever
Speak
does, its code can’t be folded into the calling method.
That’s a performance problem. Those indirections have overhead, but the bigger cost is the lost opportunity to inline. Inlining not only saves function call overhead, more importantly it opens the callee’s code up to the same optimizations that are operating on the caller, such as constant propagation, dead code elimination, bounds check elimination, further devirtualization, etc. That means a series of small virtual calls that each look innocent can, when devirtualized and inlined, collapse into a handful of instructions that would be unrecognizable and way cheaper when compared to the original source code. Without inlining, each callee is an opaque box; with it, the JIT can see through the layers.
We as .NET developers constantly rely on the JIT’s sophisticated heuristics for inlining that weigh the IL size of the callee, the exact work the callee is performing, the call frequency of the method, the expected benefit from constant arguments, and dozens of other factors. For virtual calls, the JIT needs to know what the actual target of the call will be; it needs to “devirtualize”. In some cases, it can determine that statically, where it has exact-type knowledge. For example, if the JIT can prove that
animal
is always a
Dog
, whether because it was just allocated with
new Dog()
:
Animal animal = GetSomeAnimal();
animal.Speak();
...
static Animal GetSomeAnimal() => new Dog(); // inlineable
or because the variable’s type is a sealed class:
Dog animal = GetSomeAnimal();
animal.Speak();
...
sealed class Dog { ... } // impossible for `animal` to be anything other than a `Dog`
or with NativeAOT and whole-program compilation, if it sees that
Animal
is abstract and the only type in the whole application that derives from
Animal
is
Dog
:
Animal animal = GetSomeAnimal();
animal.Speak();
...
abstract class Animal { ... }
class Dog : Animal { ... } // no other such derived type
or other such validation, it can emit a call to
Dog.Speak()
directly, and the inliner can take its shot.
But for other cases where it can’t prove this with static analysis, the JIT turns to profile-guided optimization (PGO). PGO sounds fancy, but it’s conceptually simple. With “tiered compilation”, when a method is first invoked, it can be compiled “just in time” with few-to-no optimizations (this is referred to as Tier 0). The JIT can include in this compilation additional probes (think “printf debugging”) that let it track a bunch of interesting information about the nature of the code, recording what actually happens when it runs: which branches are taken, what are the concrete types that show up at virtual call sites or cast attempts, and so on. If the method is invoked enough or loops enough times, the runtime can ask the JIT to produce a new optimized version (referred to as Tier 1). That compilation can then factor in all of the learnings gathered as part of that profiling.
The JIT, of course, still needs to generate code that’s always correct. Even if a dynamic profile says
animal
was
Dog
100% of the time, that doesn’t guarantee it’ll always be
Dog
in the future; it could be that the first 1000 calls passed in a
Dog
but the 1001st call is going to pass in
Dolphin
. How can the JIT incorporate this learning then? By emitting a run-time check. The
Dog
path can get a direct call, which may then be inlinable, and the other path keeps the original virtual call as the fallback. The speed comes from making the common case tiny, while correctness comes from leaving the uncommon case intact.
// Approximately what the JIT generates
if (animal?.GetType() == typeof(Dog))
{
((Dog)animal).Speak(); // devirtualized, inlinable
}
else
{
animal.Speak(); // original virtual call, hopefully rare
}
This “guess and verify” pattern, called “guarded devirtualization” (GDV), accounts for many of the biggest throughput wins in real workloads. It’s applicable not only to virtual dispatch but also to interface dispatch, which also happens to be a bit more expensive than virtual dispatch because a type can implement any number of interfaces and that means the interface slots don’t simply map to fixed vtable positions.
Deabstraction can also make object creation more efficient when it reveals what kind of object is involved. In general, objects in .NET are allocated on the garbage collected heap, tracked by the garbage collector (GC), and collected when no longer reachable. Heap allocation is typically fast, often effectively just bumping a pointer. However, when there’s not enough space available to bump the pointer, it can get much more expensive, including needing to incur a garbage collection. Every allocated object also effectively incurs the amortized cost of all collections, as every allocated object eventually needs to be cleaned up.
“Escape analysis” is the compiler technique that lets us ask whether this object ever “escapes” the current method. If an object reference to a newly allocated object provably doesn’t escape, then the JIT can more efficiently allocate it. It needn’t store it on the GC heap, because nothing could possibly need to reference that object again, so it can instead allocate the object on the stack, making both allocation and cleanup essentially free. Stack allocation is even faster than heap bump-pointer allocation; it’s just decrementing the stack pointer, which is typically already in a register. And more importantly it means zero GC impact, because the stack frame is freed atomically on function return.
The JIT’s been progressively expanding escape analysis over the past several .NET releases, with .NET 9 and 10 seeing significant investments in stack-allocating delegates and closures,
Nullable<T>
temporaries, and small helper objects. The key theme is that every false positive escape, every time the JIT incorrectly concludes an object may escape when it really doesn’t, represents a heap allocation that could have been avoided, and we want to whittle away at that false positive list. In .NET 11, the JIT trims that list in several ways.
We’ll start with nullable boxing. Consider this benchmark:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int? _nullableNull;
private int? _nullableValue = 42;
[Benchmark]
public object? BoxNullableNull() => (object?)_nullableNull;
[Benchmark]
public object? BoxNullableValue() => (object?)_nullableValue;
[Benchmark]
public string? FormatNullableInt() => Format(_nullableValue);
private static string? Format<T>(T value)
{
if (value is IFormattable formattable)
return formattable.ToString(null, null);
return null;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
BoxNullableNull
|
.NET 10.0
|
2.095 ns
|
1.00
|
–
|
–
|
|
BoxNullableNull
|
.NET 11.0
|
1.764 ns
|
0.84
|
–
|
–
|
|
BoxNullableValue
|
.NET 10.0
|
9.213 ns
|
1.00
|
24 B
|
1.00
|
|
BoxNullableValue
|
.NET 11.0
|
4.126 ns
|
0.45
|
24 B
|
1.00
|
|
FormatNullableInt
|
.NET 10.0
|
9.583 ns
|
1.00
|
24 B
|
1.00
|
|
FormatNullableInt
|
.NET 11.0
|
1.987 ns
|
0.21
|
–
|
0
|
dotnet/runtime#122167
expands nullable boxing inside the JIT, exposing the temporary box to escape analysis; previously, a runtime helper hid it. For a
null
input, there’s no allocation on either version, because nothing gets boxed. And on both versions,
BoxNullableValue
returns the boxed object, meaning the object escapes, so the 24-byte allocation remains. However, for
FormatNullableInt
, the JIT in .NET 11 can now see that the temporary 24-byte box doesn’t escape and eliminates that heap allocation entirely.
Escape analysis improved further for enumerators, through a mechanism called Conditional Escape Analysis (CEA). Support for CEA was introduced in .NET 10, but .NET 11 extends the set of patterns that this analysis can safely recognize. The existing escape analysis asks whether a reference created by an allocation can flow somewhere the JIT can no longer track, such as an unknown call. If it can, the object must remain on the heap. That analysis is necessarily conservative and largely flow-insensitive: if an object might be passed to an interface call on any path, it doesn’t try to prove that the path containing that call is mutually exclusive with the path containing the allocation.
Unfortunately, that’s exactly what GDV produces when it optimizes a
foreach
over an
IEnumerable<T>
. As noted earlier, GDV turns an interface call into a type check with two branches: a fast branch for the likely collection type and a fallback branch containing the original interface call. Devirtualization and inlining along the fast branch will often reveal an enumerator allocation for the collection type, while later enumerator guards retain fallback calls such as
IEnumerator<T>.MoveNext
. The existing analysis sees those calls and concludes that the locally allocated enumerator might escape. CEA instead records the relationship between the fast-path allocation and the enumerator local tested by the later guards. If every apparent escape occurs only behind a failed type check, the JIT can clone the region into a hot version where those checks are known to succeed. In that clone, the object can’t reach the fallback calls, so it can be stack-allocated and often promoted into separate scalar locals. The original region remains as the general slow path.
One case .NET 10 didn’t handle, though, was a
GetEnumerator()
implementation that returns the result of another
GetEnumerator()
call. A collection expression converted to
IEnumerable<int>
, for example, uses a compiler-generated read-only-array wrapper with exactly this structure: the wrapper’s
GetEnumerator()
delegates to the underlying array’s
GetEnumerator
. With
dotnet/runtime#122946
, the JIT in .NET 11 handles this “chaining”:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly IEnumerable<int> s_readOnlyStatic = [1, 2, 3, 4, 5];
private readonly IEnumerable<int> _readOnlyInstance = [1, 2, 3, 4, 5];
[Benchmark]
public int ReadOnlyStatic()
{
int sum = 0;
foreach (int item in s_readOnlyStatic) sum += item;
return sum;
}
[Benchmark]
public int ReadOnlyInstance()
{
int sum = 0;
foreach (int item in _readOnlyInstance) sum += item;
return sum;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
ReadOnlyStatic
|
.NET 10.0
|
2.665 ns
|
1.00
|
–
|
–
|
|
ReadOnlyStatic
|
.NET 11.0
|
2.666 ns
|
1.00
|
–
|
–
|
|
ReadOnlyInstance
|
.NET 10.0
|
13.874 ns
|
1.00
|
32 B
|
1.00
|
|
ReadOnlyInstance
|
.NET 11.0
|
2.674 ns
|
0.19
|
–
|
0
|
ReadOnlyStatic
, whose
static readonly
field the JIT can effectively treat as a constant, was already optimized in .NET 10. In .NET 11, the instance-field case also loses its 32-byte enumerator allocation and converges on the same throughput.
dotnet/runtime#121918
from
@MichalPetryka
fixes another way an address could unnecessarily make an object appear to escape. The IL
constrained.
prefix lets one generic
callvirt
sequence work for both value types and reference types: it can avoid boxing a value type, while for a reference type it dereferences the receiver and performs normal virtual dispatch.
ObjectEqualityComparer<T>.Equals
, used in the following benchmark by
EqualityComparer<T>.Default
, contains such a call to
value.Equals(other)
. The receiver was represented as an indirect read through the address of a local. Merely taking that address marked the local as exposed, preventing the newly allocated
Value
from being considered for stack allocation. The receiver is now represented as a direct value load instead, and the 24-byte heap allocation disappears.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Collections.Generic;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly Value s_other = new(42);
[Benchmark]
public bool Equals() => EqualityComparer<Value>.Default.Equals(new Value(42), s_other);
private sealed class Value(int value)
{
private readonly int _value = value;
public override bool Equals(object? obj) => obj is Value other && _value == other._value;
public override int GetHashCode() => _value;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Equals
|
.NET 10.0
|
3.874 ns
|
1.00
|
24 B
|
1.00
|
|
Equals
|
.NET 11.0
|
1.786 ns
|
0.46
|
–
|
0
|
While CEA can move a non-escaping object off the GC heap, sometimes the JIT can go further and prove an allocation need not exist at all. Generic code provides a common source of such opportunities through boxing. For example, the
ArgumentNullException.ThrowIfNull
method accepts an
object value
. That means when you have a method like this:
static void Test<T>(T value)
{
ArgumentNullException.ThrowIfNull(value);
...
}
when
T
is constrained to a non-nullable struct, boxing is incurred, in order to pass
value
as
object
.
ThrowIfNull
here is a nop if
value
is non-
null
(since the method is simply
if (value is null) Throw();
), and previous releases successfully optimized away that boxing in optimized code. However, in Tier 0, that optimization wasn’t applied, and
ThrowIfNull
would end up allocating. While this wouldn’t negatively impact steady-state throughput, it would lead to annoying noise in profiling, as well as additional overhead during startup, where such use wasn’t yet promoted out of Tier 0. In .NET 11,
dotnet/runtime#129392
adds support for this in Tier 0 as well.
On the virtual-dispatch side, multiple PRs contribute to improving generic virtual methods (GVMs).
dotnet/runtime#120866
from
@hez2010
stops eagerly spilling
ldvirtftn
call targets into a temporary, and lets generic virtual target resolution move ahead of argument setup when legal.
dotnet/runtime#122023
from
@hez2010
then enables the JIT to devirtualize non-shared GVMs, carrying the generic context needed to turn the indirect dispatch into a direct, and potentially inlineable, call. And
dotnet/runtime#128702
from
@hez2010
extends that support to shared GVMs and default interface implementations that require an instantiating stub. These optimizations can increase total code size when the newly direct calls are inlined, but that’s generally the desired trade: more of the actual work becomes visible to the optimizer. Consider the following benchmark:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Benchmark]
public int NonShared() => ((IProcessor)new Processor()).SizeOf(42);
[Benchmark]
public int Shared() => ((IProcessor)new Processor()).SizeOf("hello");
private interface IProcessor
{
int SizeOf<T>(T value);
}
private sealed class Processor : IProcessor
{
public int SizeOf<T>(T value) => Unsafe.SizeOf<T>();
}
}
Casting a freshly allocated
Processor
to
IProcessor
incurs an interface generic virtual call in the IL, but the JIT is now able to see the receiver’s exact type, even in the shared
string
case, such that .NET 11 devirtualizes and inlines both calls. That in turn exposes
Unsafe.SizeOf<T>()
as a constant and proves that the short-lived
Processor
doesn’t need to be allocated at all.
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
NonShared
|
.NET 10.0
|
6.678 ns
|
1.00
|
24 B
|
1.00
|
|
NonShared
|
.NET 11.0
|
1.764 ns
|
0.26
|
–
|
0
|
|
Shared
|
.NET 10.0
|
7.166 ns
|
1.00
|
24 B
|
1.00
|
|
Shared
|
.NET 11.0
|
1.764 ns
|
0.25
|
–
|
0
|
Building on that,
dotnet/runtime#123183
from
@hez2010
enables ReadyToRun compilation to resolve and devirtualize more non-shared generic virtual calls that would otherwise remain indirect, and
dotnet/runtime#130202
from
@hez2010
extends that support to NativeAOT. NativeAOT represents some generic virtual targets as “fat pointers” (pointers that are more than just an address, typically an address and associated metadata, and that in this case carry both a code address and generic context); by deferring that transformation until after exact-type devirtualization has had a chance to run, the JIT can turn an interface call site with a single known target to a non-shared GVM into a direct call that may then be inlined.
Type information also needs to survive the transformations the JIT performs internally. If the JIT spills a reference expression into a temporary while restructuring a tree, losing the expression’s exact class information can turn a call that was devirtualizable back into an opaque virtual call. That’s what happens here in .NET 10:
Value
gets boxed and
SetValue
is invoked through
IValue
.
dotnet/runtime#128485
from
@hez2010
preserves the class handle and exactness on the temporary. With that information still available, .NET 11 devirtualizes and inlines the call, eliminating the box and its 24-byte allocation.
Separately,
dotnet/runtime#127433
relaxes the inliner’s budget heuristics for callees on
[Intrinsic]
types like
Span
and
Vector
. These types intentionally expose many small, composable methods that serve as gateways to JIT-recognized operations. If a wrapper remains as a call, the caller pays the call overhead and optimizations around it see an opaque boundary. If it inlines, the importer can replace its body with an intrinsic node and optimize that node together with the surrounding indexing, bounds checks, and vector operations. Giving such wrappers more favorable budgeting therefore keeps more of them inlineable and exposes more of the actual operation to the rest of the optimizer.
One of the core abstraction-enabling mechanisms in .NET is delegates: they let us pass around objects representing functions to be invoked, carrying with them associated required state. Deabstraction enables avoiding paying for the overheads associated with delegates in some cases. For the rest, we still want those delegates to be as cheap as possible.
dotnet/runtime#99200
from
@MichalPetryka
simplifies CoreCLR’s delegate
representation, removing one pointer-sized field from every delegate object.
That saves 8 bytes per delegate in a 64-bit CoreCLR process.
dotnet/runtime#129304
from
@MichalPetryka
improves Native AOT’s
delegate layout separately by reordering its existing four fields so related
values are adjacent. The updated layouts also give equality and hash-code
operations more direct access to the method identity they need.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly Target s_target = new();
private static readonly Func<int> s_first = s_target.GetValue;
private static readonly Func<int> s_second = s_target.GetValue;
[Benchmark]
public Func<int> ClosedInstance() => s_target.GetValue;
[Benchmark]
public bool DelegateEquals() => s_first.Equals(s_second);
[Benchmark]
public int DelegateGetHashCode() => s_first.GetHashCode();
private sealed class Target
{
public int GetValue() => 42;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
ClosedInstance
|
.NET 10.0
|
7.395 ns
|
1.00
|
64 B
|
1.00
|
|
ClosedInstance
|
.NET 11.0
|
6.844 ns
|
0.93
|
56 B
|
0.88
|
|
DelegateEquals
|
.NET 10.0
|
3.254 ns
|
1.00
|
–
|
–
|
|
DelegateEquals
|
.NET 11.0
|
2.215 ns
|
0.68
|
–
|
–
|
|
DelegateGetHashCode
|
.NET 10.0
|
5.623 ns
|
1.00
|
–
|
–
|
|
DelegateGetHashCode
|
.NET 11.0
|
3.741 ns
|
0.67
|
–
|
–
|
dotnet/runtime#129410
from
@MichalPetryka
follows up on the CoreCLR
layout by placing the target object and method pointer next to each other.
Those are commonly consumed together during invocation, and the adjacency
enables paired loads on architectures such as Arm64.
Runtime Async
For more than a decade,
async
and
await
have let us write asynchronous code that looks remarkably similar to synchronous code: we can put a
try
/
catch
around an
await
, use local variables on either side of it, return a value and generally reason about the method in source order. When execution reaches an
await
for something that isn’t yet complete, however, the method can’t simply leave its current stack frame in place and wait for the operation to finish. The thread needs to be freed up to do other work, while the work after the
await
, including whatever local state it will need later, must survive somewhere. In C#, the compiler has traditionally been responsible for transforming the method into a representation that enables that continuation.
I went into the history and mechanics of that transformation in
How async/await really works
. The very short version is that the compiler traditionally replaces an
async
method with a small entry method and a generated state machine whose
MoveNext
method contains the transformed user code. Parameters, locals that need to survive an incomplete await, spilled expression values, awaiters, the current state number, and a method builder all become fields on a heap-allocated object. The generated
MoveNext
method runs the user’s code until an awaiter reports that it isn’t yet complete. It stores enough information to know where and with what values to resume, registers
MoveNext
as the continuation, and returns. When the operation completes,
MoveNext
is invoked again, jumps to the right location based on the saved state number (think
goto
and a label), retrieves the result from a value-producing awaiter, and continues. If every awaiter is already complete,
MoveNext
can run all the way through synchronously. When the method completes or throws, the builder publishes the result, cancellation, or exception through the returned
Task
,
Task<T>
,
ValueTask
, or
ValueTask<T>
(or, in the rare case, a custom task-like type).
For example, consider this tiny method:
static async Task<int> ReadLengthAsync(Stream stream, CancellationToken cancellationToken)
{
var buffer = new byte[4096];
int bytesRead = await stream.ReadAsync(buffer, 0, buffer.Length, cancellationToken);
return bytesRead;
}
While the code that gets generated for this changes over time and differs between debug and release builds, the lowering by the C# compiler has looked something like this:
[AsyncStateMachine(typeof(<ReadLengthAsync>d__0))]
static Task<int> ReadLengthAsync(Stream stream, CancellationToken cancellationToken)
{
<ReadLengthAsync>d__0 stateMachine = default;
stateMachine.builder = AsyncTaskMethodBuilder<int>.Create();
stateMachine.state = -1;
stateMachine.stream = stream;
stateMachine.cancellationToken = cancellationToken;
stateMachine.builder.Start(ref stateMachine);
return stateMachine.builder.Task;
}
struct <ReadLengthAsync>d__0 : IAsyncStateMachine
{
public int state;
public AsyncTaskMethodBuilder<int> builder;
public Stream stream;
public CancellationToken cancellationToken;
private TaskAwaiter<int> awaiter;
public void MoveNext()
{
int result;
try
{
TaskAwaiter<int> localAwaiter;
if (state != 0)
{
byte[] buffer = new byte[4096];
localAwaiter = stream.ReadAsync(buffer, 0, buffer.Length, cancellationToken).GetAwaiter();
if (!localAwaiter.IsCompleted)
{
state = 0;
awaiter = localAwaiter;
builder.AwaitUnsafeOnCompleted(ref localAwaiter, ref this);
return;
}
}
else
{
localAwaiter = awaiter;
awaiter = default;
state = -1;
}
result = localAwaiter.GetResult();
}
catch (Exception e)
{
state = -2;
builder.SetException(e);
return;
}
state = -2;
builder.SetResult(result);
}
}
That’s quite a lot of generated code for three lines of C#. The compiler has to make decisions before the program runs about the state-machine layout, which values might need to survive, how many awaiter fields are required, and how all the suspension points fit into one
MoveNext
dispatch. The runtime and JIT have optimized the resulting pattern heavily over the years, including combining the task, state machine, continuation, and
ExecutionContext
into a single allocation, but by the time the JIT sees the IL, the transformation has already happened, leaving it with a very complicated system to try to optimize.
.NET 11 introduces a new way to split that responsibility, a reimplementation of the
async
/
await
infrastructure referred to as “runtime async”. Rather than the C# compiler being responsible for the transformation, the JIT is. The C# compiler emits a much smaller suspension-aware IL contract for each eligible
async
method and marks the method as
async
in metadata. The runtime and JIT then do the work that depends on runtime knowledge: creating the externally visible
Task
or
ValueTask
, recognizing direct async calls, deciding which values are actually alive at each suspension point, laying out continuation objects, and generating the control flow that suspends and resumes the method. Effectively, the transformation moves from C# to the runtime, where more information is available to optimize it.
The programming model hasn’t changed. This is still C#
async
/
await
;
await
still obeys the awaiter pattern, exceptions and cancellation still surface through the returned task-like object,
ConfigureAwait
still has its usual meaning, synchronous completion is still synchronous completion, and on and on. An explicit goal for the feature has been 100% behavioral compatibility: whether an
async
method is lowered by the language compiler or by the runtime is an implementation detail, and any observable semantic difference is a bug.
In .NET 11, application code opts in with a compiler feature switch:
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net11.0</TargetFramework>
<Features>$(Features);runtime-async=on</Features>
</PropertyGroup>
</Project>
Note that there’s no new C# syntax involved, so
LangVersion=preview
isn’t required, nor is
EnablePreviewFeatures
. While this is opt-in at the application layer, most of the in-box shared framework is already built this way for .NET 11. The
async
/
await
performance goal for .NET 11 is parity with .NET 10, and in general runtime async is already as good as or better than the older implementation in many important paths. It isn’t yet fully optimized, though, and there are known cases where it still produces less efficient code. I’d encourage you to experiment in .NET 11 with opting-in your applications and services; just make sure to measure. My hope is that it’ll be on by default starting in .NET 12.
Moving the transformation from the C# compiler to the runtime has the added benefit of reducing binary size. As noted, the traditional lowering emits an entry method, a generated state-machine type, fields for captured state, and a
MoveNext
body, for every async method. Runtime async leaves a much smaller method body for the runtime to transform. The following tiny app contains ten
Task<int>
-returning async methods, each awaiting the next, and compiles the same source once with compiler lowering and once with runtime async:
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net11.0</TargetFramework>
<AssemblyName>SizeProbe</AssemblyName>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<Features Condition="'$(RuntimeAsync)' == 'true'">$(Features);runtime-async=on</Features>
</PropertyGroup>
</Project>
// dotnet build -c Release -p:RuntimeAsync=false -o classic --no-incremental; dotnet build -c Release -p:RuntimeAsync=true -o runtime --no-incremental; Get-Item .\classic\SizeProbe.dll, .\runtime\SizeProbe.dll | Select-Object Directory, Length
Console.WriteLine(await Benchmarks.Layer0());
public class Benchmarks
{
public static async Task<int> Layer0() => await Layer1();
private static async Task<int> Layer1() => await Layer2();
private static async Task<int> Layer2() => await Layer3();
private static async Task<int> Layer3() => await Layer4();
private static async Task<int> Layer4() => await Layer5();
private static async Task<int> Layer5() => await Layer6();
private static async Task<int> Layer6() => await Layer7();
private static async Task<int> Layer7() => await Layer8();
private static async Task<int> Layer8() => await Layer9();
private static async Task<int> Layer9()
{
await Task.Yield();
return 42;
}
}
|
Lowering
|
SizeProbe.dll
|
Ratio
|
|
Compiler
|
10,752 bytes
|
1.00
|
|
Runtime async
|
5,632 bytes
|
0.52
|
For a method such as:
static async Task<int> CallerAsync() => await CalleeAsync();
with runtime async enabled, the C# compiler generates IL like the following:
; MSIL
.method private hidebysig static
class System.Threading.Tasks.Task`1<int32> CallerAsync() cil managed async
{
call class System.Threading.Tasks.Task`1<int32> CalleeAsync()
call int32 System.Runtime.CompilerServices.AsyncHelpers::Await<int32>(
class System.Threading.Tasks.Task`1<int32>)
ret
}
There is no generated
<CallerAsync>d__0
type, no
IAsyncStateMachine
, no
MoveNext
, no
AsyncTaskMethodBuilder<int>
, and no
AsyncStateMachineAttribute
. Previously,
async
on a C# method evaporated at compile time. Now, the method has a new
MethodImpl
async
bit, represented in IL assembly syntax by that
async
modifier, and the body calls helpers in
System.Runtime.CompilerServices.AsyncHelpers
.
At first glance the
ret
looks impossible because the declared signature returns
Task<int>
while the value on the IL evaluation stack is an
int
. This clearly isn’t a normal calling convention. The VM can give a
Task
-returning method two related identities, or MethodDescs, where one has the normal signature the rest of managed code sees,
Task<int> CallerAsync()
. The other is the AsyncCall variant, which effectively returns
int
and has an implicit channel for a continuation. Both refer to the same logical method and metadata token, but they have different calling conventions and different jobs. If regular managed code invokes
CallerAsync
, the VM-generated outer thunk preserves the public contract and returns a
Task<int>
. If another runtime async method directly awaits it, the JIT can instead call the AsyncCall variant and receive the result directly when the call completes synchronously, or a continuation when it suspends. In other words, it can hand back the
T
directly and avoid allocating a
Task<T>
.
That pairing works in both directions. For a method compiled with runtime async, the AsyncCall variant owns the generated (newly compact) IL while the public
Task
-returning entry point is an adapter thunk; for a traditionally compiled method, the public method owns its usual IL while the VM can create an AsyncCall adapter around it. That means runtime async code remains able to await existing libraries and code compiled by older compilers, a critical capability for our goal of 100% compat. The largest wins naturally appear as more of an async call chain is compiled with runtime async.
This is where the JIT gets an opportunity that simply didn’t exist when every boundary was already expressed as a task and a generated state machine. Suppose
A
awaits
B
, which awaits
C
:
static async Task<int> A(bool yield) => await B(yield);
static async Task<int> B(bool yield) => await C(yield);
static async Task<int> C(bool yield)
{
if (yield)
await Task.Yield();
return 42;
}
Traditionally, each method has its own compiler-generated state machine and its own task-like result.
C
suspends and eventually completes its task, which wakes
B
‘s state machine;
B
then completes its task, which wakes
A
‘s state machine; and
A
completes the root task observed by the caller. There has been an enormous amount of work done over the years to reduce the costs of those objects and transitions.
With runtime async, the importer recognizes the adjacent pattern of “call a Task-returning method, then await that task.” In the simple case it can call the callee’s AsyncCall variant instead. When
yield
is false and
C
completes synchronously, the
int
flows back through
B
and
A
as a plain value, and only the outermost boundary needs to turn it into the
Task<int>
promised to the original caller. When
yield
is true and
C
suspends, the runtime links continuation state for the chain and eventually resumes it without requiring an intermediate
Task<int>
at every directly fused edge. The
Task
contract hasn’t vanished, it just moved to the place where a
Task
is actually needed.
Runtime async doesn’t make every asynchronous operation allocation-free, though. Rather, it gives the JIT enough information to avoid materializing some task objects that existed only to carry a result from one async method directly into the next. If a consumer stores the task in a collection, manually hooks up a continuation, or otherwise observes the task as an object, that object is still needed. The optimization is about not paying for boundaries that aren’t observably boundaries.
The impact is already visible with just two layers:
// dotnet run -c Release -f net11.0 --filter "*"
// The project also needs the `runtime-async=on` feature switch set.
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Configs;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[GroupBenchmarksBy(BenchmarkLogicalGroupRule.ByCategory)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly Task<int> s_completed = Task.FromResult(42);
[Benchmark(Baseline = true), BenchmarkCategory("Completed")]
public Task<int> ClassicCompleted() => ClassicCompletedOuter();
[Benchmark, BenchmarkCategory("Completed")]
public Task<int> RuntimeCompleted() => RuntimeCompletedOuter();
[Benchmark(Baseline = true), BenchmarkCategory("Yielding")]
public Task<int> ClassicYielding() => ClassicYieldingOuter();
[Benchmark, BenchmarkCategory("Yielding")]
public Task<int> RuntimeYielding() => RuntimeYieldingOuter();
[RuntimeAsyncMethodGeneration(false)]
private static async Task<int> ClassicCompletedOuter() => await ClassicCompletedInner();
[RuntimeAsyncMethodGeneration(false)]
private static async Task<int> ClassicCompletedInner() => await s_completed;
private static async Task<int> RuntimeCompletedOuter() => await RuntimeCompletedInner();
private static async Task<int> RuntimeCompletedInner() => await s_completed;
[RuntimeAsyncMethodGeneration(false)]
private static async Task<int> ClassicYieldingOuter() => await ClassicYieldingInner();
[RuntimeAsyncMethodGeneration(false)]
private static async Task<int> ClassicYieldingInner()
{
await Task.Yield();
return 42;
}
private static async Task<int> RuntimeYieldingOuter() => await RuntimeYieldingInner();
private static async Task<int> RuntimeYieldingInner()
{
await Task.Yield();
return 42;
}
}
namespace System.Runtime.CompilerServices
{
[AttributeUsage(AttributeTargets.Method)]
internal sealed class RuntimeAsyncMethodGenerationAttribute(bool runtimeAsync) : Attribute
{
public bool RuntimeAsync => runtimeAsync;
}
}
|
Method
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
ClassicCompleted
|
21.221 ns
|
1.00
|
144 B
|
1.00
|
|
RuntimeCompleted
|
6.151 ns
|
0.29
|
0 B
|
0.00
|
|
ClassicYielding
|
254.139 ns
|
1.00
|
248 B
|
1.00
|
|
RuntimeYielding
|
116.927 ns
|
0.46
|
168 B
|
0.68
|
The synchronously completing chain is more than 3x faster and avoids both
intermediate task allocations. Even after a real suspension, the same
two-layer chain takes less than half the time and allocates 80 fewer bytes.
Exception handling amplifies the difference. Again consider an async method
A
calling an async method
B
calling an async method
C
. The transformation generated by the C# compiler of each method results in a
try
/
catch
block around the whole body of the
MoveNext
method so that any unhandled exception can be stored into the returned
Task
. Let’s say code in
C
throws an unhandled exception. That’s then caught by this manufactured
catch
block and stored into the
Task
returned to
B
. The awaiter in
B
then retrieves that exception from the
Task
object and throws it. It’s then caught by
B
‘s generated catch and stored into its
Task
. And so on. An exception crossing ten such async helpers can therefore be thrown, caught, and stored ten times even though none of the source methods has an explicit handler. That is super expensive. But runtime async doesn’t need to re-enter a pass-through frame with no handler. On the synchronous path the exception unwinds through the fused calls normally, and after a real suspension, one dispatch-loop catch walks past continuation records that have no handler and faults the observable root task once.
The following benchmark measures both a fully synchronous throw and an exception after one real
Task.Yield
suspension. It uses a compiler-recognized per-method escape hatch (
RuntimeAsyncMethodGeneration
) so that the classic and runtime async methods run in the same process on the same .NET 11 runtime and differ only in how the compiler lowers them. (Note that this attribute is experimental and isn’t a public API exposed from the core libraries; as with other attributes known to the C# compiler, it recognizes them by name and signature.)
// dotnet run -c Release -f net11.0 --filter "*"
// The project also needs the `runtime-async=on` feature switch set.
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Params(1, 10, 30)]
public int Depth;
[Params(false, true)]
public bool Yield;
[Benchmark(Baseline = true)]
public int Classic() => Invoke(ClassicThrowAsync(Depth));
[Benchmark]
public int Runtime() => Invoke(RuntimeThrowAsync(Depth));
private static int Invoke(Task<int> task)
{
try
{
return task.GetAwaiter().GetResult();
}
catch (InvalidOperationException)
{
return -1;
}
}
[RuntimeAsyncMethodGeneration(false)]
private async Task<int> ClassicThrowAsync(int depth)
{
if (depth == 0)
{
if (Yield) await Task.Yield();
throw new InvalidOperationException("uh oh");
}
return await ClassicThrowAsync(depth - 1);
}
private async Task<int> RuntimeThrowAsync(int depth)
{
if (depth == 0)
{
if (Yield) await Task.Yield();
throw new InvalidOperationException("uh oh");
}
return await RuntimeThrowAsync(depth - 1);
}
}
namespace System.Runtime.CompilerServices
{
[AttributeUsage(AttributeTargets.Method)]
internal sealed class RuntimeAsyncMethodGenerationAttribute(bool runtimeAsync) : Attribute
{
public bool RuntimeAsync => runtimeAsync;
}
}
|
Depth
|
Yield
|
Method
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
1
|
False
|
Classic
|
4.727 μs
|
1.00
|
1.6 KB
|
1.00
|
|
1
|
False
|
Runtime
|
3.558 μs
|
0.75
|
1.16 KB
|
0.72
|
|
1
|
True
|
Classic
|
6.308 μs
|
1.00
|
1.68 KB
|
1.00
|
|
1
|
True
|
Runtime
|
8.211 μs
|
1.30
|
1.42 KB
|
0.85
|
|
10
|
False
|
Classic
|
19.469 μs
|
1.00
|
15.13 KB
|
1.00
|
|
10
|
False
|
Runtime
|
5.885 μs
|
0.30
|
2.13 KB
|
0.14
|
|
10
|
True
|
Classic
|
24.923 μs
|
1.00
|
15.63 KB
|
1.00
|
|
10
|
True
|
Runtime
|
6.122 μs
|
0.25
|
2.88 KB
|
0.18
|
|
30
|
False
|
Classic
|
51.302 μs
|
1.00
|
84.2 KB
|
1.00
|
|
30
|
False
|
Runtime
|
10.721 μs
|
0.21
|
5.71 KB
|
0.07
|
|
30
|
True
|
Classic
|
65.974 μs
|
1.00
|
85.53 KB
|
1.00
|
|
30
|
True
|
Runtime
|
11.254 μs
|
0.17
|
7.72 KB
|
0.09
|
Runtime async supports
Task
,
Task<T>
,
ValueTask
, and
ValueTask<T>
as method return types, but as of today it doesn’t support
async void
, async iterators, or arbitrary custom task-like return types with custom builders; those continue to use the traditional compiler transformation. For
ValueTask<T>
, the existing reasons to use the type still apply. A
ValueTask<T>
can carry a result directly, wrap a
Task<T>
, or refer to an
IValueTaskSource<T>
. That’s made it useful for APIs where synchronous completion is common enough that avoiding a
Task
allocation outweighs the larger return value and the more restrictive consumption rules, or where asynchronous completion can have its costs amortized via a reusable backing object. Runtime async then addresses some of the scenarios that would have led developers to use
ValueTask<T>
. Does that mean everyone should stop using
ValueTask<T>
? No. Choosing
Task
versus
ValueTask
remains an API design decision based on completion patterns, allocation sensitivity, call frequency, and how consumers need to use the result. Write the return type that makes sense for the API, then let the compiler, VM, and JIT optimize it as best they can.
Workloads with many layers of small async methods can benefit the most from runtime
async, because those layers are exactly where intermediate tasks and state
machines often accumulate. Shared framework code, for example, is full of this
pattern: a public method validates arguments and awaits a private helper, which
awaits a transport helper, which awaits an operating-system operation.
Application services similarly compose authentication, retry, logging,
serialization, and I/O helpers. Runtime async can make the source-level
decomposition cheaper without asking the developer to flatten the code into
one giant method in order to avoid “implementation detail” costs.
The work required to reach this point has been extensive. A GitHub search of the
runtime async tracking label
on September 14, 2026 returned 235 pull requests, far too many for me to enumerate one by one. So I won’t try; you can peruse that label in your spare time. The work is also not only about direct performance improvements but also about
improvements to diagnostics and performance tooling that help you to make better
use of async in your own code. When an async method
suspends, its physical thread stack unwinds. That method’s continuation might later run
on a different thread whose physical stack begins in the thread pool, with the
methods that led to the original
await
nowhere to be found. A sampling
CPU profiler can see where the processor is spending time, but without additional
information, it can’t reliably connect those traces back through the logical async
call chain, making it hard to answer questions about what async call paths were actually costing.
Profiling tools like the async profiler in Visual Studio have traditionally reconstructed those chains from
events emitted by
Task
‘s infrastructure, but async-heavy applications can generate enormous volumes of
those very chatty events. The resulting overhead easily perturbs the workload being measured, making
it all but unusable in production.
dotnet/runtime#127238
added a
new lightweight async-profiler event stream for .NET 11 and runtime async. Rather than sending every small
transition through the eventing system as its own full event, the runtime
writes compact records into per-thread buffers, delta-encoding timestamps and
instruction pointers and flushing the data in batches. It also puts a small
identifiable wrapper frame into the physical stack when invoking a
continuation. A profiler can use that frame as an anchor, joining ordinary CPU
samples to the logical async call stack represented by the event stream. In some measurements,
this new approach added less than 1% overhead and shrank the traced data by an order of magnitude.
dotnet/runtime#129043
and a few follow-up PRs extended
the same approach to the compiler-generated state machines used by existing
async code. Thus this
isn’t useful only to applications that opt into runtime async; tooling gets one
consistent representation across both implementations.
What should you as a developer do differently with runtime async in the picture? Mostly nothing. Keep writing asynchronous code the way you want it to read, and break a large operation into helpers when that makes the code clearer. Use
Task
by default and choose
ValueTask
where its API and usage tradeoffs genuinely fit. And don’t contort source code to remove a clean
await
just because today’s implementation might allocate an intermediate
Task
. The lowering strategy should “just work” as an implementation detail, preserve behavior, and make existing source get better as the runtime improves.
Bounds Checks
C# is a memory-safe language. Accesses to arrays, strings, and spans are guaranteed by the runtime to be in-bounds; if you try to access
someArray[i]
,
someString[i]
, or
someSpan[i]
with an index less than 0 or greater than or equal to the length of the array/string/span, you’ll get an exception, not silently corrupted memory or a process crash. The runtime guarantees that all permitted accesses are within bounds, and that means it needs to be able to prove the access is in bounds. The main method the JIT has for achieving that is by injecting code that performs a bounds check, as if instead of:
int[] array = ...;
int value = array[i];
you’d written:
int[] array = ...;
if ((uint)i >= array.Length) throw new IndexOutOfRangeException();
int value = array[i];
At the assembly level, a bounds check looks something like:
; x64
cmp ecx, dword ptr [rax+8] ; compare index with array length
jae THROW ; unsigned index >= length
mov edx, dword ptr [rax+rcx*4+16] ; load the element
The JIT could just inject such code on every access and call it a day, but such code adds overhead, so the JIT works to elide those checks and that overhead wherever it can prove the index is valid. Proving an index is valid means the JIT needs to be able to see from other evidence that it couldn’t possibly be out of bounds.
The quintessential example of that is a
for
loop over the full contents of an array or span:
for (int i = 0; i < array.Length; i++)
{
Use(array[i]);
}
The JIT recognizes from this idiom that, within the loop body,
i
is guaranteed to be in the range
[0, array.Length)
, and avoids emitting the bounds check for the
array[i]
access. The JIT has long handled this particular case. Other cases, not so much. Bounds-check elimination has improved in virtually every .NET release; more recent releases added range propagation for derived expressions (
.NET 7
and
.NET 8
saw significant improvements here), SSA-based reasoning (
.NET 9
), and better handling of
Span<T>
, whose length sits in a field rather than an object header, complicating tracking. Each year, the developers contributing to the JIT find new patterns that were being missed, that show up in the wild, and that are fixable. .NET 11 improves several such patterns.
Range analysis in the JIT tracks intervals for each variable, an upper bound and a lower bound. For example, taking the true branch of
x < 5
gives the range for
x
in that branch an upper bound of 4 while taking the true branch of
x > 2
makes the lower bound 3. What about
x != 5
? On the true edge, we know
x
isn’t 5, and if the current range for
x
is
[5, 10]
, then we know the range must actually be
[6, 10]
… the lower bound can be tightened because the only value at the lower end is excluded. Similarly, if the range is
[0, 5]
, an
x != 5
assertion tells us the range is actually the narrower
[0, 4]
. Or, at least, that’s what you’d hope it would do. The JIT had this relevant comment:
// We have a != assertion, but it doesn't tell us much about the interval. So just skip it.
continue;
In .NET 11,
dotnet/runtime#121273
replaces that logic with productive reasoning. It checks whether the excluded constant is at either edge of the currently tracked range, adding in the new insights if so. C# list patterns, introduced in C# 11, generate just such comparison sequences. For example, the pattern
name is [] or [':'] or [':', not ':', ..]
lowers to something like this:
if (name != null)
{
int num = name.Length;
if (num == 0) return true;
if (num == 1)
{
if (name[0] == ':') return true;
}
else if (name[0] == ':' && name[1] != ':')
{
return true;
}
return false;
}
Range analysis then proceeds with something like this:
-
We know that
Array.Length
is never negative, so it has a range of
[0, Array.MaxLength]
.
-
On the false edge of
num == 0
, we know that
num != 0
, so the range is narrowed now to
[1, Array.MaxLength]
.
-
Similarly, on the false edge of
num == 1
, we know that
num != 1
, so the range is narrowed now to
[2, Array.MaxLength]
.
-
We then access
name[0]
and
name[1]
, both of which are guaranteed in bounds based on the lower bound of 2 that was established.
Without the
!= constant
tightening, that narrowing wouldn’t happen, and the bounds checks in step 4 couldn’t be elided. Thankfully, they now can be in .NET 11. Consider this example:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private string[] _inputs = ["", ":", ":x", "abc", ":ab", "x", "ab:cd"];
[Benchmark]
public int ClassifyAll()
{
int total = 0;
foreach (string s in _inputs) total += Classify(s);
return total;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static int Classify(ReadOnlySpan<char> name) =>
name switch
{
[] => 0,
[':'] => 1,
[':', not ':', ..] => 10 + name[0] + name[1],
_ => 3
};
}
In .NET 10, we can see the call to
CORINFO_HELP_RNGCHKFAIL
at the bottom of the method. That’s the tell-tale sign there was at least one bounds check in the method. With .NET 11, that sign is removed.
; Arm64
--- .NET 10
+++ .NET 11
@@ -10,17 +10,15 @@
beq G_M000_IG08
G_M000_IG04:
- ldrh w2, [x0]
- cmp w2, #58
+ ldrh w1, [x0]
+ cmp w1, #58
bne G_M000_IG06
G_M000_IG05:
- cmp w1, #1
- bls G_M000_IG11
ldrh w0, [x0, #0x02]
cmp w0, #58
beq G_M000_IG06
- add w0, w2, w0
+ add w0, w1, w0
add w0, w0, #10
b G_M000_IG07
@@ -44,8 +42,4 @@
mov w0, wzr
b G_M000_IG07
-G_M000_IG11:
- bl CORINFO_HELP_RNGCHKFAIL
- brk #0
-
-; Total bytes of code 112
+; Total bytes of code 96
“Assertion” machinery in the JIT propagates learned facts (like the aforementioned range information) between “basic blocks” (a sequence of instructions with one entry point, one exit point, and no branches into or out of the middle of it), so information established in block A flows to block B if A “dominates” B (meaning the only way to get to B is through A). But what about facts established earlier within the same block? That’s the gap that
dotnet/runtime#121527
addresses. Consider this code:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int[] _arr = new int[512];
[Benchmark]
public int RunMany()
{
int touched = 0;
for (int i = 0; i < _arr.Length - 2; i++)
{
Test(_arr, i);
touched++;
}
return touched;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static void Test(int[] arr, int i)
{
arr[i] = 0; // 1: establishes 'i >= 0 && i < arr.Length'
i++; // 2: same block
if (i < arr.Length) arr[i] = 0; // 3: proven safe from 1's assertion
}
}
Statements 1, 2, and 3 are all in the same basic block, up to the conditional; after statement 1 executes, if we reach statement 2, the bounds check on statement 1 passed, we know
i >= 0
and
i < arr.Length
, and after statement 2,
i
becomes
i + 1
. After the
if
guard
i < arr.Length
we know the incremented
i
is still within bounds. But when the range check pass in the .NET 10 JIT examined statement 3’s bounds check, it saw the assertions propagated from predecessor blocks. Since the assertion from statement 1 is generated within the current block, the range check couldn’t see it. The PR fixed it to walk the current block’s tree in execution order, accumulating assertions as it went. When we reach statement 3’s bounds check, we’ve already walked past statement 1 and picked up its
i >= 0 && i < arr.Length
assertion.
; Arm64
--- .NET 10
+++ .NET 11
@@ -13,8 +13,6 @@
ble G_M000_IG04
G_M000_IG03:
- cmp w1, w2
- bhs G_M000_IG05
str wzr, [x0, w1, UXTW #2]
G_M000_IG04:
@@ -25,4 +23,4 @@
bl CORINFO_HELP_RNGCHKFAIL
brk #0
-; Total bytes of code 68
+; Total bytes of code 60
There are almost an infinite number of things the JIT could look for and special-case. But every special case requires code, maintenance, and, most importantly, compilation time. A “just-in-time” compiler typically runs while the application is running, so the JIT itself must be optimized and spend its limited budget only where there’s a likely payoff. That pushes the developers building it toward patterns that occur in real workloads. One such pattern, often seen in libraries like format decoders, builds a table
index with bitwise operations on a byte, for example
((b & 0x03) << 4) | ((b & 0xf0) >> 4)
. Each masked piece has a tiny upper
bound, so the OR of those pieces is always in
[0..63]
, safely in range for
e.g. a Base64 alphabet table. Until
dotnet/runtime#122263
, the JIT
often failed to prove that combined bound and left a bounds check on the
index. Existing range-check code understood the upper bounds produced by
bitwise AND and shifts, but not OR; the change lets the JIT combine the known
bounds of both OR operands and remove the remaining array check.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly byte[] _input = new byte[4096];
[GlobalSetup]
public void Setup() => new Random(42).NextBytes(_input);
[Benchmark]
public int Base64LikeIndex() => Sum(_input);
[MethodImpl(MethodImplOptions.NoInlining)]
private static int Sum(ReadOnlySpan<byte> input)
{
int sum = 0;
foreach (byte b in input)
{
int index = ((b & 0x03) << 4) | ((b & 0xF0) >> 4);
sum += "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/="u8[index];
}
return sum;
}
}
The .NET 10 assembly checks the computed index against the 65-byte lookup
table on every iteration. In .NET 11, range analysis proves the index is at
most 63, so both the comparison and the branch to the range-check failure
helper disappear:
; x64
M01_L00:
movzx r9d, byte ptr [rdx+r8]
mov r11d, r9d
and r11d, 3
shl r11d, 4
and r9d, 0F0
sar r9d, 4
or r9d, r11d
- cmp r9d, 41
- jae short M01_L02
movzx r9d, byte ptr [r10+r9]
add eax, r9d
inc r8d
cmp r8d, ecx
jl short M01_L00
-M01_L02:
- call CORINFO_HELP_RNGCHKFAIL
- int 3
-
-; Total bytes of code 95
+; Total bytes of code 79
As another example,
dotnet/runtime#125056
improves the handling of guards like
(uint)i < span.Length
that are pervasive in performance-sensitive code. Consider this benchmark:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int[] _data = Enumerable.Range(0, 512).ToArray();
[Benchmark]
public int RunMany()
{
int sum = 0;
for (int i = 0; i < _data.Length; i++)
sum += Test(_data, i);
return sum;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static int Test(Span<int> span, int i)
{
if ((uint)i < (uint)span.Length)
{
if (i != 0)
return span[i - 1] + span[i];
return span[i];
}
return 0;
}
}
Because the comparison is unsigned,
(uint)i
would be a large positive number if
i
were negative, making it impossible for
(uint)i < (uint)span.Length
to be true (since a span’s length is never negative,
(uint)span.Length
is at most
int.MaxValue
). Inside the true branch,
i
is therefore in
[0, span.Length - 1]
. Previously, the JIT wasn’t always recording the lower bound
i >= 0
when it processed the
(uint)i < span.Length
assertion, and that could leave bounds checks on expressions like
i - 1
in place. The fix adds the
[0, int.MaxValue - 1]
lower bound deduction for the index variable upon entering the true arm of a
(uint)i < span.Length
check. Combined with the existing range tracking for the upper bound, this gives the JIT a complete picture of
i
‘s range inside the guarded block.
; Arm64
--- .NET 10
+++ .NET 11
@@ -8,10 +8,8 @@
cbz w2, G_M000_IG05
G_M000_IG03:
- sub w3, w2, #1
- cmp w3, w1
- bhs G_M000_IG09
- ldr w1, [x0, w3, UXTW #2]
+ sub w1, w2, #1
+ ldr w1, [x0, w1, UXTW #2]
ldr w0, [x0, w2, UXTW #2]
add w0, w1, w0
@@ -33,8 +31,4 @@
ldp fp, lr, [sp], #0x10
ret lr
-G_M000_IG09:
- bl CORINFO_HELP_RNGCHKFAIL
- brk #0
-
-; Total bytes of code 84
+; Total bytes of code 68
Bounds check elision is generally based on forms of range analysis, where the JIT needs to prove that a given index is guaranteed to be within the range of the data structure. But the same range analysis-based facts can prove that other checks are unnecessary. For example, once the JIT knows that an integer is in
[0..100]
, it can prove both that converting it to
byte
can’t lose data and that multiplying it by 10 can’t overflow.
dotnet/runtime#124147
enables the JIT to use such facts to avoid unnecessary branches as part of
checked
operations. When range analysis proves that the operands are in ranges whose result can’t overflow, making
checked
a nop, the backend can now emit plain add/multiply/subtract instructions, without the jump to failure, as in the following example:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _array = new int[99];
[Benchmark]
public int ArrayLengthPlusConstant() => AddToLength(_array);
[MethodImpl(MethodImplOptions.NoInlining)]
private static int AddToLength(int[] array) => checked(array.Length + 10);
[Benchmark]
public int GuardedLengthTimesConstant() => Multiply(_array);
[MethodImpl(MethodImplOptions.NoInlining)]
private static int Multiply(Span<int> span)
{
if (span.Length >= 100) return 0;
return checked(span.Length * 10);
}
}
; Arm64
--- .NET 10
+++ .NET 11
G_M000_IG02:
cmp w1, #100
bge G_M000_IG05
G_M000_IG03:
mov w0, #10
- smull x0, w1, w0
- lsr x2, x0, #32
- cmp w2, w0, ASR #31
+ mul w0, w1, w0
- bne G_M000_IG07
G_M000_IG04:
ldp fp, lr, [sp], #0x10
ret lr
-G_M000_IG07:
- bl CORINFO_HELP_OVERFLOW
- brk #0
-
-; Total bytes of code 64
+; Total bytes of code 44
That makes the change broadly applicable: any time you write
checked
arithmetic on quantities that are inherently bounded, such as collection counts, lengths, or indices constrained by prior comparisons, the JIT now has a chance to prove at compile time that the overflow can’t happen and thus eliminate the run-time check entirely. Building on that range-check work,
dotnet/runtime#124184
teaches the JIT to eliminate “narrowing casts” under the same kinds of guards:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private uint _value = 100;
[Benchmark]
public byte GuardedNarrowingCast() => Narrow(_value);
[MethodImpl(MethodImplOptions.NoInlining)]
private static byte Narrow(uint value)
{
if (value > 100) return 0;
return checked((byte)value);
}
}
; Arm64
--- .NET 10
+++ .NET 11
@@ -4,23 +4,10 @@
G_M000_IG02:
cmp w0, #100
- bhi G_M000_IG04
- cmp w0, #255
- bhi G_M000_IG06
+ csel w0, w0, wzr, ls
G_M000_IG03:
ldp fp, lr, [sp], #0x10
ret lr
-G_M000_IG04:
- mov w0, wzr
-
-G_M000_IG05:
- ldp fp, lr, [sp], #0x10
- ret lr
-
-G_M000_IG06:
- bl CORINFO_HELP_OVERFLOW
- brk #0
-
-; Total bytes of code 52
+; Total bytes of code 24
Such use of
checked
is common in serialization and protocol code where you validate a value’s range prior to truncating it. In this benchmark I’ve used
checked
explicitly, but the more common form is with the whole project compiled with
<CheckForOverflowUnderflow>true</CheckForOverflowUnderflow>
in the .csproj, such that this
checked
becomes implicit. After the change, the range analysis sees that
value
is in the range
[0, 100]
, knows
byte
fits values up to 255, and elides the check.
dotnet/runtime#128620
further teaches range analysis the possible results of leading-zero count, trailing-zero count, and population count instructions. Those results are often used to index small lookup tables… knowing their bounds lets the JIT remove the bounds check.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly int[] s_lookup =
Enumerable.Range(0, 33).Select(i => i * i).ToArray();
private uint[] _values;
[GlobalSetup]
public void Setup()
{
Random rng = new(42);
_values = Enumerable.Range(0, 1024).Select(i => (uint)rng.Next(1, int.MaxValue)).ToArray();
}
[Benchmark]
public int SumLookupByLeadingZeroCount()
{
int sum = 0;
foreach (var v in _values)
sum += s_lookup[BitOperations.LeadingZeroCount(v)];
return sum;
}
}
The lookup improves because the JIT now knows
LeadingZeroCount(uint)
is between 0 and 32 and can remove the bounds check.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SumLookupByLeadingZeroCount
|
.NET 10.0
|
516.1 ns
|
1.00
|
|
SumLookupByLeadingZeroCount
|
.NET 11.0
|
438.5 ns
|
0.85
|
The JIT is also able to conditionally apply range check-based elision via “cloning”. Cloning is a mechanism where the JIT takes one piece of code and duplicates it. One of the copies it leaves as it was originally, and the other copy it special cases. So, for example, if you had code like:
int value = array[i];
the JIT could theoretically clone that in order to avoid the implicit bounds check, e.g.
int value;
if ((uint)i < array.Length)
{
// no bounds check emitted by JIT, e.g.
value = Unsafe.Add(ref MemoryMarshal.GetArrayDataReference(array), i);
}
else
{
// bounds check emitted
value = array[i];
}
That particular code looks silly, as we’re just trading an implicit bounds check for an explicit one. It becomes less silly when the JIT is able to elide multiple bounds checks with a single branch, e.g.
int sum;
if (4 < array.Length)
{
// zero bounds checks
ref int startRef = ref MemoryMarshal.GetArrayDataReference(array);
sum =
startRef +
Unsafe.Add(ref startRef, 1) +
Unsafe.Add(ref startRef, 2) +
Unsafe.Add(ref startRef, 3);
}
else
{
// potentially four bounds checks
sum =
array[0] +
array[1] +
array[2] +
array[3];
}
Such optimizations are already handled in the JIT, via its
optRangeCheckCloning
phase. It groups bounds checks from a basic block, emits one guard for the largest required range, and duplicates the affected code into a fast path where the individual checks can be removed and a fallback path where they remain. However, one long-standing limitation of range-check cloning is that it refused to process the last statement of any “terminator” block, a block that ends with a jump or return instruction. For a method like:
static int ArrayAccess(int[] abcd) => abcd[0] + abcd[1] + abcd[2] + abcd[3];
all four array accesses live in the return statement, the last statement of a return block, so nothing got cloned and the hot path retained four separate bounds checks. In .NET 11,
dotnet/runtime#124705
removes that restriction, making the return statement eligible for range-check cloning and allowing a single fast-path guard to cover all four accesses.
But even without range-check cloning, there’s really no reason such accesses should require four bounds checks: the JIT should be able to see that the array or span needs to have a length of at least 4 and guard all accesses by that single check. If there were intervening operations that had side effects, the JIT would need to maintain order of operations, at least enough to maintain the observable behavior of those effects, but that’s not the case here. With
dotnet/runtime#127439
in .NET 11, the JIT will now coalesce those checks within a basic block, strengthening the first check to the largest constant index and removing the rest.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _values = Enumerable.Range(0, 16).ToArray();
[Benchmark]
public int Sum16()
{
int[] values = _values;
return
values[0] + values[1] + values[2] + values[3] +
values[4] + values[5] + values[6] + values[7] +
values[8] + values[9] + values[10] + values[11] +
values[12] + values[13] + values[14] + values[15];
}
}
In previous releases, you’d sometimes see a proactive developer doing a similar optimization manually, e.g. reordering the accesses in an example like that to put the largest read first. That’s no longer necessary.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Sum16
|
.NET 10.0
|
2.958 ns
|
1.00
|
|
Sum16
|
.NET 11.0
|
1.828 ns
|
0.62
|
Another bounds checking improvement comes in
dotnet/runtime#127488
, which actually targets explicitly-implemented bounds checks (rather than the implicit ones we’ve been discussing) and targets code that reads a fixed-size value from the end of a span, such as
BinaryPrimitives.ReadInt32BigEndian(span.Slice(span.Length - 4))
behind a
span.Length >= 4
guard, e.g.
if (span.Length >= 4)
{
// Parse an int from the end of the span
... = ReadInt32BigEndian(span.Slice(span.Length - 4));
...
}
There shouldn’t be any additional bounds checking required here. However,
Span.Slice
begins with:
if ((uint)start > (uint)_length)
ThrowHelper.ThrowArgumentOutOfRangeException();
and
ReadInt32BigEndian
begins with:
if (sizeof(T) > source.Length)
ThrowHelper.ThrowArgumentOutOfRangeException();
so even though our
span.Length >= 4
check should have been sufficient, we’re still ending up with two additional checks. To address that, the JIT needed two things.
First, it needed to be able to identify that
x - (x + a)
is the same as
-a
. Without this identity,
length - (length - 4)
is just an opaque subtraction of two expressions with no obvious constant result. With the identity, the JIT can recognize the inner expression
(length - 4)
as
length + (-4)
, apply
x - (x + a) == -a
with
x == length
and
a == -4
, and end up with
-(-4) == 4
. Now
ReadInt32BigEndian
‘s check against 4 becomes
4 >= 4
, which the JIT can trivially see is true.
Second,
Slice(start)
must establish that
start
is between zero and the span’s length. When
start
is
length - 4
, the existing
length >= 4
guard proves the result is non-negative, while subtracting a positive constant means the result can’t exceed
length
. The improved range analysis connects that guard to the subtraction and removes
Slice
‘s check.
Both fixes together mean the above example now elides both extra bounds
checks. That’s useful in particular for libraries like parsers, network
protocol implementations, and cryptographic code, all of which frequently on
hot paths do things like “read the last N bytes of a buffer.”
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Buffers.Binary;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly byte[] _buffer = new byte[64];
[Benchmark]
public int ReadLastInt32() => ReadLastInt32(_buffer);
[MethodImpl(MethodImplOptions.NoInlining)]
private static int ReadLastInt32(ReadOnlySpan<byte> span)
{
if (span.Length >= sizeof(int))
{
return BinaryPrimitives.ReadInt32BigEndian(span.Slice(span.Length - sizeof(int)));
}
return -1;
}
}
In .NET 10, the helper is 73 bytes and includes both additional checks and
their throw paths:
; x64
cmp ecx,4
jl RETURN_MINUS_ONE
lea edx,[rcx-4]
cmp edx,ecx
ja THROW_SLICE
mov r8d,edx
add rax,r8
sub ecx,edx
cmp ecx,4
jl THROW_READ
movbe eax,[rax]
In .NET 11, the helper is 28 bytes, and only the original length guard remains:
; x64
cmp ecx,4
jl RETURN_MINUS_ONE
add ecx,-4
add rax,rcx
movbe eax,[rax]
dotnet/runtime#122040
and
dotnet/runtime#127117
similarly help to remove bounds checks involving
span.Slice
. Vectorized loops often work through a span a chunk at a time, slicing off the elements they’ve already processed. The JIT hasn’t always been able to keep track of how those progressively smaller slices relate to the original span, so it could end up checking the same limits again on each iteration. These changes improve that tracking, enabling more of those repeated checks to be removed.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _data = Enumerable.Repeat(1, 1_024).ToArray();
[Benchmark]
public Vector256<int> CreateFromSlice() => CreateFromSlice(_data);
[Benchmark]
public int SumSliced() => SumSliced(_data);
[MethodImpl(MethodImplOptions.NoInlining)]
private static Vector256<int> CreateFromSlice(Span<int> values)
{
if (values.Length < 16)
return default;
return Vector256.Create(values.Slice(8));
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static int SumSliced(ReadOnlySpan<int> data)
{
Vector128<int> sum = default;
while (data.Length >= Vector128<int>.Count)
{
sum += Vector128.Create(data);
data = data.Slice(Vector128<int>.Count);
}
int result = Vector128.Sum(sum);
foreach (int value in data)
result += value;
return result;
}
}
In .NET 10, the loop condition proves that at least one vector remains, but
the construction of the vector from the current span performs the same check
again. .NET 11 retains the length relationship, so
the loop body begins directly with the vector addition:
; x64, vector loop
-cmp esi, 4
-jl THROW_ARGUMENT_OUT_OF_RANGE
-vpaddd xmm6, xmm6, [rbx]
-add rbx, 10
-add esi, 0FFFFFFFC
-cmp esi, 4
+vpaddd xmm0, xmm0, [rax]
+add rax, 10
+add ecx, 0FFFFFFFC
+cmp ecx, 4
jge LOOP
We saw earlier how range-check cloning enables duplicating a sequence of instructions in order to eliminate bounds checks. “Loop cloning” extends that to a whole loop. Consider a loop that processes the first
count
elements of an array:
for (int i = 0; i < count; i++)
sum += values[i];
The test
i < count
doesn’t by itself prove that
i < values.Length
, so by default the compilation would need a bounds check in the body, which would mean a bounds check for every
values[i]
access. Loop cloning gives the JIT another option. Instead of generating the equivalent of:
for (int i = 0; i < count; i++)
sum += values[i]; // bounds check!
it can generate the equivalent of:
if ((uint)count <= (uint)values.Length)
{
// no bounds checks
ref int startRef = ref MemoryMarshal.GetArrayDataReference(values);
for (int i = 0; i < count; i++)
{
sum += Unsafe.Add(ref startRef, i);
}
}
else
{
// bounds check per iteration
for (int i = 0; i < count; i++)
{
sum += values[i];
}
}
For the common case where the iteration is in bounds, execution proceeds through a cloned loop with no per-iteration bounds checks, whereas the original checked loop remains as the fallback that preserves exceptional behavior for invalid inputs. The normal path pays for one guard and avoids a check on every iteration, but that comes at the expense of duplicating code. The JIT therefore needs to apply the optimization selectively.
The JIT has long employed loop cloning, but it didn’t always kick in even in cases it seemed applicable. The previous example showed loop cloning with
<
in the iteration condition. For whatever reason, however, some developers used
!=
, and loop cloning didn’t apply (I’m guessing they used
!=
because they thought it was more efficient, and they actually end up deoptimizing). Thanks to
dotnet/runtime#129268
, in .NET 11
!=
is now also handled, as long as specific conditions are met, such as the stride being exactly 1 or -1, e.g.
i++
qualifies, while
i += 2
doesn’t.
dotnet/runtime#129303
also improves loops that terminate with
i != bound
, giving the JIT a tighter understanding of the values
i
can take and allowing it to remove some bounds checks even when it can’t clone the whole loop.
Lookahead in arrays and spans is another recurring pattern, especially in parsers.
dotnet/runtime#124242
and
dotnet/runtime#125235
recognize conditions such as
(uint)(i + 2) < (uint)span.Length
and use that relation to remove the follow-on checks for
span[i + 1]
and
span[i + 2]
. Consider this benchmark:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System;
using System.Linq;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _text = string.Concat(Enumerable.Repeat("%FE", 128));
[Benchmark]
public bool ContainsPercentFF()
{
ReadOnlySpan<char> span = _text;
for (int i = 0; i < span.Length; i++)
{
if (span[i] == '%' &&
(uint)(i + 2) < (uint)span.Length &&
span[i + 1] == 'F' &&
span[i + 2] == 'F')
{
return true;
}
}
return false;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ContainsPercentFF
|
.NET 10.0
|
232.1 ns
|
1.00
|
|
ContainsPercentFF
|
.NET 11.0
|
194.9 ns
|
0.84
|
Several smaller changes broaden the range of code from which the JIT can remove bounds checks:
-
dotnet/runtime#121640
helps in a situation where once an access using a chosen index has been checked, a later access to the same array at that index need not be checked again.
-
dotnet/runtime#121683
enables the JIT to trace an array’s length through calculations performed earlier in the method, exposing more redundant checks, including some involving index-from-end expressions.
-
dotnet/runtime#124387
and
dotnet/runtime#130326
teach the optimizer to rely on a span’s length always being non-negative.
-
dotnet/runtime#124571
improves sequences of index-from-end accesses: once an access like
arr[^4]
establishes that the array has at least four elements, the JIT reuses that information for nearby accesses such as
arr[^3]
.
-
dotnet/runtime#129101
improves how the JIT combines and carries forward the possible ranges of arithmetic expressions, including expressions involving bitwise OR and unsigned division. Those tighter ranges can show that more values are non-negative or within bounds.
Bounds-check elimination is only one payoff from understanding a loop’s structure. The JIT analyzes induction variables (values like loop counters that change predictably each iteration) and puts loops into standard forms so that later optimizations can reason about them. .NET 11 broadens the range of loops for which that works:
-
dotnet/runtime#122184
recognizes another representation of a 32-to-64-bit zero extension. That lets pointer loops using expressions such as
data[(uint)i]
replace the repeated index extension and address calculation with a pointer increment.
-
dotnet/runtime#119537
follows simple control-flow predecessors when finding an induction variable’s initialization and zero-trip test, while
dotnet/runtime#128303
gives loops with multiple backedges a single canonical latch block.
-
dotnet/runtime#128532
makes loop cloning tolerate more statements around the update and test.
-
dotnet/runtime#129309
extends cloning to more span loops with non-unit strides and offset limits.
-
dotnet/runtime#129349
handles large strides in array loops with an explicit safety guard rather than rejecting them outright.
-
dotnet/runtime#129472
allows loop inversion to spend more of its budget on likely cloning candidates.
-
dotnet/runtime#130205
removes comparisons that are redundant given the induction variable’s known range.
-
dotnet/runtime#131362
corrects profile weights after inversion changes a loop’s exit.
Much of this work wasn’t motivated by contrived benchmarks containing nothing
but array indexing as I’m prone to use in these posts. Rather, many of the improvements
stemmed from an ongoing audit of unsafe code throughout the
.NET libraries, part of a broader
effort to improve memory safety in .NET
. .NET and C# are memory safe, but as with other memory safe languages like Rust,
it provides escape hatches that enable turning off the guardrails provided by the compiler and runtime.
This effort is about reducing where and when developers feel compelled to use those escape hatches, since every
occurrence is an opportunity for increased risk. Unsafe code was often introduced years earlier to manually avoid bounds
checks, typically by walking a buffer with pointers, byrefs, or
Unsafe.Add
.
Sometimes the audit found that the unsafe code was no longer needed and could
simply be removed. Sometimes a “safe” rewrite (meaning not using
unsafe
and friends) was already just as fast or even faster.
And sometimes the rewrite exposed an optimization the JIT was missing, in which
case the answer was to improve the JIT and then rewrite the library code to use
normal, bounds-checked C#. Several of the optimizations discussed in this
section are the result of exactly that feedback loop.
dotnet/runtime#127429
is a
particularly nice example. The vectorized implementation of
Enumerable.Sum
used
MemoryMarshal.GetReference
,
Vector.LoadUnsafe
, and
Unsafe.Add
to walk
its input without bounds checks. With the span-slicing improvements described
earlier, it could instead use
Vector.Create(span)
,
span.Slice(...)
, and a
foreach
for the tail. That’s easier to reason about, removes the unchecked
indexing, and ended up being faster.
dotnet/runtime#114757
similarly
replaced an unsafe pointer-based header-name accessor with a generic
ReadOnlySpan<T>
implementation without loss of performance.
Similarly,
dotnet/runtime#121270
removed
more unsafe code from
Uri
parsing and actually improved performance of the cited code measurably.
There’s a useful “go do” here for libraries outside of dotnet/runtime, as well.
Unsafe code written to work around the JIT is a snapshot of what the JIT could
do at the time that code was written. If you own code that has hand-written pointer or
Unsafe
-based loops whose purpose is to avoid bounds checks, it’s worth
rewriting them with safe, bounds-checked C# and measuring again on .NET 11.
Chances are, you’ll find the gap at this point is either non-existent or small
enough that it’s not worth the increased maintenance and risk for managing the safety yourself.
And if the revised version is still slower, that’s a great opportunity for you to share a repro
in the dotnet/runtime repo, hopefully serving as inspiration for one of the first performance improvements
to go into the JIT for .NET 12.
unsafe
code is still necessary for scenarios like interop,
but performance alone shouldn’t be a permanent reason to eschew all the valuable guardrails .NET provides.
The
C# 15 memory-safety preview
pushes in the same direction and is part and parcel of this effort. Historically, C# has largely equated pointers
with unsafe code: simply declaring or manipulating a pointer generally required
an
unsafe
context, even if the code never accessed the memory to which it
points. In the preview, pointer plumbing such as declaring a pointer, taking an
address with
&
, using
fixed
, converting
stackalloc
to a pointer, and
applying
sizeof
to an unmanaged type no longer requires an
unsafe
context.
Operations that actually access the pointed-to memory, including
*p
,
p->member
, and
p[i]
, still do. C# 15 also adds an
unsafe(expression)
form,
analogous to
checked(expression)
, so an unsafe context can cover one precise
expression rather than a larger statement block. Those changes are the first preview slice of a larger, multi-release
unsafe evolution
.
The end goal is to make unsafe regions smaller, make their assumptions visible through the call graph,
and make them easier for reviewers and tools to find. Pairing that with a JIT
that makes idiomatic safe code fast removes a lot of the historical pressure to
use unsafe code in the first place.
Assertion Propagation
As discussed earlier, the JIT continually learns facts while compiling a method: a value equals a constant, a reference isn’t null, an integer falls within a particular range, and so on. “Assertion propagation” carries those facts forward so they can simplify later code. “Value numbering” complements it by letting the JIT recognize when two expressions compute the same value, even if they appear in different places or use different variables. Together, these mechanisms enable optimizations such as removing redundant null and bounds checks, folding conditions to constants, and reusing repeated computations. .NET 11 improves assertion propagation primarily by fixing places where useful facts were either never recorded or weren’t recognized later.
For example, reading an array’s length normally carries an implicit null-check: if the array reference is
null
, the read must throw. Once global assertion propagation already knows the reference is non-null, however, we should be able to avoid the implicit null check. In .NET 11,
dotnet/runtime#124291
takes care of that for
Array.Length
:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _values = new int[1024];
[Benchmark]
public void DeadLength() => Test(_values);
[MethodImpl(MethodImplOptions.NoInlining)]
private static void Test(int[]? values)
{
if (values is not null)
_ = values.Length;
}
}
The .NET 10 code still tests the reference and reads the length. In .NET 11, the guard proves the read can’t throw, and since its result isn’t used, the access disappears:
; Arm64
--- .NET 10
+++ .NET 11
G_M000_IG01:
stp fp, lr, [sp, #-0x10]!
mov fp, sp
G_M000_IG02:
- cbz x0, G_M000_IG04
-
-G_M000_IG03:
- ldr wzr, [x0, #0x08]
-
-G_M000_IG04:
ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 24
+; Total bytes of code 16
dotnet/runtime#119474
improves
the starting point for integer range analysis. The JIT now uses facts inherent
in a value itself, e.g. a constant has one exact value, while a value converted
to
byte
, for example, must be between 0 and 255. That can eliminate bounds
checks and conditions even when no preceding
if
explicitly established the
range.
dotnet/runtime#124415
further refines this handling of casts, combining what is known about both the
source value and the destination type to derive the tightest useful range.
Those improvements derive ranges from facts inherent in a value, but ranges
can also come from control flow. After
if ((uint)x < 10)
, for example, the
JIT knows that
x
is between 0 and 9 on the true path, which may be enough to
remove a later comparison or array bounds check.
dotnet/runtime#123624
derives tighter ranges from assertions and casts, including proving that some
comparisons are always true or false.
dotnet/runtime#129390
preserves range information more accurately when control-flow paths merge.
Other changes make better use of the ranges once known.
dotnet/runtime#129354
traces values back through their definitions to fold more span- and slice-related comparisons, and
dotnet/runtime#126917
uses narrowed ranges to remove more relational branches.
dotnet/runtime#124711
teaches the JIT to learn implicit facts from operations that have already completed successfully. For example:
-
Creating an array proves its requested length wasn’t negative.
-
A reference-array store may need a runtime covariance check, because a value typed as
object[]
can actually refer to a
string[]
; the helper that performs that type check also validates the index, so if it returns successfully, the index was in range.
-
Integer division or modulo proves the divisor wasn’t zero.
And so on. Those facts can then remove redundant checks and conditions later in the method.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly object?[] _objArr = new object?[8];
private readonly object _value = new();
[Benchmark]
public object? CovariantArrayStore()
{
object?[] objArr = _objArr;
objArr[3] = _value;
return objArr[2];
}
}
A successful store to element 3 proves that particular array has at least four elements; since an array’s length can’t change, the subsequent read of element 2 doesn’t need another bounds check.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
CovariantArrayStore
|
.NET 10.0
|
3.565 ns
|
1.00
|
|
CovariantArrayStore
|
.NET 11.0
|
2.985 ns
|
0.84
|
dotnet/runtime#128522
simplifies how the global assertion pass identifies values, making it less likely to miss a fact learned earlier. One practical impact of this is better propagation of a static
string
‘s known length, which can turn a general string comparison into a fixed-size vectorized comparison.
dotnet/runtime#127810
improves null-check elimination where control flow merges. With
??=
, which is a very common operator used for lazy initialization, the resulting value is non-null whether it came from the existing field or from the newly allocated object. The JIT now combines the facts from both paths and recognizes that the subsequent call doesn’t need another null check.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
Inner? _inner;
[Benchmark]
[Arguments(42)]
public int Invoke(int n) => (_inner ??= new()).Increment(n);
private sealed class Inner
{
[MethodImpl(MethodImplOptions.NoInlining)]
public int Increment(int n) => n + 1;
}
}
The generated code consequently loses the null check on the merged value:
; x64
M00_L00:
mov edx, esi
- cmp [rcx], ecx
call qword ptr [...] ; Inner.Increment(Int32)
-; Total bytes of code 75
+; Total bytes of code 73
dotnet/runtime#128701
removes similarly redundant null checks from copies of structs that contain object references. Such copies use a runtime helper so the garbage collector is correctly notified about the reference writes, but lowering had been adding probes for both source and destination without preserving whether either address could actually fault. It now emits only the probes that are needed.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private FourRefs _src = new()
{
A = new(),
B = new(),
C = new(),
D = new()
};
private FourRefs _dst;
[Benchmark]
public void BulkStructCopy() => _dst = _src;
private struct FourRefs
{
public object? A;
public object? B;
public object? C;
public object? D;
}
}
Both
_src
and
_dst
are fields of the same object, so after probing the source address has established that the object isn’t null, probing the destination address can’t provide any additional information. .NET 11 removes that second probe:
; Arm64
G_M000_IG02:
add x1, x0, #8
ldrsb wzr, [x1]
add x0, x0, #40
- ldrsb wzr, [x0]
movz x2, ...
ldr x3, [x2]
mov x2, #32
blr x3 // CORINFO_HELP_BULK_WRITEBARRIER
-; Total bytes of code 56
+; Total bytes of code 52
Additionally,
dotnet/runtime#125215
lets the JIT retain and efficiently find more assertions in larger methods, increasing the opportunities for the same kinds of simplification. And
dotnet/runtime#129312
removes unnecessary temporary variables when the same simple field address is used multiple times, enabling more efficient loads and stores.
Simplification
Assertion propagation is largely about proving things to help the generated code. Once the JIT knows enough about an operation’s inputs, it can often replace the operation with something simpler and cheaper.
“Constant folding” is a fancy way of saying the compiler does work once so it doesn’t need to be repeated at run time. If the compiler has everything it needs to compute an answer when building, it can bake that answer in to the generated code and avoid needing the code to re-compute it. That answer can then be further used by other computations at build time, potentially folding further. The C# compiler handles constant folding expressions composed entirely of language constants, while the JIT compiler can go further after inlining and after learning things about values and control flow. The JIT already does a ton of folding, and as with every release, it goes further in .NET 11.
One straightforward example is the offset of a field within a struct.
dotnet/runtime#122297
recognizes more cases where two addresses refer to the same struct and replaces their difference with the known field offset. Here, the second
int
field begins four bytes into the struct:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public unsafe class Benchmarks
{
private struct MyStruct
{
public int A;
public int Field;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static nint OffsetOfFieldInline()
{
MyStruct dummy;
return (nint)((byte*)&dummy.Field - (byte*)&dummy);
}
[Benchmark]
[Arguments(1_000)]
public nint OffsetOfFieldLoop(int n)
{
nint sum = 0;
for (int i = 0; i < n; i++)
sum += OffsetOfFieldInline();
return sum;
}
}
Without the fold, the loop repeatedly computes the field offset. With the fold, each iteration simply adds the constant
4
.
; Arm64
--- .NET 10
+++ .NET 11
@@ -1,7 +1,6 @@
G_M000_IG01:
- stp fp, lr, [sp, #-0x20]!
+ stp fp, lr, [sp, #-0x10]!
mov fp, sp
- str xzr, [fp, #0x18]
G_M000_IG02:
mov x0, xzr
@@ -9,22 +8,18 @@
ble G_M000_IG05
G_M000_IG03:
- add x2, fp, #0x1C
- add x3, fp, #24
- sub x2, x2, x3
align [0 bytes for IG04]
align [0 bytes]
align [0 bytes]
align [0 bytes]
G_M000_IG04:
- str xzr, [fp, #0x18]
- add x0, x2, x0
+ add x0, x0, #4
sub w1, w1, #1
cbnz w1, G_M000_IG04
G_M000_IG05:
- ldp fp, lr, [sp], #0x20
+ ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 60
+; Total bytes of code 40
dotnet/runtime#121985
from
@hez2010
enables the JIT to evaluate
SequenceEqual
at compile time when both inputs are known.
SequenceEqual
normally walks two sequences element by element, stopping at the first mismatch. But if inlining exposes both sequences as constants, there’s nothing useful left to do at run time: the JIT can compare them while compiling and replace the whole operation with a constant
true
or
false
. This intrinsic underpins APIs including
MemoryExtensions.SequenceEqual
,
ReadOnlySpan<T>.SequenceEqual
, and
string.Equals
.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static string AlphaLower => "abcdefghijklmnopqrstuvwxyz";
private static string AlphaUpper => "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
[Benchmark]
public bool CompareEqual() => AlphaLower.Equals(AlphaLower);
[Benchmark]
public bool CompareDistinct() => AlphaLower.Equals(AlphaUpper);
}
Because these properties aren’t
const
, the C# compiler can’t evaluate the comparisons. The JIT, however, can see the string literals after inlining. It now folds comparisons of the same input whose contents are available at the time of compilation.
CompareDistinct
therefore becomes a constant
false
.
; x64
--- .NET 10
+++ .NET 11
-mov rax,LOWER_STRING
-mov rcx,UPPER_STRING
-add rax,0C
-vmovups ymm0,[rax]
-vmovups ymm1,[rax+14]
-vmovups ymm2,[rcx]
-vpxor ymm0,ymm2,ymm0
-vpxor ymm1,ymm1,[rcx+14]
-vpor ymm0,ymm1,ymm0
-vptest ymm0,ymm0
-sete al
-movzx eax,al
-vzeroupper
+xor eax,eax
ret
-; Total bytes of code 65
+; Total bytes of code 3
Folding an operation is only the first step, though. The result can then simplify later code, even when it’s a vector.
dotnet/runtime#127124
extends assertion propagation to 128-bit integer vector constants. If a branch establishes that a vector is zero, uses of that vector within the branch can now be replaced with zero and simplified just like scalar values.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int _selector;
[MethodImpl(MethodImplOptions.NoInlining)]
private Vector128<int> Compute() => _selector == 0 ? Vector128<int>.Zero : Vector128.Create(7);
[Benchmark]
public int AndNotIfZero()
{
Vector128<int> v = Compute();
if (v == Vector128<int>.Zero)
{
Vector128<int> masked = Vector128.AndNot(v, Vector128.Create(0x00FF00FF));
return masked[0];
}
return -1;
}
}
In the benchmark’s zero branch, the JIT can now fold away the mask creation,
AndNot
, and lane extraction, reducing the Arm64 method from 68 bytes to 56 bytes. This currently applies to integer vectors up to 128 bits (floating-point equality has additional NaN and signed-zero semantics that prevent the same reasoning at present).
; Arm64
--- .NET 10
+++ .NET 11
@@ -11,14 +11,11 @@
umaxp v16.4s, v0.4s, v0.4s
umov x0, v16.d[0]
movn w1, #0
- movi v16.8h, #0xFF, LSL #8
- and v16.4s, v0.4s, v16.4s
- smov x2, v16.s[0]
cmp x0, #0
- csel w0, w1, w2, ne
+ cinc w0, w1, eq
G_M000_IG03:
ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 68
+; Total bytes of code 56
Two backend cleanups take advantage of simpler expressions.
dotnet/runtime#124332
from
@jonathandavies-arm
removes an unnecessary negation when Arm64 code compares a negated value with zero. And
dotnet/runtime#124642
from
@yykkibbb
lets short-circuit Boolean returns fold even when inlining has left unused writes in the same block; those stores previously obscured the simple Boolean expression from the optimizer.
Branches offer another opportunity for simplification. Modern processors work on several instructions at different stages at the same time. When a processor encounters a conditional branch, it predicts which path will be taken so that it can continue fetching and executing instructions speculatively. A correct prediction hides much of the branch’s cost. A misprediction throws away that speculative work, redirects instruction fetch to the correct path, and refills the processor’s execution pipeline. That can make the predictability of a branch as important as the work in either branch. The JIT can sometimes avoid that variability, particularly inside small hot loops, by replacing a branch with a conditional move instruction or by recognizing that several branches describe one simpler condition. This isn’t always profitable: branchless code may evaluate work that a predictable branch would skip, making the branching code less expensive in the majority case. But it can be valuable for small, data-dependent choices.
dotnet/runtime#124567
recognizes zero-based equality chains, e.g.
value == 0 || value == 1 || value == 2
. Such chains can be replaced with an
unsigned range check, e.g.
(uint)value <= 2
, producing a branchless result.
The unsigned comparison also handles negative inputs: when interpreted as
unsigned, any negative
int
is larger than the upper bound.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int _value = 2;
[Benchmark]
public bool IsLetterCategory() =>
_value == 0 ||
_value == 1 ||
_value == 2 ||
_value == 3 ||
_value == 4;
}
The .NET 10 JIT already combines the first four comparisons, but still needs
a branch and a separate comparison for
4
:
; x64
mov ecx,[rcx+8]
cmp ecx,3
ja CHECK_FOUR
mov eax,1
ret
CHECK_FOUR:
cmp ecx,4
sete al
movzx eax,al
ret
.NET 11 recognizes the whole chain as one unsigned range check, reducing the
method from 24 bytes to 13:
; x64
mov eax,[rcx+8]
cmp eax,5
setb al
movzx eax,al
ret
dotnet/runtime#128524
from
@BoyBaykiller
extends the same optimization to contiguous ranges that don’t start at zero. For example,
x == 3 || x == 4 || x == 5
can become
(uint)(x - 3) <= 2
.
Casts can obscure an equally simple comparison.
dotnet/runtime#128091
from
@BoyBaykiller
broadens cast-comparison optimization to equality and inequality. In this benchmark, converting a
uint
to
ulong
adds no information needed to compare it with
uint.MaxValue
, so the JIT can keep the comparison at 32 bits:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Linq;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _values = Enumerable.Range(0, 128).ToArray();
[Benchmark]
public int CastEquality()
{
int matches = 0;
foreach (int value in _values)
if ((ulong)(uint)value == uint.MaxValue)
matches++;
return matches;
}
}
The widening cast disappears, reducing the Arm64 method from 80 bytes to 76 bytes.
; Arm64
--- .NET 10
+++ .NET 11
@@ -18,8 +18,7 @@
G_M000_IG04:
ldr w3, [x0]
- mov x4, #0xFFFFFFFF
- cmp x3, x4
+ cmn w3, #1
beq G_M000_IG08
G_M000_IG05:
@@ -38,4 +37,4 @@
add w1, w1, #1
b G_M000_IG05
-; Total bytes of code 80
+; Total bytes of code 76
The examples thus far simplify individual comparisons.
dotnet/runtime#127181
also combines multiple comparisons in the same expression. For example,
(x >= c) && (x <= c)
can only be true when
x == c
; corresponding OR forms can be simplified similarly.
Once the JIT can reason about one comparison in terms of another, it can apply the same idea across branches.
dotnet/runtime#126587
removes an earlier test when a later, stronger test subsumes it. For example,
if (x > 0) if (x > 1)
needs only the
x > 1
test, as reaching the nested body with
x > 1
necessarily also means
x > 0
.
Rather than simply removing a test, the JIT can sometimes use the outcome of an earlier branch to choose the destination of a later one. This is known as “jump threading”: the JIT threads a control-flow path through the intervening jumps directly to its eventual destination. For example, consider:
int value = condition ? 1 : 2;
if (value == 1)
{
One();
}
else
{
Two();
}
The path where
condition
is true can go directly to
One
, while the false path can go directly to
Two
, eliminating the second test, effectively:
int value;
if (condition)
{
value = 1;
One();
}
else
{
value = 2;
Two();
}
dotnet/runtime#126812
lets this continue through more places where paths rejoin, and
dotnet/runtime#127103
ensures the rewritten values remain correct in more of those cases.
dotnet/runtime#127950
carries relationships between values further, so facts like
a > 10
and
b > a
can simplify later branches or bounds. The same reasoning can apply to type information.
dotnet/runtime#128500
combines the known types of instances arriving from multiple paths; if every value derives from the tested base type, the JIT can remove the
is
test after the paths merge. And
dotnet/runtime#127434
from
@hez2010
lets redundant-branch elimination look through empty jump blocks. Such a block contains no work of its own and exists only to redirect control elsewhere, but it could still hide the relationship between two conditions from the optimizer. Consider this benchmark:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static object? s_sink;
private int _x = 20;
private int _y = 30;
private bool _flag = true;
private int _count = 5;
[Benchmark]
public bool TransitiveComparison() => TransitiveComparison(_x, _y);
[Benchmark]
public bool MergedTypeCheck() => MergedTypeCheck(_flag);
[Benchmark]
public int NestedThresholds() => NestedThresholds(_count);
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool TransitiveComparison(int x, int y)
{
if (x > 10 && x < 100 && y > x)
return y > 0;
return false;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool MergedTypeCheck(bool flag)
{
object shape = flag ? new Circle() : new Rectangle();
s_sink = shape;
return shape is Shape;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static int NestedThresholds(int count)
{
if (count > 1)
if (count > 2)
if (count > 3)
if (count > 4)
return 1;
return 3;
}
private abstract class Shape;
private sealed class Circle : Shape;
private sealed class Rectangle : Shape;
}
In
TransitiveComparison
, reaching
y > 0
means the JIT already knows that
x > 10
and
y > x
, which together prove that
y
is positive. The final comparison disappears, reducing the Arm64 method from 40 bytes to 36 bytes:
; Arm64
--- .NET 10
+++ .NET 11
cmp w1, w0
ccmp w2, w3, c, gt
- ccmp w1, #0, nzc, ls
- cset x0, gt
+ cset x0, ls
-; Total bytes of code 40
+; Total bytes of code 36
In
MergedTypeCheck
, each path creates a different concrete type, but both derive from
Shape
. .NET 11 keeps the allocations and the store that make the example observable, but replaces the
is
helper call and its result test with the constant
true
, reducing the method from 112 bytes to 88 bytes:
; Arm64
--- .NET 10
+++ .NET 11
bl CORINFO_HELP_ASSIGN_REF
- movz x0, #0xEA30
- movk x0, #0x4EB LSL #16
- movk x0, #0x7FFF LSL #32
- bl CORINFO_HELP_ISINSTANCEOFCLASS
- cmp x0, #0
- cset x0, ne
+ mov w0, #1
-; Total bytes of code 112
+; Total bytes of code 88
For
NestedThresholds
, reaching the
return 1
requires
count
to be greater than all four constants, which is equivalent to just
count > 4
. Once redundant-branch elimination can see through the empty jump blocks left behind while simplifying the nested conditions, the other three comparisons disappear:
; Arm64
--- .NET 10
+++ .NET 11
mov w1, #3
mov w2, #1
- cmp w0, #1
- ccmp w0, #2, nzc, gt
- ccmp w0, #3, nzc, gt
- ccmp w0, #4, nzc, gt
+ cmp w0, #4
csel w0, w1, w2, le
-; Total bytes of code 44
+; Total bytes of code 32
Removing a redundant branch is ideal; why do work when it’s provably unnecessary? Often, however, the branch is necessary, as both outcomes are possible (or at least not provably impossible). In such cases, the JIT may still be able to avoid branching via specialized instructions that bake the choice into the instruction. “If-conversion” replaces a small
if
/
else
with a conditional-move instruction or another branchless form when both alternatives are cheap. The JIT has been able to do this for several releases, and improves in .NET 11.
dotnet/runtime#124738
from
@BoyBaykiller
recognizes an earlier default assignment as the implicit
else
, so
bool x = false; if (cond) x = true;
can become the same branchless form as an explicit
else
.
dotnet/runtime#127915
from
@BoyBaykiller
handles the opposite cleanup, removing a conditional selection when both outcomes are the same constant while preserving any side effects from evaluating the condition.
dotnet/runtime#128533
from
@BoyBaykiller
also helps these Boolean optimizations meet in the middle by normalizing power-of-two bit tests. A power of two has exactly one bit set, in which case
(A & bit) == bit
is equivalent to
(A & bit) != 0
; putting both forms into the same canonical representation makes them easier to combine with surrounding conditions. All three improvements are visible in the following benchmarks:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private int _left = 1;
private int _right = 2;
private double _double = 0.0;
private int _bits = 4;
[Benchmark]
public bool ImplicitElse() => ImplicitElse(_left, _right);
[Benchmark]
public bool IsDefaultValue() => IsDefaultValue(_double);
[Benchmark]
public bool HasEitherBit() => HasEitherBit(_bits);
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool ImplicitElse(int left, int right)
{
bool leftIsSmaller = false;
if (left < right)
leftIsSmaller = true;
return leftIsSmaller;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool IsDefaultValue(double value) => 0.0.Equals(value);
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool HasEitherBit(int value) =>
((value & 4) == 4) || ((value & 8) == 8);
}
For
ImplicitElse
, .NET 10 already avoids a branch, but it still materializes both Boolean values and selects between them. In .NET 11, the method becomes just the comparison and a
cset
, shrinking from 36 bytes to 24 bytes:
; Arm64
--- .NET 10
+++ .NET 11
- mov w2, wzr
- mov w3, #1
cmp w0, w1
- csel w2, w2, w3, ge
- mov w0, w2
+ cset x0, lt
-; Total bytes of code 36
+; Total bytes of code 24
0.0.Equals(value)
needs to account for
NaN
, but because the left operand is zero, the case where both operands are
NaN
can never apply. Removing the conditional selection for that case leaves one floating-point comparison and one
cset
, reducing
IsDefaultValue
from 40 bytes to 24 bytes:
; Arm64
--- .NET 10
+++ .NET 11
fcmp d0, #0.0
- beq G_M000_IG04
-
-G_M000_IG03:
- fcmp d0, d0
- csel w0, wzr, wzr, eq
- b G_M000_IG05
-
-G_M000_IG04:
- mov w0, #1
-
-G_M000_IG05:
+ cset x0, eq
+
+G_M000_IG03:
ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 40
+; Total bytes of code 24
Finally, normalizing both power-of-two comparisons lets the JIT combine their results. The short-circuit branch in
HasEitherBit
is replaced by two masks and an
or
, reducing the method from 40 bytes to 36 bytes:
; Arm64
--- .NET 10
+++ .NET 11
- tbz w0, #2, G_M000_IG05
-
-G_M000_IG03:
- mov w0, #1
-
-G_M000_IG04:
- ldp fp, lr, [sp], #0x10
- ret lr
-
-G_M000_IG05:
- tst w0, #8
+ and w1, w0, #4
+ and w0, w0, #8
+ orr w0, w1, w0
+ cmp w0, #0
cset x0, ne
-G_M000_IG06:
+G_M000_IG03:
ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 40
+; Total bytes of code 36
Not every simplification depends on broader control-flow reasoning.
“Peephole optimizations” instead replace a short, recognizable pattern with an
equivalent cheaper one. Each may save only an instruction or expose a form
that another optimization understands, but these patterns can occur very
frequently on hot paths throughout generated code. For example,
dotnet/runtime#126529
from
@BoyBaykiller
recognizes that
255 - x
for a
byte
is equivalent to
x ^ 255
: both simply flip all eight bits, but the latter can remove an instruction if it’s able to replace a negation and add with an xor. Similarly,
-1 - x
can turn into the equivalent of
~x
.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly byte[] _data = new byte[4096];
[GlobalSetup]
public void Setup() => new Random(42).NextBytes(_data);
[Benchmark]
public int InvertBytes()
{
int sum = 0;
foreach (byte b in _data) sum += 255 - b;
return sum;
}
}
In .NET 11, the loop loses a separate negate and add:
; Arm64
--- .NET 10
+++ .NET 11
@@ -19,9 +19,8 @@
G_M000_IG04:
ldrb w4, [x0, w2, UXTW]
- neg w4, w4
+ eor w4, w4, #255
add w1, w4, w1
- add w1, w1, #255
add w2, w2, #1
cmp w3, w2
bgt G_M000_IG04
@@ -33,4 +32,4 @@
ldp fp, lr, [sp], #0x10
ret lr
-; Total bytes of code 76
+; Total bytes of code 72
dotnet/runtime#129361
removes another unnecessary instruction when comparing an
sbyte
with a constant that fits in eight bits. The JIT can compare the byte directly, with no sign extension:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private sbyte _value = -65;
[Benchmark]
public bool IsLow() => IsLow(_value);
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool IsLow(sbyte value) => value < -64;
}
The optimized codegen then compares the byte directly, removing the
movsx
sign-extension instruction (though the JIT still retains it in the few comparison forms that require a full-width sign bit for correctness).
; x64
--- .NET 10
+++ .NET 11
-movsx rax,cl
-cmp eax,0FFFFFFC0
+cmp cl,0C0
setl al
movzx eax,al
ret
-; Total bytes of code 14
+; Total bytes of code 10
dotnet/runtime#125180
from
@saucecontrol
improves non-overflowing
float
and
double
conversions to
long
and
ulong
on x86 machines with AVX-512 or AVX10.2. These casts have defined behavior for NaN and out-of-range values, so older code used a helper to preserve those semantics. The newer instruction set lets the JIT keep the normal path inline and register-based, avoiding the helper call; machines that don’t support these instructions retain the existing fallback.
// Run with 32-bit x86 dotnet on a machine with AVX-512 or AVX10.2:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private float _single = 123_456.75f;
private double _double = 123_456.75;
[Benchmark] public long SingleToInt64() => (long)_single;
[Benchmark] public ulong SingleToUInt64() => (ulong)_single;
[Benchmark] public long DoubleToInt64() => (long)_double;
[Benchmark] public ulong DoubleToUInt64() => (ulong)_double;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
SingleToInt64
|
.NET 10.0
|
5.103 ns
|
1.00
|
31 B
|
|
SingleToInt64
|
.NET 11.0
|
2.093 ns
|
0.41
|
54 B
|
|
|
|
|
|
|
|
SingleToUInt64
|
.NET 10.0
|
4.810 ns
|
1.00
|
31 B
|
|
SingleToUInt64
|
.NET 11.0
|
1.366 ns
|
0.28
|
34 B
|
|
|
|
|
|
|
|
DoubleToInt64
|
.NET 10.0
|
4.834 ns
|
1.00
|
31 B
|
|
DoubleToInt64
|
.NET 11.0
|
2.101 ns
|
0.43
|
54 B
|
|
|
|
|
|
|
|
DoubleToUInt64
|
.NET 10.0
|
4.663 ns
|
1.00
|
31 B
|
|
DoubleToUInt64
|
.NET 11.0
|
1.363 ns
|
0.29
|
34 B
|
Vectorization
SIMD, or “single instruction, multiple data”, is the concept of one instruction applying the same operation to several values at once. A “scalar”
add
, for example, might combine one pair of 32-bit integers, while a 128-bit SIMD
add
can combine “vectors” of four pairs in the same instruction; 256- and 512-bit variants can handle vectors of eight and sixteen pairs, respectively. When the iterations of an operation are independent, “vectorizing” a loop can therefore replace several scalar iterations with one, improving the throughput of the loop significantly.
.NET exposes portable (they work on any machine) variable-width vector type
Vector<T>
(which can represent different counts of
T
depending on the current hardware), fixed-width
Vector64<T>
through
Vector512<T>
types (which always represent the same count of
T
), and architecture-specific intrinsics (performing operations on such vector types which the JIT then maps to the right underlying hardware instructions). Each element in a vector is often referred to as a “lane”. Because the JIT recognizes these operations directly, it can fold constants, select instructions, and remove unsupported paths without treating them as normal method calls.
A variety of PRs in .NET 11 improve AVX-512 broadcasting and masking. Embedded broadcasting lets an instruction load a single scalar value and replicate it across all vector lanes, avoiding the need to materialize a full-width vector constant in memory to feed into the instruction. For example, this bitwise AND instruction:
; x64
vpandd zmm0, zmm1, dword ptr [reloc @RWD00] {1to16}
can replace this one:
; x64
vpandd zmm0, zmm1, zmmword ptr [reloc @RWD00]
storing only 4 bytes in the read-only data section rather than 64. Because the broadcast is handled as part of the load, there’s no additional instruction-level latency; the primary benefit is reduced data size and cache footprint.
Embedded masking similarly lets an instruction update only a subset of the lanes. A mask is one bit per vector lane, where each bit indicates whether and how the operation should affect the corresponding lane. Without embedded masking, code often needs to compute every lane and then blend that result with the old value, so folding the mask into the operation can remove both the separate blend and a zero-vector setup.
dotnet/runtime#117700
from
@saucecontrol
improves broadcast selection when an intrinsic’s natural element size differs from its managed vector type. VNNI, the Vector Neural Network Instructions used for small-integer multiply-accumulate operations, and bitwise operations can now use the smallest valid repeated constant, avoiding a full-vector load.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
// Requires AVX-VNNI and AVX-512F.
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.Intrinsics;
using System.Runtime.Intrinsics.X86;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector128<byte> _bytes = Vector128.Create((byte)1);
private readonly Vector128<ulong> _u64 = Vector128.Create(1UL);
private readonly Vector128<uint> _u32 = Vector128.Create(1U);
private readonly Vector512<int> _v512 = Vector512.Create(1);
private int _n = 42;
[Benchmark]
public Vector128<int> VnniBroadcast() =>
AvxVnni.MultiplyWideningAndAdd(
Vector128<int>.Zero, _bytes, Vector128<sbyte>.One);
[Benchmark]
public Vector128<uint> MaskAnd() =>
Vector128.ConditionalSelect(
Vector128.GreaterThan(_u32, Vector128<uint>.Zero),
(_u64 & Vector128<uint>.One.AsUInt64()).AsUInt32(),
Vector128<uint>.Zero);
[Benchmark]
public Vector512<int> BlendMaskAllOnes() =>
Avx512F.BlendVariable(
Vector512.Create(_n),
_v512,
Vector512.Create(-1));
[Benchmark]
public Vector512<int> MultiInsert() =>
Vector512.ConditionalSelect(
Vector512.Create(0, -1, 0, 0, 0, -1, 0, 0, 0, -1, 0, 0, 0, -1, 0, 0),
_v512,
Vector512.Create(_n));
[Benchmark]
public Vector512<int> MultiInsertZero() =>
Avx512F.BlendVariable(
_v512,
Vector512<int>.Zero,
Vector512.Create(0, -1, 0, 0, 0, -1, 0, 0, 0, -1, 0, 0, 0, -1, 0, 0));
}
In .NET 11, this results in 12 fewer bytes in the read-only data section, and
12 fewer bytes of constant-pool cache footprint.
; x64
-C4E279503500000000 vpdpbusd xmm6, xmm0, xmmword ptr [reloc @RWD00]
+62F27D18503500000000 vpdpbusd xmm6, xmm0, dword ptr [reloc @RWD00] {1to4}
-RWD00 dq 0101010101010101h, 0101010101010101h
+RWD00 dd 01010101h
The fix also impacts embedded masking. For example, with
MaskAnd
previously, the AND used a qword broadcast,
{1to2}
, and a separate blend then moved the masked result, meaning two instructions. Now that
Vector128<uint>.One
can be broadcast at dword granularity, the mask’s element size and the AND’s element size agree, unlocking using the single merged-masked form. This pattern shows up throughout vectorized algorithms that do lots of bitwise manipulation and hashing, including implementations in System.Numerics.Tensors, System.IO.Hashing, and System.Private.CoreLib.
; x64
- vpandq xmm0, xmm0, qword ptr [reloc @RWD00] {1to2}
- vpblendmd xmm0 {k1}{z}, xmm0, xmm0
+ vpandd xmm0 {k1}{z}, xmm0, dword ptr [reloc @RWD00] {1to4}
; Code: 45 → 39 bytes; data: 8 bytes → 4 bytes
That
MaskAnd
example starts as an AND followed by a blend, an operation that
chooses independently for each vector lane whether to take its value from one
input or the other, with the JIT able to fold those two operations together.
Similar opportunities arise with blends more generally. Sometimes the mask or
one of the inputs makes the choice trivial, e.g. an all-ones mask always selects the
same input, so the blend is just a move. If one input is zero, it can often
become an
AND
or
ANDN
. AVX-512 provides more options still, as constant
masks and zeroing can be encoded directly in the instruction.
dotnet/runtime#123146
from
@saucecontrol
makes these simplifications
consistently across the portable and hardware-specific APIs. A blend with an all-ones mask provides a particularly clear example:
// Run on x64 with AVX-512:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Runtime.Intrinsics;
using System.Runtime.Intrinsics.X86;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector512<int> _values = Vector512.Create(1);
private int _n = 42;
[GlobalSetup]
public void Setup()
{
if (!Avx512F.IsSupported)
throw new PlatformNotSupportedException();
}
[Benchmark]
public Vector512<int> BlendMaskAllOnes() =>
Avx512F.BlendVariable(Vector512.Create(_n), _values, Vector512.Create(-1));
}
The generated code no longer needs
to create the first input, load the mask, or perform the blend. It simply
loads the input the all-ones mask would always select:
; x64
-vpbroadcastd zmm0, dword ptr [rcx+8]
-kmovq k1, qword ptr [RWD00]
-vpblendmd zmm0 {k1}, zmm0, [rcx+48]
+vmovups zmm0, [rcx+48]
vmovups [rdx], zmm0
mov rax, rdx
vzeroupper
ret
; 39 bytes → 23 bytes
Intrinsics
An intrinsic is a managed API that the JIT recognizes and special-cases. Often that special-casing involves actually replacing calls to the method with custom code that’s behaviorally equivalent but better in some way (faster, smaller, etc.)
As an example,
dotnet/runtime#128678
improves recognition of generic-math calls to
IBinaryNumber<T>.Log2
. The method computes the base-2 logarithm of an integer, equivalent to the index of the number’s highest set bit; for example,
Log2(16)
is
4
. Previously, the JIT’s normalized integer type lost the signedness needed to import the operation directly as an intrinsic. Inlining the managed implementation could still produce the same optimized code, but when inlining didn’t happen, the managed call remained. In .NET 11, the JIT consults the precise type and imports the operation directly: unsigned and non-negative signed inputs can become leading-zero-count or bit-scan arithmetic, while a negative signed value retains the managed fallback and its exact exception behavior.
Sometimes the JIT has a perfectly good intrinsic lowering but doesn’t recognize a call that should use it.
Enum.Equals
from a generic
T : Enum
context was a good example. Even though both arguments to the generic helper are strongly typed as
T
, an enum doesn’t provide an
Equals(T)
method; it inherits the virtual
Enum.Equals(object)
implementation. The second argument therefore needs to be boxed to pass it as
object
. The receiver is invoked with a constrained virtual call, but because the concrete enum doesn’t override the method itself, it too needs to be boxed to invoke the implementation on
System.Enum
. Thus, what looks like a strongly-typed comparison can end up allocating two boxes and making a virtual call. In .NET 11,
dotnet/runtime#122779
eliminates this overhead by teaching the JIT to recognize the call and fold it to a direct comparison of the enum’s underlying integer values. For example:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly StringComparison[] s_values =
{
StringComparison.Ordinal, StringComparison.OrdinalIgnoreCase,
StringComparison.CurrentCulture, StringComparison.CurrentCultureIgnoreCase,
StringComparison.InvariantCulture, StringComparison.Ordinal,
};
[Benchmark]
public int CountOrdinal_Generic()
{
int count = 0;
foreach (var v in s_values)
if (EqualsGeneric(v, StringComparison.Ordinal))
count++;
return count;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool EqualsGeneric<T>(T a, T b) where T : Enum => a.Equals(b);
}
Once the JIT knows the callee is
Enum.Equals
and knows the exact enum type, it asks the runtime for the underlying integer type and replaces the virtual call with a direct comparison. That in turn makes both box/unbox pairs redundant, and the generated code contains neither allocation. For the six comparisons performed here, .NET 10 creates twelve boxes, totaling 288 bytes. In .NET 11, the helper becomes just the integer comparison, eliminating both the allocations and the virtual dispatch.
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
|
CountOrdinal_Generic
|
.NET 10.0
|
59.24 ns
|
1.00
|
288 B
|
|
CountOrdinal_Generic
|
.NET 11.0
|
10.01 ns
|
0.17
|
–
|
NativeAOT had been carrying an equivalent optimization for years, implemented as IL rewriting in ILCompiler that patches
Enum.Equals
to use typed comparisons. With the JIT now handling it, including in NativeAOT’s own use of the JIT (NativeAOT uses the JIT ahead of time rather than just in time),
dotnet/runtime#123086
deletes that rewriting and its supporting machinery.
dotnet/runtime#127329
improves the
Vector256.Sum
and
Vector512.Sum
intrinsics. The JIT now performs most of the reduction at full width and combines the per-lane results at the end, avoiding the extracts and duplicate shuffle sequences needed when splitting wide vectors into 128-bit pieces. And
dotnet/runtime#127402
extends vector-constant propagation from 128-bit vectors to
Vector256
and
Vector512
. Code that compares a wide vector with a known sentinel can now simplify subsequent uses just as narrower vectors already could. The following benchmark exemplifies both:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
// Requires AVX2 for the assembly shown below.
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector256<float> _floats =
Vector256.Create(1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f);
private int _selector;
[Benchmark]
public float Sum() => Vector256.Sum(_floats);
[Benchmark]
public int TransformWhenKnown()
{
Vector256<int> value = GetVector();
if (value == Vector256.Create(0, 1, 2, 3, 4, 5, 6, 7))
return (value + Vector256.Create(10)).GetElement(6);
return -1;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private Vector256<int> GetVector() =>
_selector == 0 ?
Vector256.Create(0, 1, 2, 3, 4, 5, 6, 7) :
Vector256.Create(7);
}
For
Sum
, .NET 10 separately reduces each 128-bit half and then adds the two scalar results. In .NET 11, the permutes and adds operate on both halves in parallel as 256-bit instructions, after which only the two already-reduced halves need to be combined:
; x64
vmovups ymm0, [rcx+28]
-vmovaps ymm1, ymm0
-vpermilps xmm2, xmm1, 0B1
-vaddps xmm1, xmm2, xmm1
-vpermilps xmm2, xmm1, 4E
-vaddps xmm1, xmm2, xmm1
-vextractf128 xmm0, ymm0, 1
-vpermilps xmm2, xmm0, 0B1
-vaddps xmm0, xmm2, xmm0
-vpermilps xmm2, xmm0, 4E
-vaddps xmm0, xmm2, xmm0
-vaddss xmm0, xmm1, xmm0
+vpermilps ymm1, ymm0, 0B1
+vaddps ymm0, ymm1, ymm0
+vpermilps ymm1, ymm0, 4E
+vaddps ymm0, ymm1, ymm0
+vextractf128 xmm1, ymm0, 1
+vaddps xmm0, xmm1, xmm0
; 63 bytes → 39 bytes
TransformWhenKnown
uses a deliberately non-repeating constant across its eight lanes. On the branch where the comparison succeeds, .NET 11 can replace
value
with that constant, fold the vector addition, and determine that element 6 is
16
. The
vpaddd
, extraction, second 32-byte constant, and associated control flow all disappear:
; x64
-cmp eax, 0FFFFFFFF
-jne M00_L00
-vmovups ymm0, [rsp+20]
-vpaddd ymm0, ymm0, [RWD32]
-vextracti128 xmm0, ymm0, 1
-vpextrd eax, xmm0, 2
-vzeroupper
-add rsp, 58
-ret
-
-M00_L00:
-mov eax, 0FFFFFFFF
+mov ecx, 0FFFFFFFF
+mov edx, 10
+cmp eax, 0FFFFFFFF
+mov eax, edx
+cmovne eax, ecx
vzeroupper
add rsp, 58
ret
; 85 bytes → 59 bytes
One of the goals of .NET is that you can write code once and have it run anywhere, optimized for whatever that “anywhere” has to offer. For vectorization, that means providing portable operations whenever the intent is common across instruction sets, while retaining architecture-specific APIs for algorithms that really do need to target a particular machine.
Whenever possible, we want to enable developers to express their algorithms using the portable APIs, and each release of .NET fills additional gaps there. Including .NET 11.
dotnet/runtime#129627
from
@hez2010
adds portable APIs for constructing common lane sequences (e.g.
[1, 2, 4, 8]
or
[a, b, a, b]
), concatenating half-vectors (the lower halves of
[a, b, c, d]
and
[w, x, y, z]
producing
[a, b, w, x]
), interleaving (
[a, b]
and
[x, y]
producing
[a, x, b, y]
), de-interleaving (
[a, x, b, y]
producing
[a, b]
and
[x, y]
), and reversal (
[a, b, c, d]
producing
[d, c, b, a]
), along with their JIT intrinsification. These operations were already expressible, but only verbosely and only if you knew which hardware instruction to reach for, e.g. writing
Zip
by hand meant targeting a platform-specific API like
AdvSimd.Arm64.ZipLow
. The new APIs let the code state the transformation and leave instruction selection to the JIT.
Once the intrinsic operation has been recognized, the backend still needs to keep it in a useful vector form while assigning registers and selecting instructions. Vector values are structs, and the JIT will often apply “struct promotion,” tracking a struct’s fields as independent locals so that each can be optimized separately. That’s useful for ordinary structs, but counterproductive when a value is meant to remain in a vector or mask register: splitting it can introduce extra moves and obscure what should be a single whole-value store, particularly after inlining introduces more local stores.
dotnet/runtime#128013
consistently marks SIMD and mask stores as intrinsic-related across platforms, including 32-bit x86 and x64 mask stores, so those locals remain intact.
dotnet/runtime#129563
extends that principle to user-defined structs that are bitcast to SIMD types. This trades away struct promotion for those locals, but enables the JIT to preserve their vector representation.
This matters for user-defined numerical types that store the same data as a
hardware vector but expose named fields or domain-specific operations. The
following
Vector2Double
is laid out as two adjacent
double
values, so it can
be bitcast to
Vector128<double>
, operated on with SIMD, and bitcast back:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
using System.Runtime.Intrinsics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
public struct Vector2Double(double x, double y)
{
public double X = x;
public double Y = y;
public static Vector2Double operator +(Vector2Double left, Vector2Double right)
{
Vector128<double> simdLeft = Unsafe.BitCast<Vector2Double, Vector128<double>>(left);
Vector128<double> simdRight = Unsafe.BitCast<Vector2Double, Vector128<double>>(right);
return Unsafe.BitCast<Vector128<double>, Vector2Double>(simdLeft + simdRight);
}
}
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector2Double _a = new(1.0, 2.0);
private readonly Vector2Double _b = new(3.0, 4.0);
private readonly Vector2Double _c = new(5.0, 6.0);
[Benchmark]
public Vector2Double Add() => Add(_a, _b, _c);
[MethodImpl(MethodImplOptions.NoInlining)]
private static Vector2Double Add(Vector2Double a, Vector2Double b, Vector2Double c) =>
a + b + c;
}
In .NET 10, promotion of the intermediate struct sends the first SIMD result
through two stack locations before the second addition. .NET 11 keeps that
value in
xmm0
, reducing the helper from 52 bytes to 22 bytes:
; x64
-sub rsp, 28
vmovups xmm0, [rdx]
vaddpd xmm0, xmm0, [r8]
-vmovaps [rsp], xmm0
-vmovups xmm0, [rsp]
-vmovups [rsp+18], xmm0
-vmovups xmm0, [rsp+18]
vaddpd xmm0, xmm0, [r9]
vmovups [rcx], xmm0
mov rax, rcx
-add rsp, 28
ret
; 52 bytes → 22 bytes
dotnet/runtime#128350
gives the xarch register allocator more freedom around fused multiply-add (FMA) and AVX-512 ternary-logic operations. These instructions can read and overwrite operands in several equivalent arrangements; choosing the arrangement that already matches the surrounding registers avoids otherwise necessary moves.
Generic vector code introduces another wrinkle. Operators like
Vector128<T>.operator ==
return
bool
, so the return type doesn’t reveal the
vector’s element type. The JIT instead needs to obtain that type from the
operands in order to select the right comparison instruction. In some generic
contexts, including helpers built on the internal
ISimdVector
abstraction,
the JIT was consulting the wrong type information and failed to import the
operator as an intrinsic. It then executed the managed fallback, which compares
the lanes individually.
dotnet/runtime#130086
marks these operators so their element type is taken from the first argument. As an example, the generic helpers used internally by ordinal-ignore-case string comparer benefit from this.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _lower = new('a', 256);
private readonly string _upper = new('A', 256);
[Benchmark]
public bool OrdinalIgnoreCase() => string.Equals(_lower, _upper, StringComparison.OrdinalIgnoreCase);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
OrdinalIgnoreCase
|
.NET 10.0
|
27.794 ns
|
1.00
|
|
OrdinalIgnoreCase
|
.NET 11.0
|
21.861 ns
|
0.79
|
.NET 11 adds support for newer x86 capabilities while also
improving code generated for existing hardware. These changes benefit both
direct users of hardware intrinsics and portable vector code selected by the
JIT. For example,
dotnet/runtime#124114
from
@saucecontrol
improves 32-bit x86 without AVX-512, where converting
uint
to
float
or
double
previously required a runtime helper. Older x86 conversion instructions accept signed integers, and half of the
uint
range doesn’t fit in a signed 32-bit value, which is why the helper existed. The JIT now emits an inline vector-instruction sequence that handles the high bit explicitly, avoiding the call and its register and stack overhead.
// Run with 32-bit x86 dotnet and AVX-512 disabled (DOTNET_EnableAVX512=0)
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private uint _value = 0xF123_4567;
[Benchmark] public float UInt32ToSingle() => _value;
[Benchmark] public double UInt32ToDouble() => _value;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
UInt32ToSingle
|
.NET 10.0
|
4.752 ns
|
1.00
|
37 B
|
|
UInt32ToSingle
|
.NET 11.0
|
2.403 ns
|
0.51
|
43 B
|
|
|
|
|
|
|
|
UInt32ToDouble
|
.NET 10.0
|
4.727 ns
|
1.00
|
39 B
|
|
UInt32ToDouble
|
.NET 11.0
|
2.402 ns
|
0.51
|
41 B
|
dotnet/runtime#124804
from
@alexcovington
adds the AVX-512 Bit Matrix Multiply APIs. A binary matrix treats each bit as an element and combines rows and columns with bitwise operations, not integer multiplication. The instructions are useful in areas such as error correction and CRC computation. Each replaces a much longer sequence of shifts, masks, and exclusive-ORs. And
dotnet/runtime#128365
from
@jamesburton
adds
AvxVnni.V512
, extending the AVX-VNNI APIs from 256-bit to 512-bit operands so the small-integer dot products used by quantized machine-learning models can process 64 bytes per operation instead of 32.
dotnet/runtime#126062
from
@saucecontrol
also avoids converting a vector selector into an AVX-512 mask register when the eventual operation still needs the vector form. In such cases, the older-looking vector blend is actually shorter and uses fewer resources:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.Intrinsics;
using System.Runtime.Intrinsics.X86;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector128<float> _v1 = Vector128.Create(-1.0f, 2.0f, -3.0f, 4.0f);
private readonly Vector128<float> _v2 = Vector128.Create(10.0f);
[GlobalSetup]
public void Setup()
{
if (!Sse41.IsSupported)
throw new PlatformNotSupportedException();
}
[Benchmark]
public Vector128<float> AddToNegative() =>
Sse41.BlendVariable(_v1, _v1 + _v2, _v1);
}
In .NET 11, you get the simpler
vblendvps
form that avoids an unnecessary k-register operation.
; x64
vmovups xmm0, [rcx+8]
- vpmovd2m k1, xmm0
- vaddps xmm0 {k1}, xmm0, [rcx+18]
+ vaddps xmm1, xmm0, [rcx+18]
+ vblendvps xmm0, xmm0, xmm1, xmm0
vmovups [rdx], xmm0
; 29 bytes → 24 bytes
The masked EVEX form looks more modern, but when the mask originates from a
vector anyway, the vector-blend sequence is five bytes shorter and avoids
writing a mask register. There are only 8 k-registers, and some
microarchitectures have port contention for instructions that write them.
A compiler’s cost model assigns estimates to operations and instructions, such as their execution cost or throughput and their impact on code size, and uses those estimates to choose between otherwise legal transformations or instruction sequences. Wrong estimates can still produce semantically correct code, just slower or larger code. With
dotnet/runtime#127048
, which updates the JIT’s xarch floating-point and SIMD cost model, the JIT’s cost model reflects modern instruction throughput and encoded size, replacing old x87 assumptions and a flat cost for every intrinsic. That leads to better decisions about common-subexpression elimination and loop unrolling, particularly for 512-bit operations.
dotnet/runtime#130422
folds a vector lane extraction followed by
WithElement
into one
insertps
that reads the source lane directly. Code such as
destination.WithElement(0, source.GetElement(2))
conceptually extracts a scalar and then inserts it elsewhere.
insertps
, however, has an immediate operand whose bits select both the source lane and destination lane. The JIT can therefore pass the original source vector to the instruction and encode lane 2 in that immediate, instead of first shuffling lane 2 into the scalar position and then inserting it.
Three more xarch changes tighten public SIMD operations on the hardware where they apply.
dotnet/runtime#125666
from
@alexcovington
replaces the dedicated AVX dot-product instruction with a multiply, add, and permute reduction that has better throughput on contemporary cores:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Numerics;
using System.Runtime.Intrinsics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Plane _plane = new(new Vector3(1.0f, 2.0f, 3.0f), 4.0f);
private readonly Vector4 _vector4 = new(5.0f, 6.0f, 7.0f, 8.0f);
private readonly Quaternion _quaternion1 = new(1.0f, 2.0f, 3.0f, 4.0f);
private readonly Quaternion _quaternion2 = new(5.0f, 6.0f, 7.0f, 8.0f);
private readonly Vector128<float> _vector1 = Vector128.Create(1.0f, 2.0f, 3.0f, 4.0f);
private readonly Vector128<float> _vector2 = Vector128.Create(5.0f, 6.0f, 7.0f, 8.0f);
[Benchmark]
public float PlaneDot() => Plane.Dot(_plane, _vector4);
[Benchmark]
public float QuaternionDot() => Quaternion.Dot(_quaternion1, _quaternion2);
[Benchmark]
public float Vector128Dot() => Vector128.Dot(_vector1, _vector2);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
PlaneDot
|
.NET 10.0
|
2.616 ns
|
1.00
|
13 B
|
|
PlaneDot
|
.NET 11.0
|
1.365 ns
|
0.52
|
31 B
|
|
|
|
|
|
|
|
QuaternionDot
|
.NET 10.0
|
2.640 ns
|
1.00
|
13 B
|
|
QuaternionDot
|
.NET 11.0
|
1.326 ns
|
0.50
|
31 B
|
|
|
|
|
|
|
|
Vector128Dot
|
.NET 10.0
|
2.597 ns
|
1.00
|
13 B
|
|
Vector128Dot
|
.NET 11.0
|
1.366 ns
|
0.53
|
31 B
|
Multiplying vectors of bytes is more involved than multiplying vectors of
larger integer types because x86 doesn’t provide a packed byte-multiply
instruction. The implementation needs to combine wider 16-bit multiplications
while retaining only the low byte of each product. When it couldn’t widen the
whole operation to the next vector size, .NET 10 split the input into two
halves, widened and multiplied each half, narrowed both results, and joined
them again.
dotnet/runtime#126348
from
@saucecontrol
instead separates the even and odd bytes with masks and shifts, performs two 16-bit multiplications over the full vector width, and recombines the low bytes:
// Run on x64 with AVX-512:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Runtime.Intrinsics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Vector512<byte> _left = Vector512.Create((byte)17);
private readonly Vector512<byte> _right = Vector512.Create((byte)19);
[Benchmark]
public Vector512<byte> Multiply() => _left * _right;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
Multiply
|
.NET 10.0
|
3.752 ns
|
1.00
|
114 B
|
|
Multiply
|
.NET 11.0
|
2.174 ns
|
0.58
|
73 B
|
The .NET 11 sequence no longer extracts, widens, narrows, and reinserts both
256-bit halves:
; x64
vmovups zmm0, [rcx+8]
-vmovaps zmm1, zmm0
-vpmovzxbw zmm1, ymm1
-vmovups zmm2, [rcx+48]
-vmovaps zmm3, zmm2
-vpmovzxbw zmm3, ymm3
-vpmullw zmm1, zmm3, zmm1
-vpmovwb ymm1, zmm1
-vextracti32x8 ymm0, zmm0, 1
-vpmovzxbw zmm0, ymm0
-vextracti32x8 ymm2, zmm2, 1
-vpmovzxbw zmm2, ymm2
-vpmullw zmm0, zmm2, zmm0
-vpmovwb ymm0, zmm0
-vinserti32x8 zmm0, zmm1, ymm0, 1
+vmovups zmm1, [rcx+48]
+vpmullw zmm2, zmm0, zmm1
+vpsrlw zmm0, zmm0, 8
+vpandd zmm1, zmm1, dword bcst [RWD00]
+vpmullw zmm0, zmm1, zmm0
+vpternlogd zmm0, zmm2, dword bcst [RWD04], 0F8
vmovups [rdx], zmm0
; 114 bytes → 73 bytes
dotnet/runtime#127094
lets scalar conversions between
Half
and
float
use F16C’s
vcvtps2ph
and
vcvtph2ps
instructions when AVX2 is enabled:
// Run on x64 with AVX2 enabled:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Half _half = (Half)123.5f;
private float _single = 123.5f;
[Benchmark] public float HalfToSingle() => (float)_half;
[Benchmark] public Half SingleToHalf() => (Half)_single;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
HalfToSingle
|
.NET 10.0
|
2.506 ns
|
1.00
|
104 B
|
|
HalfToSingle
|
.NET 11.0
|
1.380 ns
|
0.55
|
14 B
|
|
|
|
|
|
|
|
SingleToHalf
|
.NET 10.0
|
2.598 ns
|
1.00
|
134 B
|
|
SingleToHalf
|
.NET 11.0
|
1.351 ns
|
0.52
|
19 B
|
Finally,
dotnet/runtime#127536
from
@Ruihan-Yin
completes support for APX, Intel’s Advanced Performance Extensions. In addition to expanding the general-purpose register set, APX adds forms of many instructions that don’t overwrite the processor’s condition flags. That gives the register allocator and instruction scheduler more freedom to keep values and pending conditions alive at the same time. Its
CTEST
and
CFCMOV
instructions can also represent chained conditions without branches and replace some compare-with-zero forms with shorter encodings. Applications don’t need to call APX-specific APIs to benefit; when the hardware and operating system expose APX, the JIT is able to utilize the additional instructions automatically.
On Arm64, the work in .NET 11 spans both conventional code generation and
continued support for SVE (Scalable Vector Extension). Unlike 128-bit AdvSimd
vectors, an SVE vector doesn’t have one width fixed by the instruction set;
each processor chooses a supported width, and the same compiled loop uses
predicate masks to operate on however many elements fit. That makes SVE well
suited to loops whose trip counts are not exact multiples of a particular
vector size.
dotnet/runtime#121986
improves zeroing for larger stack allocations on Arm64. The JIT can store two zeroed 128-bit vector registers at a time, doubling the amount cleared by each instruction:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics.Arm;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Benchmark] public void Stackalloc512() => Consume(stackalloc byte[512]);
[Benchmark] public void Stackalloc1024() => Consume(stackalloc byte[1024]);
[Benchmark] public void Stackalloc16384() => Consume(stackalloc byte[16384]);
[MethodImpl(MethodImplOptions.NoInlining)]
private static void Consume(Span<byte> x) { }
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Stackalloc512
|
.NET 10.0
|
13.65 ns
|
1.00
|
|
Stackalloc512
|
.NET 11.0
|
9.557 ns
|
0.70
|
|
Stackalloc1024
|
.NET 10.0
|
25.35 ns
|
1.00
|
|
Stackalloc1024
|
.NET 11.0
|
14.332 ns
|
0.57
|
|
Stackalloc16384
|
.NET 10.0
|
312.97 ns
|
1.00
|
|
Stackalloc16384
|
.NET 11.0
|
162.656 ns
|
0.52
|
A wave of smaller Arm64 changes improves instruction selection. In .NET 11,
dotnet/runtime#119758
from
@jonathandavies-arm
lets a comparison with zero consume condition flags set as a side effect of the preceding arithmetic or logical instruction, avoiding a separate
cmp
.
dotnet/runtime#123138
from
@jonathandavies-arm
recognizes bit-extraction idioms such as
(value >> 6) & 0x3F
and maps them to the dedicated
ubfx
instruction. And
dotnet/runtime#123546
from
@jonathandavies-arm
removes a non-overflowing
int
-to-
long
widening cast when the result is immediately truncated to a smaller integer type.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD", "left", "right", "value")]
public class Benchmarks
{
[Benchmark]
[Arguments(-1, 2)]
public bool CompareWithZero(int left, int right) => (left & right) <= 0;
[Benchmark]
[Arguments(0x7F65_4321)]
public int ExtractBits(int value) => (value >> 6) & 0x3F;
[Benchmark]
[Arguments(0x1122_3344)]
public sbyte TruncateAfterWidening(int value) => (sbyte)(long)value;
}
Each example removes one instruction.
CompareWithZero
changes
and
to its flag-setting
ands
form and drops the subsequent
cmp
;
ExtractBits
replaces a shift and mask with
ubfx
; and
TruncateAfterWidening
drops the
sxtw
that widened the value to 64 bits only for
sxtb
to immediately truncate it again:
; Arm64
; CompareWithZero: 28 bytes → 24 bytes
- and w0, w1, w2
- cmp w0, #0
+ ands w0, w1, w2
cset x0, le
; ExtractBits: 24 bytes → 20 bytes
- asr w0, w1, #6
- and w0, w0, #63
+ ubfx w0, w1, #6, #6
; TruncateAfterWidening: 24 bytes → 20 bytes
- sxtw x0, w1
- sxtb w0, w0
+ sxtb w0, w1
Instruction selection also improves where values move between registers and memory. In .NET 11,
dotnet/runtime#126803
changes
ToScalar
on a vector of 64-bit integers to use
fmov Xd, Dn
rather than the lane-extract instruction
umov
; in both cases lane zero moves to a general-purpose register, but
fmov
is the more direct form. For ReadyToRun code,
dotnet/runtime#129589
folds relocatable indirection-cell loads from
adrp + add + ldr
into
adrp + ldr #:lo12:
, removing the separate address addition. And
dotnet/runtime#129932
re-enables
ldp
/
stp
formation for negative unscaled offsets, letting two adjacent loads or stores become one paired instruction.
The first and third changes are easy to see with small methods:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Vector128<long> _vector = Vector128.Create(42L, 84L);
private nint[] _storage = new nint[8];
[Benchmark]
public long ToScalar() => ToScalarCore(_vector);
[Benchmark]
public void ClearPrevious() => ClearPreviousCore(ref _storage[4]);
[MethodImpl(MethodImplOptions.NoInlining)]
private static long ToScalarCore(Vector128<long> value) => value.ToScalar();
[MethodImpl(MethodImplOptions.NoInlining)]
private static void ClearPreviousCore(ref nint value)
{
Unsafe.Add(ref value, -1) = 0;
Unsafe.Add(ref value, -2) = 0;
Unsafe.Add(ref value, -3) = 0;
Unsafe.Add(ref value, -4) = 0;
}
}
The
ToScalar
change is a direct instruction substitution, while the negative-offset stores collapse from four instructions to two, reducing the helper from 32 bytes to 24 bytes:
; Arm64
; ToScalarCore
- umov x0, v0.d[0]
+ fmov x0, d0
; ClearPreviousCore
- str xzr, [x0, #-0x08]
- str xzr, [x0, #-0x10]
- str xzr, [x0, #-0x18]
- str xzr, [x0, #-0x20]
+ stp xzr, xzr, [x0, #-0x10]
+ stp xzr, xzr, [x0, #-0x20]
Bit-counting operations benefit as well.
PopCount
counts the one bits in a value, while
TrailingZeroCount
counts the zero bits below its least-significant one bit.
dotnet/runtime#128677
imports both as dedicated Arm64 intrinsics, making their intent visible to later optimization. On processors with the FEAT_CSSC extension,
dotnet/runtime#130332
can then lower them directly to the scalar
cnt
and
ctz
instructions.
Comparison masks are another place where spelling out the intent enables much better code. Portable SIMD code often compares vectors, calls
ExtractMostSignificantBits
, and then asks whether any lane matched, counts matching lanes, or finds the first or last match.
dotnet/runtime#129688
from
@jonathandavies-arm
recognizes those consumers on Arm64 and avoids materializing the full scalar mask: it can horizontally reduce the vector mask directly.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics;
using System.Runtime.CompilerServices;
using System.Runtime.Intrinsics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Vector128<int> _value = Vector128.Create(1, -2, 3, -4);
[Benchmark]
public bool AnyLessThan() => AnyLessThanCore(_value, 0);
[Benchmark]
public int CountLessThan() => CountLessThanCore(_value, 0);
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool AnyLessThanCore(Vector128<int> value, int limit) =>
Vector128.LessThan(value, Vector128.Create(limit))
.ExtractMostSignificantBits() != 0;
[MethodImpl(MethodImplOptions.NoInlining)]
private static int CountLessThanCore(Vector128<int> value, int limit) =>
BitOperations.PopCount(
Vector128.LessThan(value, Vector128.Create(limit))
.ExtractMostSignificantBits());
}
In .NET 10, both helpers first pack the most-significant bit from every comparison lane into a scalar. .NET 11 instead keeps the comparison as a vector.
; Arm64
; AnyLessThanCore
cmgt v16.4s, v16.4s, v0.4s
- movi v17.4s, #0x80, LSL #24
- and v16.4s, v16.4s, v17.4s
- ldr q17, [@RWD00]
- ushl v16.4s, v16.4s, v17.4s
- addv s16, v16.4s
- smov x0, v16.s[0]
+ umaxv s16, v16.4s
+ umov w0, v16.s[0]
cmp w0, #0
cset x0, ne
; CountLessThanCore
cmgt v16.4s, v16.4s, v0.4s
- movi v17.4s, #0x80, LSL #24
- and v16.4s, v16.4s, v17.4s
- ldr q17, [@RWD00]
- ushl v16.4s, v16.4s, v17.4s
- addv s16, v16.4s
- movi v17.2s, #0
- smov x0, v16.s[0]
- ins v17.s[0], w0
- cnt v16.8b, v17.8b
- addv b16, v16.8b
- umov w0, v16.b[0]
+ ushr v16.4s, v16.4s, #31
+ addv s16, v16.4s
+ umov w0, v16.s[0]
On the SVE and SVE2 side,
dotnet/runtime#129852
from
@snickolls-arm
removes the old 128-bit size ceiling for
Vector<T>
on Arm64 and lets the runtime size the type from the process’s actual SVE vector length. (Scalable
Vector<T>
remains experimental and disabled by default in .NET 11, so this expands what the experimental mode can do; it doesn’t speed up the default
Vector<T>
configuration.)
The public intrinsic surface also grows. In .NET 11,
dotnet/runtime#118957
from
@SwapnilGaikwad
exposes odd-lane floating-point conversions; “odd lane” here means converting elements 1, 3, 5, and so on, which is useful when widening or narrowing interleaved data.
dotnet/runtime#123890
from
@ylpoonlg
and
dotnet/runtime#123892
from
@ylpoonlg
add non-temporal gather loads and scatter stores, which read from or write to multiple non-contiguous addresses (the “gather” part) while hinting that the data need not remain in cache (the “non-temporal” part).
Other changes improve the predicates that make scalable loops work.
dotnet/runtime#127538
adds hardware-generated predicate masks for more loop and memory-access patterns, while
dotnet/runtime#126398
from
@ylpoonlg
reduces setup moves for masked operations. And
dotnet/runtime#128326
from
@snickolls-arm
improves how SVE masks flow through the JIT, allowing zeroing forms of instructions to replace separate constant setup.
dotnet/runtime#127520
from
@a74nh
enables scalable vector and mask constants, and
dotnet/runtime#128148
from
@snickolls-arm
uses vector stores to initialize scalable vector locals, replacing scalar loops.
Register Allocation
Generated code constantly moves values between the CPU’s limited set of fast registers and temporary stack slots. Register allocation in a compiler decides which values stay in registers and which are “spilled” to the stack; avoiding one spill can remove both the store and the later reload.
Some small structs are passed with multiple fields packed into one register. In .NET 11,
dotnet/runtime#112740
lets the JIT extract those fields directly, avoiding a “spill” to a temporary stack slot followed by a reload of each field:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Drawing;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Memory<int>[] _memories = CreateMemories();
private static Memory<int>[] CreateMemories()
{
Random rng = new(42);
var memories = new Memory<int>[4096];
for (int i = 0; i < memories.Length; i++)
memories[i] = new int[rng.Next(0, 20)];
return memories;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static bool Test(Memory<int> mem) => mem.Length > 10;
[Benchmark]
public int MemoryLengthExtract_Loop()
{
int count = 0;
for (int i = 0; i < _memories.Length; i++)
if (Test(_memories[i]))
count++;
return count;
}
}
The measured row uses
Memory<int>
because its length arrives packed into part of an argument register on Arm64. The new extraction avoids a stack round-trip on every call.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
MemoryLengthExtract_Loop
|
.NET 10.0
|
27.15 μs
|
1.00
|
|
MemoryLengthExtract_Loop
|
.NET 11.0
|
23.95 μs
|
0.88
|
Two broader register-allocation changes reduce unnecessary copies and spills:
dotnet/runtime#125214
handles more conflicts directly, while
dotnet/runtime#125219
steers short-lived values away from registers an upcoming operation will overwrite.
dotnet/runtime#126552
from
@SingleAccretion
removes an old restriction on method prologs, eliminating jumps that existed only to satisfy that encoding rule.
Write Barriers and Garbage Collection
The .NET garbage collector is generational: new objects start in gen0, while objects that survive collections are promoted to gen1 and gen2. That enables the GC to collect younger generations without having to scan the whole heap. Of course, a reference to a younger object could get written to a field of an older one, in which case only scanning the younger generation would lead to problems. To ensure such references aren’t missed, whenever a write could create one, the JIT emits a small piece of code to update the GC’s bookkeeping; that code is known as a GC write barrier. Reference writes happen a lot, so it’s really important for performance that those barriers be as cheap as possible, and elided if they’re provably not needed at all.
Managed reference stores may require both an array covariance check and a GC write barrier. Arrays in .NET are covariant, meaning a
TDerived[]
can be used as a
TBase[]
, e.g. a
string[]
can be used as an
object[]
; consequently, storing an instance into an
object[]
must validate that the instance is actually of the right type (otherwise, you could have a
TDerived1[]
masquerading as a
TBase[]
and try to store a
TDerived2
into it, which would cause badness if it were to store successfully).
dotnet/runtime#126547
expands calls to the runtime’s array-store helper into the individual operations it performs, exposing both the covariance check and write barrier to the JIT. When the JIT knows the array’s exact type, it can then eliminate the covariance check and optimize the barrier:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly object[] _array = new object[4096];
private object _value = new();
[MethodImpl(MethodImplOptions.NoInlining)]
private static void StoreAll(object[] arr, object value)
{
for (int i = 0; i < arr.Length; i++)
arr[i] = value;
}
[Benchmark]
public object[] CovariantStore_Loop()
{
StoreAll(_array, _value);
return _array;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
CovariantStore_Loop
|
.NET 10.0
|
10.85 μs
|
1.00
|
|
CovariantStore_Loop
|
.NET 11.0
|
6.042 μs
|
0.56
|
Sometimes writes are done one at a time, but sometimes they can be batched, as happens when copying structs.
dotnet/runtime#128238
extends the JIT’s heap-destination analysis from individual stores to whole-struct copies.
dotnet/runtime#128542
then replaces a specialized helper that copied one reference field at a time with reference stores and vector stores for the non-reference data. Together, they let the JIT choose more efficient write barriers and copy the rest of a mixed struct with SIMD.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[InlineArray(4)]
public struct InlineArray4Long
{
private long _element0;
}
public struct MyStruct
{
public string A;
public InlineArray4Long G;
public string B;
}
private MyStruct _src;
private MyStruct _dst;
[GlobalSetup]
public void Setup()
{
_src = new MyStruct { A = "hello", B = "world" };
_src.G[0] = 1;
_src.G[1] = 2;
_src.G[2] = 3;
_src.G[3] = 4;
}
[Benchmark]
public void HeapStructCopy() => _dst = _src;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
HeapStructCopy
|
.NET 10.0
|
4.132 ns
|
1.00
|
|
HeapStructCopy
|
.NET 11.0
|
3.071 ns
|
0.74
|
dotnet/runtime#130535
handles the equivalent case for small structs that don’t contain object references. Once the JIT has turned the copy into several writes to adjacent fields, it can combine them into fewer, wider writes.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Int128 _value;
[Benchmark]
public void StoreInt128() => _value = 123456789;
}
.NET 10 stores the low and high halves separately. .NET 11 loads the value into a vector register and writes all 16 bytes at once.
; x64
; StoreInt128
- mov qword ptr [rcx+8], 75BCD15
- xor eax, eax
- mov [rcx+10], rax
+ vmovss xmm0, dword ptr [RWD00]
+ vmovups [rcx+8], xmm0
-; Total bytes of code 15
+; Total bytes of code 14
The same idea applies when the source code assigns neighboring fields
individually.
dotnet/runtime#126562
enables this for promoted struct locals, while
dotnet/runtime#130107
extends it to adjacent fields at constant static addresses:
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static Point s_point;
[Benchmark]
public void SetPoint() => Set();
[MethodImpl(MethodImplOptions.NoInlining | MethodImplOptions.AggressiveOptimization)]
private static void Set()
{
s_point.X = 1;
s_point.Y = 2;
}
private struct Point
{
public int X;
public int Y;
}
}
The referenced .NET 11 x64 build combines the two 32-bit constants and writes
both fields with one 64-bit store:
; x64
mov rax, 200000001
mov rcx, <address of s_point>
mov [rcx], rax
dotnet/runtime#127487
applies a related improvement when stack protection requires a struct parameter to be copied. It uses consistently sized writes so a subsequent wider read doesn’t need to wait for the processor to reconcile overlapping stores.
Write barriers are only one part of the interaction between generated code
and the garbage collector. During a compacting collection, the GC needs to
plan where surviving objects will move and then update references to them. To
do that efficiently, it records their addresses, sorts those addresses, and
groups adjacent survivors into regions called “plugs.” With enough live
objects, sorting these mark lists becomes a meaningful part of the collection.
Recent x86/x64 runtimes use a vectorized
vxsort
implementation for
sufficiently large lists. In .NET 11,
dotnet/runtime#110692
from
@a74nh
extends that support to Arm64.
The generation assigned to GC metadata matters just as much as the speed of
one collection. .NET’s generational GC is based on the observation that most
objects die young: generation 0 and generation 1 collections, collectively
called ephemeral collections, run frequently and should avoid revisiting
state that has already survived into generation 2. A dependent handle
associates a primary object with a secondary object, keeping the secondary
alive while the primary remains reachable;
ConditionalWeakTable<TKey, TValue>
is built on this mechanism. Previously, the handle itself didn’t age
with its referents, so every ephemeral collection continued scanning it even
after both objects had become long-lived.
dotnet/runtime#78746
ages
dependent handles accordingly and moves a handle back to a younger generation
when necessary. Old handles can therefore be skipped by young collections
without compromising reachability.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private ConditionalWeakTable<object, object> _table = new();
private object[] _keys = [];
[Params(100_000, 1_000_000)]
public int Handles { get; set; }
[GlobalSetup]
public void Setup()
{
_table = new();
_keys = new object[Handles];
for (int i = 0; i < _keys.Length; i++)
{
object key = new();
_keys[i] = key;
_table.Add(key, new object());
}
GC.Collect(2, GCCollectionMode.Forced, blocking: true, compacting: true);
}
[Benchmark]
public void CollectGen0() =>
GC.Collect(0, GCCollectionMode.Forced, blocking: true, compacting: false);
}
|
Method
|
Runtime
|
Handles
|
Mean
|
Ratio
|
|
CollectGen0
|
.NET 10.0
|
100000
|
1.522 ms
|
1.00
|
|
CollectGen0
|
.NET 11.0
|
100000
|
255.5 μs
|
0.17
|
|
CollectGen0
|
.NET 10.0
|
1000000
|
10.737 ms
|
1.00
|
|
CollectGen0
|
.NET 11.0
|
1000000
|
310.7 μs
|
0.029
|
Runtime Knowledge and Frozen Data
The JIT can optimize only the facts it knows. Some facts come from its own analysis; others are contracts supplied by the runtime, such as which helpers have side effects, the length of a newly allocated string, or whether a data object will ever move.
A generic virtual call such as
baseReference.Foo<string>()
may need help from the runtime to find the implementation for both the object’s actual type and the generic argument. If that lookup appears to have arbitrary side effects, the JIT has to perform it exactly where it occurs, rather than possibly resulting on a cached answer from a previous lookup. In .NET 11,
dotnet/runtime#122017
teaches the JIT more precisely which exceptions these runtime helpers can throw and whether they otherwise have side effects. The JIT can then share repeated lookups or move an unchanging lookup out of a loop:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Runtime.CompilerServices;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
public abstract class Base
{
public abstract void Foo<T>();
}
public class Derived : Base
{
public override void Foo<T>() { }
}
private Base _b = new Derived();
[Benchmark]
public void GvmCseHoist()
{
Base b = _b;
b.Foo<string>();
b.Foo<int>();
b.Foo<string>();
b.Foo<int>();
for (int i = 0; i < 10; i++)
b.Foo<double>();
}
}
In .NET 11, the repeated lookups outside the loop are shared and the loop’s lookup is performed once, not ten times.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
GvmCseHoist
|
.NET 10.0
|
45.75 ns
|
1.00
|
|
GvmCseHoist
|
.NET 11.0
|
24.06 ns
|
0.53
|
Profile data is another way the JIT learns what matters. Inlining could previously hide important work from the instrumentation used to gather that data.
dotnet/runtime#119658
allows the inlined code to be instrumented as well, giving later PGO-driven compilation a more complete picture of the hot paths.
JIT Throughput and Cleanup
The quality of the generated code isn’t the only concern; the time spent producing it matters too. Every analysis the JIT performs has a cost.
dotnet/runtime#123856
removes checks and maps from Global Assertion Propagation whose bookkeeping wasn’t paying for itself. This is the recurring balancing act in the development of the JIT: retaining the information that enables meaningful optimizations while avoiding analysis overhead whose code-quality benefit is negligible.
dotnet/runtime#127363
makes profile-guided optimization more resilient with OSR (on-stack replacement), which replaces a method while one of its loops is already running. Because that execution begins in the middle of the method rather than at its normal entry, reconstructed profile data doesn’t always line up perfectly with the paths actually available. The JIT now estimates the likelihood of those paths rather than asserting or abandoning the profile.
Optimizations can leave behind code that’s no longer reachable, so the JIT also needs to be good at dead code removal.
dotnet/runtime#126223
runs another sweep whenever the method’s branching structure changes, catching blocks made obsolete by earlier transformations.
And
dotnet/runtime#128515
from
@BoyBaykiller
repeatedly combines equivalent return and throw endings, removing duplicate exit paths and sometimes exposing more code that can be shared.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Benchmark]
[Arguments((byte)9)]
public bool IsLinearWhiteSpace(byte value) =>
value <= 32 &&
(value == 32 || value == 10 || value == 13 || value == 9);
}
In .NET 10, tail merging combines the paths that return
false
, but not both paths that return
true
. As a result, the JIT’s bit test covers three of the four values, with a separate comparison for
9
. In .NET 11, the true returns are merged as well, enabling all four values to be handled by the same bit test:
; x64
- movzx ecx, dl
- cmp ecx, 20
- jg M00_L02
- cmp ecx, 20
- ja M00_L01
- mov eax, 0FFFFDBFF
- bt rax, rcx
- jae M00_L00
- mov eax, 1
- ret
-M00_L00:
- cmp ecx, 9
- sete al
- movzx eax, al
- ret
-M00_L01:
+ movzx eax, dl
+ cmp eax, 20
+ jg M00_L00
+ cmp eax, 20
+ ja M00_L00
+ mov ecx, 0FFFFD9FF
+ bt rcx, rax
+ jb M00_L00
+ mov eax, 1
+ ret
+M00_L00:
xor eax, eax
ret
-; Total bytes of code 43
+; Total bytes of code 33
Also related to dead code, a call that never returns, such as one that always throws, makes everything after it unreachable. In .NET 11, after inlining,
dotnet/runtime#128513
removes the remaining statements and outgoing paths from such a block and marks it as ending in a throw, exposing the dead code early enough for the cleanup passes above to remove it.
Startup and Deployment
Before managed
Main
can run, the native host needs to locate the application’s dependencies, CoreCLR needs to load enough types and code to begin execution, and various pieces of framework infrastructure need to initialize themselves. Work removed from any of those stages helps the application get going sooner, improving startup time.
The host starts by reading the application’s
.deps.json
, turning its entries into paths, and building the trusted platform assembly (TPA) list. That list tells CoreCLR which framework and application assemblies it can resolve by simple name. Several costs in this process scaled with the number of assets rather than with the amount of useful work.
dotnet/runtime#123568
in .NET 11 avoids checking every asset against a servicing directory unless the resolver is actually probing that directory.
dotnet/runtime#123919
avoids repeatedly comparing the servicing-directory name and copying every dependency asset while constructing the TPA list, avoiding a lot of allocation.
dotnet/runtime#125251
removes more allocation by normalizing each asset’s directory separators once when parsing the
.deps.json
, rather than normalizing the path again every time it is used.
Once the host hands off to CoreCLR, ReadyToRun (R2R) code helps avoid compiling methods before they can execute. However, initializing
Comparer<T>.Default
and
EqualityComparer<T>.Default
called a reflection-based helper whose resulting concrete comparer type wasn’t known when the R2R image was built. The comparer constructor and operations could consequently fall back to being interpreted. In .NET 11,
dotnet/runtime#126204
uses specialized helpers that R2R can compile ahead of time and ensures the required comparer types are included in the image.
Even better than making initialization faster is avoiding it altogether. An
EventSource
normally discovers its event metadata and computes its provider GUID when it is initialized.
dotnet/runtime#121180
adds an internal source generator that performs this work when the framework is built and emits the result for its
EventSource
implementations, including the ones for core runtime tracing. Applications then don’t need to pay the reflection and setup costs when those event sources are first used.
Startup also has a memory footprint outside the managed heap. Native AOT’s
AllocHeap
typically holds only small amounts of runtime metadata. On Windows, however, its virtual-memory allocator reserved a 64 KB region for each block even when it initially needed only 4 KB. In .NET 11,
dotnet/runtime#122822
instead uses ordinary
new
and
delete
for these small blocks, matching the allocation strategy to the amount of memory normally involved.
Note that the aforementioned R2R work wasn’t motivated only by desktop and server startup. It was also
part of the substantial effort to make CoreCLR the runtime for .NET on mobile.
Starting with .NET 11,
.NET MAUI moved to CoreCLR
for Android, iOS, and Mac Catalyst, the last .NET MAUI platforms that had still
been using Mono. This is much more than swapping one execution engine for another. Those apps
now use the same runtime as ASP.NET Core, cloud services, and desktop .NET,
with the same JIT, garbage collector, diagnostics infrastructure, performance improvements, and bug fixes.
It also brings CoreCLR’s tiered compilation, ReadyToRun, and profile-guided
optimization to mobile, while providing a common foundation for NativeAOT.
That combination is important: R2R and packaged profiles can precompile the
code most important to startup, while the optimizing JIT can produce
higher-quality code for hot methods on platforms where dynamic compilation is
available. Improvements like the comparer specialization mentioned earlier keep more code
on the compiled path instead of falling back to interpretation.
Threading
Threading is a cross-cutting concern that impacts almost every
application and service. Whether code is protecting shared state, queueing work, or
coordinating asynchronous operations, small costs in the underlying machinery
can quickly add up. As such, it’s something that’s revisited in every release of .NET.
Monitor
is the synchronization primitive historically used to implement
lock
, providing the most pervasively used support for mutual exclusion. It also supports sending signals, such that one thread can wait on a
Monitor
with
Monitor.Wait
for another thread to
Pulse
it. The internal object that tracks these waiters is a “condition variable.”
dotnet/runtime#129083
stores that condition directly on the lock, removing a separate
ConditionalWeakTable
lookup from this already synchronization-heavy path.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int RoundTripsPerInvoke = 2_000;
private readonly object _gate = new();
private int _ping;
private int _pong;
private bool _stop;
private Thread _responder = null!;
[GlobalSetup]
public void Setup()
{
_responder = new Thread(ResponderLoop) { IsBackground = true };
_responder.Start();
}
[GlobalCleanup]
public void Cleanup()
{
lock (_gate)
{
_stop = true;
Monitor.PulseAll(_gate);
}
_responder.Join();
}
private void ResponderLoop()
{
lock (_gate)
{
int seen = 0;
while (true)
{
while (_ping == seen && !_stop)
Monitor.Wait(_gate);
if (_stop)
return;
seen = _ping;
_pong = seen;
Monitor.PulseAll(_gate);
}
}
}
[Benchmark(OperationsPerInvoke = RoundTripsPerInvoke)]
public int PingPong_MonitorWaitPulse()
{
lock (_gate)
{
for (int i = 0; i < RoundTripsPerInvoke; i++)
{
_ping++;
int expected = _ping;
Monitor.PulseAll(_gate);
while (_pong != expected)
Monitor.Wait(_gate);
}
return _pong;
}
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
PingPong_MonitorWaitPulse
|
.NET 10.0
|
4.194 μs
|
1.00
|
|
PingPong_MonitorWaitPulse
|
.NET 11.0
|
3.517 μs
|
0.84
|
In the case of
Monitor
, that improvement targeted the specific shared implementation. In other cases, the costs are spread out in a more peanut butter manner across lots of code.
dotnet/runtime#125274
removes some of that peanut butter by removing unnecessary
volatile
annotations from a wide range of library fields whose correctness already comes from locks,
Interlocked
, or one-time initialization. On x86/x64 hardware, which already provides a strong memory model, those annotations generally don’t result in extra instructions, though they can still constrain compiler optimizations. Arm, however, permits more reordering, so the JIT often needs to emit memory fences to provide
volatile
‘s guarantees. Removing the annotations where they’re redundant therefore can end up removing unnecessary fences from Arm’s generated code.
Similar considerations apply to code in the runtime.
dotnet/runtime#125259
replaces
full memory barriers in the runtime’s
HashMap
with the narrower acquire and
release operations actually required. On top of that, many VM
hash tables, including its
EEHashTable
, are read constantly but updated only
occasionally.
dotnet/runtime#124822
adds epoch-based reclamation, enabling readers to avoid entering cooperative
GC mode simply to keep an old set of buckets alive. And
dotnet/runtime#129640
replaces
the previous byte-at-a-time hash used by these tables with an xxHash
implementation that consumes four bytes at a time.
Along the same lines, in .NET 11
dotnet/runtime#122726
reduces the scheduling overhead around small thread-pool work items. It removes unnecessary memory fences and shared-state updates, checks in with the thread-pool controller once per batch rather than once per item, spends less time spinning on a semaphore, and requests another worker only when the queued work shows one is needed. The result is less coordination overhead and fewer workers woken just as the queue becomes empty.
Earlier in this post, we talked about runtime async, which can have a significant impact on the performance of
async
/
await
code, how they produce
Task
s, and so on. They’re not the only improvements in .NET 11 related to
Task
s, though.
One fun one is a new analyzer, CA2027, introduced in
dotnet/sdk#51452
. With that, the SDK can point out problematic usage of
Task.Delay
that I’ve seen on multiple occasions to lead to non-trivial performance issues in large scale services. Consider this code:
Task someTask = ...;
if (await Task.WhenAny(someTask, Task.Delay(timeout)) != someTask) // oops!
{
throw new TimeoutException();
}
The developer that wrote this is obviously trying to implement a timeout. The problem, however, is that this leaks. In the hopefully common case where
someTask
completes really quickly, the
Task.Delay
will still be pending. That
Delay
has associated with it a
System.Threading.Timer
that’s consuming valuable resources, as well as other data in memory, and if this
timeout
is long and this code is on a hotter path, we could accumulate thousands upon thousands of those timers. That in turn can increase memory use and slow down other calls that interact with timers.
The fix is to instead use the
Task.WaitAsync
method, introduced all the way back in .NET 6. It provides a much more efficient mechanism for doing this same kind of timed waiting, and it correctly handles all the relevant cleanup. CA2027 will detect common forms of this issue and recommend the replacement.
Numerics
BigInteger
is one of those types that many applications may never need, but
for those that do, there’s often no practical substitute. It powers workloads
ranging from cryptography and number theory to compilers and applications that
need to parse, format, or compute with integers larger than the fixed-width
primitives can hold. Despite that need, however,
BigInteger
hasn’t received the
same steady stream of performance investment as many of .NET’s other core
types. Thankfully, in .NET 11 it gets a makeover.
dotnet/runtime#125799
rewrote significant portions of
BigInteger
‘s implementation, changing its limbs (the fixed-size pieces stored in its backing array) from
uint
to
nuint
(
UIntPtr
). That makes no effective difference on a 32-bit machine. On a 64-bit machine, however, each limb grows from 32 to 64 bits; since most arithmetic on a 64-bit value on a 64-bit platform costs no more than the corresponding 32-bit operation, each step can therefore process twice as many bits in the same number of cycles. The implementation also improves the algorithms around those wider limbs, including Montgomery multiplication and sliding-window exponentiation in
ModPow
, fused bitwise steps, additional hardware intrinsics, loop unrolling, and caching. That all builds on top of other optimizations that were done previously in the release, such as faster conversion of huge values to decimal text in
dotnet/runtime#112178
from
@kzrnm
,
dotnet/runtime#112876
from
@kzrnm
using Toom-Cook multiplication for sufficiently large operands, and improved shifts and rotations thanks to
dotnet/runtime#113005
from
@kzrnm
. Toom-Cook splits each operand into several chunks and combines smaller products, doing less work than the straightforward every-limb-by-every-limb algorithm once the operands are large enough.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics;
using System.Globalization;
using System.Text;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Params(64, 512)]
public int Limbs;
private BigInteger _a;
private BigInteger _b;
private BigInteger _shiftSubject;
private BigInteger _hugeValueForToString;
private string _decimalDigits100000 = "";
private byte[] _utf8Digits1000 = [];
private byte[] _utf8FormatBuffer = new byte[120_000];
private BigInteger _divideDividendBelowThreshold;
private BigInteger _divideDivisorBelowThreshold;
private BigInteger _divideDividendAboveThreshold;
private BigInteger _divideDivisorAboveThreshold;
[GlobalSetup]
public void Setup()
{
_a = MakeDeterministicBigInteger(Limbs, seed: 1);
_b = MakeDeterministicBigInteger(Limbs, seed: 2);
_shiftSubject = MakeDeterministicBigInteger(Limbs, seed: 3);
_decimalDigits100000 = MakeDeterministicDecimalDigits(100_000);
_hugeValueForToString = BigInteger.Parse(_decimalDigits100000, CultureInfo.InvariantCulture);
string decimalDigits1000 = MakeDeterministicDecimalDigits(1_000);
_utf8Digits1000 = Encoding.UTF8.GetBytes(decimalDigits1000);
_divideDivisorBelowThreshold = MakeDeterministicBigInteger(16, seed: 4);
_divideDividendBelowThreshold = MakeDeterministicBigInteger(16 + 96, seed: 5);
_divideDivisorAboveThreshold = MakeDeterministicBigInteger(128, seed: 6);
_divideDividendAboveThreshold = MakeDeterministicBigInteger(128 + 96, seed: 7);
}
private static BigInteger MakeDeterministicBigInteger(int limbCount, int seed)
{
Random rng = new(seed);
byte[] bytes = new byte[(limbCount * 4) + 1]; // trailing 0 byte keeps the value positive
rng.NextBytes(bytes);
bytes[^1] = 0;
return new BigInteger(bytes);
}
private static string MakeDeterministicDecimalDigits(int digitCount)
{
StringBuilder sb = new(digitCount);
sb.Append('9'); // avoid a leading zero, which would shorten the effective digit count
Random rng = new(42);
for (int i = 1; i < digitCount; i++)
sb.Append((char)('0' + rng.Next(0, 10)));
return sb.ToString();
}
[Benchmark]
public BigInteger Divide_BelowBurnikelZieglerThreshold() => _divideDividendBelowThreshold / _divideDivisorBelowThreshold;
[Benchmark]
public BigInteger Divide_AboveBurnikelZieglerThreshold() => _divideDividendAboveThreshold / _divideDivisorAboveThreshold;
[Benchmark]
public BigInteger Multiply() => _a * _b;
[Benchmark]
public BigInteger ShiftLeft() => _shiftSubject << 12345;
[Benchmark]
public BigInteger ParseLargeDecimal() => BigInteger.Parse(_decimalDigits100000, CultureInfo.InvariantCulture);
[Benchmark]
public string ToStringLargeDecimal() => _hugeValueForToString.ToString(CultureInfo.InvariantCulture);
}
|
Method
|
Runtime
|
Limbs
|
Mean
|
Ratio
|
|
Divide_BelowBurnikelZieglerThreshold
|
.NET 10.0
|
64
|
2,954.3 ns
|
1.00
|
|
Divide_BelowBurnikelZieglerThreshold
|
.NET 11.0
|
64
|
1,493.8 ns
|
0.51
|
|
Divide_AboveBurnikelZieglerThreshold
|
.NET 10.0
|
64
|
10,766.7 ns
|
1.00
|
|
Divide_AboveBurnikelZieglerThreshold
|
.NET 11.0
|
64
|
6,303.4 ns
|
0.59
|
|
Multiply
|
.NET 10.0
|
64
|
2,359.5 ns
|
1.00
|
|
Multiply
|
.NET 11.0
|
64
|
1,328.2 ns
|
0.56
|
|
ShiftLeft
|
.NET 10.0
|
64
|
217.1 ns
|
1.00
|
|
ShiftLeft
|
.NET 11.0
|
64
|
121.6 ns
|
0.56
|
|
ParseLargeDecimal
|
.NET 10.0
|
64
|
9,111,926.1 ns
|
1.00
|
|
ParseLargeDecimal
|
.NET 11.0
|
64
|
3,899,478.0 ns
|
0.43
|
|
ToStringLargeDecimal
|
.NET 10.0
|
64
|
135,894,135.4 ns
|
1.00
|
|
ToStringLargeDecimal
|
.NET 11.0
|
64
|
7,868,359.3 ns
|
0.058
|
|
Divide_BelowBurnikelZieglerThreshold
|
.NET 10.0
|
512
|
2,894.6 ns
|
1.00
|
|
Divide_BelowBurnikelZieglerThreshold
|
.NET 11.0
|
512
|
1,482.0 ns
|
0.51
|
|
Divide_AboveBurnikelZieglerThreshold
|
.NET 10.0
|
512
|
10,751.7 ns
|
1.00
|
|
Divide_AboveBurnikelZieglerThreshold
|
.NET 11.0
|
512
|
6,317.8 ns
|
0.59
|
|
Multiply
|
.NET 10.0
|
512
|
68,063.6 ns
|
1.00
|
|
Multiply
|
.NET 11.0
|
512
|
35,443.5 ns
|
0.52
|
|
ShiftLeft
|
.NET 10.0
|
512
|
673.0 ns
|
1.00
|
|
ShiftLeft
|
.NET 11.0
|
512
|
309.4 ns
|
0.46
|
|
ParseLargeDecimal
|
.NET 10.0
|
512
|
9,149,793.0 ns
|
1.00
|
|
ParseLargeDecimal
|
.NET 11.0
|
512
|
3,891,313.0 ns
|
0.43
|
|
ToStringLargeDecimal
|
.NET 10.0
|
512
|
135,829,594.6 ns
|
1.00
|
|
ToStringLargeDecimal
|
.NET 11.0
|
512
|
7,880,631.1 ns
|
0.058
|
In addition to internal changes,
BigInteger
also gained new public APIs that avoid transcoding. Protocols and storage formats increasingly expose text as UTF-8 bytes, but the previous parsing and formatting APIs required UTF-16 characters. Callers therefore had to decode the input into a temporary string before parsing, or format into characters and encode the result back to bytes.
dotnet/runtime#117745
adds direct UTF-8 parsing and formatting to both
BigInteger
and
Complex
, sharing the generic numeric machinery used for UTF-16 and letting those consumers operate on their original representation.
dotnet/runtime#130721
improves a different
BigInteger
boundary: casting to
double
and
float
. The general conversion needs to inspect the arbitrary-width magnitude, locate its highest set bits, and perform the rounding required by the target floating-point format. But many
BigInteger
instances are much smaller than that machinery is designed for… the implementation now recognizes values that fit in 64 bits and routes them through the hardware’s native integer conversion support.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly BigInteger _small = (BigInteger.One << 63) + 123;
private readonly BigInteger _large = (BigInteger.One << 1023) + (BigInteger.One << 511) + 123;
[Benchmark] public double SmallToDouble() => (double)_small;
[Benchmark] public float SmallToSingle() => (float)_small;
[Benchmark] public double LargeToDouble() => (double)_large;
[Benchmark] public float LargeToSingle() => (float)_large;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SmallToDouble
|
.NET 10.0
|
2.873 ns
|
1.00
|
|
SmallToDouble
|
.NET 11.0
|
1.764 ns
|
0.61
|
|
SmallToSingle
|
.NET 10.0
|
3.548 ns
|
1.00
|
|
SmallToSingle
|
.NET 11.0
|
1.764 ns
|
0.50
|
|
LargeToDouble
|
.NET 10.0
|
2.863 ns
|
1.00
|
|
LargeToDouble
|
.NET 11.0
|
2.797 ns
|
0.98
|
|
LargeToSingle
|
.NET 10.0
|
3.559 ns
|
1.00
|
|
LargeToSingle
|
.NET 11.0
|
2.849 ns
|
0.80
|
The same limb-widening advantages given to
BigInteger
in .NET 11 were also extended to the core floating-point types. Parsing a very long decimal input and formatting a floating-point value with many requested digits both need temporary arbitrary-precision arithmetic once the value no longer fits in the normal mantissa. .NET uses a separate internal
Number.BigInteger
for that work.
dotnet/runtime#132577
applies the same native-width limb representation to that type, reducing the amount of per-limb work in floating-point parsing, formatting, and rounding.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Globalization;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _longFraction = "0." + new string('1', 768);
[Benchmark]
public double ParseLongFraction() => double.Parse(_longFraction, CultureInfo.InvariantCulture);
[Benchmark]
public string FormatSubnormal() => double.Epsilon.ToString("G99", CultureInfo.InvariantCulture);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ParseLongFraction
|
.NET 10.0
|
8.592 μs
|
1.00
|
|
ParseLongFraction
|
.NET 11.0
|
3.569 μs
|
0.42
|
|
FormatSubnormal
|
.NET 10.0
|
6.884 μs
|
1.00
|
|
FormatSubnormal
|
.NET 11.0
|
1.237 μs
|
0.18
|
The .NET 11 improvements aren’t limited to the scalar representations underlying
BigInteger
and floating-point parsing and formatting. Other numerical types improve as well. Consider
Matrix4x4
. A 4×4 matrix
determinant combines products of many independent matrix elements, making it a
natural fit for SIMD.
dotnet/runtime#123954
from
@alexcovington
adds an SSE
implementation of
Matrix4x4.GetDeterminant
, evaluating several of those
products in parallel:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Matrix4x4 _matrix =
Matrix4x4.CreateFromYawPitchRoll(0.4f, 0.8f, 1.1f) *
Matrix4x4.CreateTranslation(1.5f, -2.5f, 3.25f) *
Matrix4x4.CreateScale(1.1f, 0.9f, 1.05f);
[Benchmark]
public float GetDeterminant() => _matrix.GetDeterminant();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
GetDeterminant
|
.NET 10.0
|
3.836 ns
|
1.00
|
|
GetDeterminant
|
.NET 11.0
|
2.645 ns
|
0.69
|
The
System.Numerics.Tensors
APIs are designed to perform the same numerical operation over many values, making them a natural fit for SIMD.
dotnet/runtime#126052
adds vector implementations of inverse sine to the portable vector types and uses them in
TensorPrimitives.Asin
. The tensor loop now evaluates a polynomial approximation for several inputs together, with special handling near the ends of the function’s
[-1, 1]
domain, rather than calling
MathF.Asin
or
Math.Asin
separately for every element:
// Run separately so each target uses its matching System.Numerics.Tensors package:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Numerics.Tensors;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int Length = 4096;
private float[] _floatsIn = new float[Length];
private float[] _floatsOut = new float[Length];
private double[] _doublesIn = new double[Length];
private double[] _doublesOut = new double[Length];
[GlobalSetup]
public void Setup()
{
Random rng = new(42);
for (int i = 0; i < Length; i++)
{
float v = (float)((rng.NextDouble() * 2.0) - 1.0); // Asin's domain is [-1, 1]
_floatsIn[i] = v;
_doublesIn[i] = v;
}
}
[Benchmark]
public float AsinFloat()
{
TensorPrimitives.Asin(_floatsIn, _floatsOut);
return _floatsOut[0];
}
[Benchmark]
public double AsinDouble()
{
TensorPrimitives.Asin(_doublesIn, _doublesOut);
return _doublesOut[0];
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
AsinFloat
|
.NET 10.0
|
33.72 μs
|
1.00
|
|
AsinFloat
|
.NET 11.0
|
8.240 μs
|
0.24
|
|
AsinDouble
|
.NET 10.0
|
35.80 μs
|
1.00
|
|
AsinDouble
|
.NET 11.0
|
10.975 μs
|
0.31
|
TensorPrimitives
also picked up a few more targeted SIMD improvements. For floating-point values,
BitIncrement
and
BitDecrement
move to the immediately adjacent representable value; despite their names, they can’t simply add or subtract one, as they also need to handle signed zero, infinities, and NaNs correctly.
dotnet/runtime#123610
and
dotnet/runtime#123754
process multiple
float
/
double
and
Half
values at once, respectively. The
Half
path works directly with the raw
ushort
bit patterns, avoiding conversion to
float
and back, and both paths use vector masks and conditional selection rather than calling a scalar helper for every element.
// Run separately so each target uses its matching System.Numerics.Tensors package:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Numerics.Tensors;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int Length = 4096;
private readonly float[] _floats = new float[Length];
private readonly float[] _floatDestination = new float[Length];
private readonly double[] _doubles = new double[Length];
private readonly double[] _doubleDestination = new double[Length];
private readonly Half[] _halves = new Half[Length];
private readonly Half[] _halfDestination = new Half[Length];
[GlobalSetup]
public void Setup()
{
for (int i = 0; i < Length; i++)
{
float value = (i & 7) switch
{
0 => 0,
1 => -0.0f,
2 => float.PositiveInfinity,
3 => float.NegativeInfinity,
4 => float.NaN,
_ => i / 7.0f,
};
_floats[i] = value;
_doubles[i] = value;
_halves[i] = (Half)value;
}
}
[Benchmark]
public void BitIncrementFloat() => TensorPrimitives.BitIncrement(_floats, _floatDestination);
[Benchmark]
public void BitIncrementDouble() => TensorPrimitives.BitIncrement(_doubles, _doubleDestination);
[Benchmark]
public void BitIncrementHalf() => TensorPrimitives.BitIncrement(_halves, _halfDestination);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
BitIncrementFloat
|
.NET 10.0
|
4.223 μs
|
1.00
|
|
BitIncrementFloat
|
.NET 11.0
|
1,071.1 ns
|
0.25
|
|
BitIncrementDouble
|
.NET 10.0
|
4.223 μs
|
1.00
|
|
BitIncrementDouble
|
.NET 11.0
|
2,140.6 ns
|
0.51
|
|
BitIncrementHalf
|
.NET 10.0
|
3.918 μs
|
1.00
|
|
BitIncrementHalf
|
.NET 11.0
|
573.6 ns
|
0.15
|
dotnet/runtime#124280
removes a more mechanical cost from
TensorPrimitives.Round
: for
digits == 0
, the old code invoked a full-span rounding kernel and then continued through another full-span pass. Returning immediately removes that redundant traversal and overwrite of the destination.
// Run separately so each target uses its matching System.Numerics.Tensors package:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Numerics.Tensors;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int Length = 4096;
private readonly float[] _source = new float[Length];
private readonly float[] _destination = new float[Length];
[Benchmark]
public void RoundZero() => TensorPrimitives.Round(_source, 0, MidpointRounding.ToEven, _destination);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
RoundZero
|
.NET 10.0
|
882.7 ns
|
1.00
|
|
RoundZero
|
.NET 11.0
|
205.5 ns
|
0.23
|
Half
comparisons are faster as well. Previously,
Half.CompareTo
separately
asked whether one value was less than, greater than, or equal to the other,
repeating the special handling required for NaN and signed zero each time.
dotnet/runtime#131297
performs
that work once and then arranges the underlying bits into a form that can be
compared directly, while still treating
+0
and
-0
as equal. On x64 with
AVX2, it also makes
CompareTo
,
<
, and
<=
faster by converting the operands
to
float
, which the hardware can do very efficiently. Equality remains
bit-based, as that’s already the cheaper approach.
// Run on x64 with AVX2:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Half[] _left = Enumerable.Range(0, 4096).Select(i => (Half)(i - 2048)).ToArray();
private readonly Half[] _right = Enumerable.Range(0, 4096).Select(i => (Half)(2048 - i)).ToArray();
[Benchmark]
public int CompareTo()
{
int sum = 0;
for (int i = 0; i < _left.Length; i++)
sum += _left[i].CompareTo(_right[i]);
return sum;
}
[Benchmark]
public int LessThan()
{
int count = 0;
for (int i = 0; i < _left.Length; i++)
count += _left[i] < _right[i] ? 1 : 0;
return count;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
CompareTo
|
.NET 10.0
|
9.340 μs
|
1.00
|
|
CompareTo
|
.NET 11.0
|
5.745 μs
|
0.62
|
|
|
|
|
|
|
LessThan
|
.NET 10.0
|
7.514 μs
|
1.00
|
|
LessThan
|
.NET 11.0
|
5.672 μs
|
0.75
|
Multiplying two 64-bit integers produces a 128-bit result, and x64 has instructions that provide both 64-bit halves directly.
dotnet/runtime#117261
from
@Daniel-Svensson
exposes those signed and unsigned forms through an
X86Base.X64.BigMul
intrinsic.
Math.BigMul
can then map directly to
imul
or
mul
and return both halves in registers, avoiding the extra instructions and register shuffling required by the previous paths.
// Run on x64:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser, HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly long _signedLeft = 0x1234_5678_9ABC_DEF;
private readonly long _signedRight = 0x0FED_CBA9_8765_432;
private readonly ulong _unsignedLeft = 0xFEDC_BA98_7654_3210;
private readonly ulong _unsignedRight = 0x1234_5678_9ABC_DEF0;
[Benchmark]
public long Signed()
{
long high = Math.BigMul(_signedLeft, _signedRight, out long low);
return high ^ low;
}
[Benchmark]
public ulong Unsigned()
{
ulong high = Math.BigMul(_unsignedLeft, _unsignedRight, out ulong low);
return high ^ low;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Code Size
|
|
Signed
|
.NET 10.0
|
2.210 ns
|
1.00
|
65 B
|
|
Signed
|
.NET 11.0
|
1.344 ns
|
0.61
|
12 B
|
|
|
|
|
|
|
|
Unsigned
|
.NET 10.0
|
1.446 ns
|
1.00
|
39 B
|
|
Unsigned
|
.NET 11.0
|
1.323 ns
|
0.92
|
12 B
|
Fixed-format numeric and identifier helpers benefit from a much simpler technique: establish the exact span length once, then let the JIT reuse that fact.
dotnet/runtime#119254
from
@xtqqczze
applies that pattern in
Decimal
,
Guid
, and
IPAddress
, removing repeated bounds checks.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const string Value = "a8098c1a-f86e-11da-bd1a-00112444be1e";
[Benchmark]
public bool TryParseExactD() => Guid.TryParseExact(Value, "D", out _);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
TryParseExactD
|
.NET 10.0
|
15.94 ns
|
1.00
|
|
TryParseExactD
|
.NET 11.0
|
12.60 ns
|
0.79
|
Guid
has been improving every .NET release, and sees several improvements in .NET 11. Whenever possible, .NET tries to maintain similar performance and behaviors across operating systems, but low-level functionality often simply delegates to the operating system, exposing that OS’ characteristics. When it comes to random number generation, historically cryptographically-secure random number generation, as is used in
Guid.NewGuid
, has been a bit slower on Linux than on Windows due to using
/dev/urandom
as the source of entropy.
dotnet/runtime#123540
from
@reedz
moves
Guid.NewGuid()
off of that file-descriptor path to the
getrandom()
syscall, avoiding descriptor setup and reads through the file abstraction.
And on the subject of randomness,
dotnet/runtime#119890
from
@hamarb123
removes two pieces of work from
Random.Shuffle
: an unnecessary copy of the span length and a branch that skipped swapping an element with itself. A self-swap is harmless and uncommon, while testing for it adds an unpredictable branch to every iteration. The difference is most visible for short arrays and small value types, where the swap itself is cheap:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Params(16, 4096)]
public int Length;
private readonly Random _random = new(42);
private int[] _values = [];
[GlobalSetup]
public void Setup() => _values = Enumerable.Range(0, Length).ToArray();
[Benchmark]
public int ShuffleSmallValueType()
{
_random.Shuffle(_values);
return _values[0] + _values[^1];
}
}
|
Method
|
Runtime
|
Length
|
Mean
|
Ratio
|
|
ShuffleSmallValueType
|
.NET 10.0
|
16
|
138.9 ns
|
1.00
|
|
ShuffleSmallValueType
|
.NET 11.0
|
16
|
89.34 ns
|
0.64
|
|
ShuffleSmallValueType
|
.NET 10.0
|
4096
|
25,925.1 ns
|
1.00
|
|
ShuffleSmallValueType
|
.NET 11.0
|
4096
|
14,151.08 ns
|
0.55
|
Random
itself picked up a small but pointed code-generation fix.
Random.InternalSample
contains a condition that’s inherently hard for the processor to predict, so it’s better implemented with conditional instructions than with a branch. The JIT’s if-conversion support we previously discussed would have been able to do that transformation, except it doesn’t currently support if-conversion inside of loops, which is a pretty common place to find an inlined
Random.Next
call.
dotnet/runtime#131714
marks the helper as
[MethodImpl(MethodImplOptions.NoInlining)]
to preserve the branch-free form; once the JIT can perform if-conversion inside loops, that annotation can be reconsidered.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Random _random = new(42);
[Benchmark]
public int Next()
{
int sum = 0;
for (int i = 0; i < 1024; i++)
sum += _random.Next();
return sum;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Next
|
.NET 10.0
|
5.954 μs
|
1.00
|
|
Next
|
.NET 11.0
|
3.275 μs
|
0.55
|
Globalization
Many globalization-related APIs sit atop data that can be expensive to locate
and interpret.
DateTime.Now
, for example, depends on time-zone transition
data, while casing and parsing depend on native globalization services and
culture-specific tables.
dotnet/runtime#119662
substantially reworks
TimeZoneInfo
around that observation. Determining an offset isn’t always a fixed arithmetic operation: daylight-saving rules can vary by year, and historical rules can contain multiple transitions and exceptional cases. Once the transitions for a zone and year have been interpreted, however, other conversions in that year can reuse them. Similarly, the local offset used by
DateTime.Now
can’t change between transition instants. Conversions now reuse cached per-year transition data rather than repeatedly walking adjustment rules, while
DateTime.Now
caches the active UTC offset together with the instant at which it next needs to be recomputed.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly DateTime _utc = new(2026, 7, 15, 12, 0, 0, DateTimeKind.Utc);
private readonly DateTime _local = new(2026, 7, 15, 5, 0, 0, DateTimeKind.Unspecified);
private readonly TimeZoneInfo _zone = TimeZoneInfo.FindSystemTimeZoneById(
OperatingSystem.IsWindows() ? "Pacific Standard Time" : "America/Los_Angeles");
[Benchmark]
public DateTime ConvertTimeFromUtc() => TimeZoneInfo.ConvertTimeFromUtc(_utc, _zone);
[Benchmark]
public DateTime ConvertTimeToUtc() => TimeZoneInfo.ConvertTimeToUtc(_local, _zone);
[Benchmark]
public DateTime GetLocalNow() => DateTime.Now;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ConvertTimeFromUtc
|
.NET 10.0
|
45.13 ns
|
1.00
|
|
ConvertTimeFromUtc
|
.NET 11.0
|
19.44 ns
|
0.43
|
|
ConvertTimeToUtc
|
.NET 10.0
|
51.97 ns
|
1.00
|
|
ConvertTimeToUtc
|
.NET 11.0
|
20.23 ns
|
0.39
|
|
GetLocalNow
|
.NET 10.0
|
76.41 ns
|
1.00
|
|
GetLocalNow
|
.NET 11.0
|
34.39 ns
|
0.45
|
dotnet/runtime#120685
separates two costs in invariant casing. With the normal globalization configuration,
ToUpperInvariant
and
ToLowerInvariant
now try a managed ASCII path first, so casing ASCII text can avoid or delay initialization of ICU, the native library .NET uses for culture-aware globalization. In invariant-globalization mode, where ICU isn’t loaded at all, that managed path also improves ASCII casing throughput. Non-ASCII input still needs the appropriate globalization path.
// DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1 dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _short = "runtime";
private readonly string _long = new('a', 139);
[Benchmark]
public string ShortAscii() => _short.ToUpperInvariant();
[Benchmark]
public string LongAscii() => _long.ToUpperInvariant();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
|
ShortAscii
|
.NET 10.0
|
18.12 ns
|
1.00
|
40 B
|
|
ShortAscii
|
.NET 11.0
|
14.62 ns
|
0.81
|
40 B
|
|
LongAscii
|
.NET 10.0
|
248.38 ns
|
1.00
|
304 B
|
|
LongAscii
|
.NET 11.0
|
39.22 ns
|
0.16
|
304 B
|
Several smaller changes remove setup around date and culture data.
dotnet/runtime#123886
allocates the
DateTimeFormatInfo
date-word table only for cultures that actually contain such words. And
dotnet/runtime#122918
replaces synchronized, boxing
Hashtable
caches used by time-zone and encoding tables with typed
ConcurrentDictionary
instances.
The round-trip
"O"
date format always contains exactly seven fractional-second digits, matching the 10,000,000 ticks in a second.
dotnet/runtime#129005
parses those digits directly as ticks, avoiding a conversion through
double
followed by division, multiplication, and rounding. Formatting benefits from specialization as well.
dotnet/runtime#129374
routes invariant
DateTime.ToString("G")
through the existing fixed-format fast path, bypassing the general culture-aware formatter.
DateTimeOffset
retains the general path because its offset changes the output:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Globalization;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly DateTime _dateTime = new(2024, 3, 15, 13, 45, 30, DateTimeKind.Utc);
[Benchmark]
public string DateTime_ToString_G() => _dateTime.ToString("G", CultureInfo.InvariantCulture);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
DateTime_ToString_G
|
.NET 10.0
|
65.54 ns
|
1.00
|
|
DateTime_ToString_G
|
.NET 11.0
|
29.76 ns
|
0.45
|
Strings and Spans
UTF-8 is everywhere, from web protocols and JSON payloads to files on disk.
Since .NET strings use UTF-16, applications frequently need to convert between
the two, making it especially important for those conversions to be fast.
UTF-8 encoding must validate UTF-16 surrogate pairs as it counts and converts
them. On Arm64, the vectorized implementation in .NET 10 still examined
individual elements when counting the resulting UTF-8 bytes and checking that
surrogates were correctly paired. That gets expensive for text containing many
supplementary characters, as every surrogate-heavy vector falls back to this
element-by-element work.
dotnet/runtime#121981
from
@ylpoonlg
instead performs the counting and
surrogate checks with vector-wide operations. As part of that work, it also
unifies most of the x86 and Arm64 implementations, retaining small
platform-specific helpers where the instruction sets differ:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Text;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int Length = 4096;
private string _validWithSurrogatePairs = string.Empty;
[GlobalSetup]
public void Setup()
{
Random rng = new(42);
StringBuilder sb = new(Length);
while (sb.Length < Length - 2)
{
sb.Append((char)('A' + rng.Next(0, 26)));
sb.Append("\U0001F600"); // emoji -> surrogate pair
}
_validWithSurrogatePairs = sb.ToString();
}
[Benchmark]
public int ValidWithSurrogatePairs() => Encoding.UTF8.GetByteCount(_validWithSurrogatePairs);
}
This input deliberately contains a surrogate pair for every ASCII character,
making the removed per-element work especially visible.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ValidWithSurrogatePairs
|
.NET 10.0
|
2.994 μs
|
1.00
|
|
ValidWithSurrogatePairs
|
.NET 11.0
|
856.8 ns
|
0.29
|
The byte-to-char direction was also improved on Arm. UTF-8 decoding can copy ASCII bytes directly to UTF-16 characters, but as soon as we find the first non-ASCII byte, we need the full multi-byte decoder. The vector loop therefore needs both a fast test for whether any lane is non-ASCII and, only when one is found, its exact position. Calculating that position for every all-ASCII vector wastes work on the overwhelmingly common fast path.
dotnet/runtime#121382
from
@ylpoonlg
first performs the cheap vector-wide test and then computes the lane index only after that test succeeds.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Text;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly byte[] _ascii = Enumerable.Repeat((byte)'a', 16_384).ToArray();
[Benchmark]
public int Utf8GetCharCount() => Encoding.UTF8.GetCharCount(_ascii);
}
With all-ASCII input, every vector can stay on the cheap path:
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Utf8GetCharCount
|
.NET 10.0
|
443.5 ns
|
1.00
|
|
Utf8GetCharCount
|
.NET 11.0
|
210.6 ns
|
0.47
|
Base64 is commonly used when binary data needs to travel through
text-oriented formats and protocols. Its encoder naturally works in groups of
three input bytes and four output characters, but the line-breaking option
also needs to stop at the MIME-style 76-character boundary and insert
\r\n
.
The older implementation handled that formatting through a separate scalar
path.
dotnet/runtime#123403
brings the optimized span-based Base64 encoder to
Convert.ToBase64String
with
Base64FormattingOptions.InsertLineBreaks
, processing each line with the same vectorized core and handling the separators around it:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Params(57, 570)]
public int ByteLength { get; set; }
private byte[] _bytes = [];
[GlobalSetup]
public void Setup()
{
_bytes = new byte[ByteLength];
new Random(42).NextBytes(_bytes);
}
[Benchmark]
public string ToBase64String_InsertLineBreaks() => Convert.ToBase64String(_bytes, Base64FormattingOptions.InsertLineBreaks);
}
|
Method
|
Runtime
|
ByteLength
|
Mean
|
Ratio
|
|
ToBase64String_InsertLineBreaks
|
.NET 10.0
|
57
|
60.95 ns
|
1.00
|
|
ToBase64String_InsertLineBreaks
|
.NET 11.0
|
57
|
23.91 ns
|
0.39
|
|
ToBase64String_InsertLineBreaks
|
.NET 10.0
|
570
|
560.66 ns
|
1.00
|
|
ToBase64String_InsertLineBreaks
|
.NET 11.0
|
570
|
194.99 ns
|
0.35
|
Base64 decoding got the same treatment from the other direction.
Base64.DecodeFromUtf8InPlace
decodes in place, overwriting the encoded input with the decoded bytes. In .NET 10, it still employed a scalar loop, long after the out-of-place
DecodeFromUtf8
had acquired AVX-512, AVX2, AdvSimd, and SSSE3 paths. In-place decoding turns out to be safe to vectorize precisely because of Base64’s ratio: 4 bytes read produce 3 bytes written, so the write cursor always trails the read cursor, and each vector store, including its zero-padded overshoot, ends at or before the next vector load and never clobbers source that hasn’t been read yet.
dotnet/runtime#131333
therefore reuses the existing decode helpers for the in-place path.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Buffers;
using System.Buffers.Text;
using System.Text;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly byte[] _encoded = Encoding.ASCII.GetBytes(Convert.ToBase64String(new byte[16_384]));
private byte[] _buffer = [];
[IterationSetup]
public void Setup() => _buffer = (byte[])_encoded.Clone();
[Benchmark]
public OperationStatus Decode() => Base64.DecodeFromUtf8InPlace(_buffer, out _);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Decode
|
.NET 10.0
|
10.70 μs
|
1.00
|
|
Decode
|
.NET 11.0
|
2.256 μs
|
0.21
|
MemoryExtensions.CommonPrefixLength
compares two spans and returns how many
elements they share at the beginning (“hello” and “help”, for example, have a
common prefix length of 3). Internally, it utilizes a helper that slices whichever input was longer to
the length of the shorter one.
dotnet/runtime#121104
from
@xtqqczze
simplifies that helper: after
shortening the second span if necessary, it always slices the first span to
the second’s length. That gives the JIT the same explicit relationship between
the two lengths regardless of which input started out longer.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System;
using System.Linq;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string[] _shorter = Enumerable.Repeat("value", 64).ToArray();
private readonly string[] _longer = Enumerable.Repeat("value", 128).ToArray();
[Benchmark]
public int ShorterFirst() => _shorter.AsSpan().CommonPrefixLength(_longer);
[Benchmark]
public int LongerFirst() => _longer.AsSpan().CommonPrefixLength(_shorter);
}
The longer-first case was already efficient. The change improves the
shorter-first case, bringing the two orderings to essentially the same
throughput:
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ShorterFirst
|
.NET 10.0
|
45.16 ns
|
1.00
|
|
ShorterFirst
|
.NET 11.0
|
25.43 ns
|
0.56
|
|
LongerFirst
|
.NET 10.0
|
26.40 ns
|
1.00
|
|
LongerFirst
|
.NET 11.0
|
26.31 ns
|
1.00
|
Text processing often starts by obtaining an
Encoding
. Properties such as
Encoding.UTF8
provide fast access to popular encodings, while legacy code
pages can be made available by registering
CodePagesEncodingProvider
. In
.NET 10, that provider’s tables, including the name lookup used by
Encoding.GetEncoding(string)
once the provider is registered, used
reader-writer locks.
dotnet/runtime#125001
replaces those caches with
ConcurrentDictionary
instances, allowing
warmed-up provider lookups to proceed without acquiring the reader lock.
On
string
itself,
dotnet/runtime#130361
from
@prozolic
recognizes when
string.Concat(IEnumerable<string?>)
receives a
string[]
or
List<string?>
and passes its contiguous storage directly to the span-based implementation:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Collections.Generic;
using System.Linq;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly IEnumerable<string?> _array = Enumerable.Range(0, 1_000).Select(i => i.ToString()).ToArray();
private readonly IEnumerable<string?> _list = Enumerable.Range(0, 1_000).Select(i => i.ToString()).ToList();
[Benchmark]
public string Array() => string.Concat(_array);
[Benchmark]
public string List() => string.Concat(_list);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
|
Array
|
.NET 10.0
|
4.230 μs
|
1.00
|
5.7 KB
|
|
Array
|
.NET 11.0
|
3.285 μs
|
0.78
|
5.67 KB
|
|
List
|
.NET 10.0
|
6.703 μs
|
1.00
|
5.71 KB
|
|
List
|
.NET 11.0
|
3.253 μs
|
0.49
|
5.67 KB
|
Some of my favorite improvements in .NET are the tiny ones that show up everywhere. A good example of that is in
dotnet/roslyn#82729
. Previously, when you wrote
span[start..]
, the compiler would lower that to the equivalent of
span.Slice(start, span.Length - start)
. The JIT has made strides towards compiling this exactly how it would
span.Slice(start)
, but everyone is better off if the C# compiler just emits that in the first place. And it now does. The difference is clear in the IL for a method that returns
span[start..]
:
; Platform-independent IL
-// Before: 21 bytes
+// After: 9 bytes
-.locals init ([0] System.Span<char>&, [1] int32)
ldarga.s span
-stloc.0
ldarg.1
-stloc.1
-ldloc.0
-ldloc.1
-ldloc.0
-call instance int32 System.Span<char>::get_Length()
-ldloc.1
-sub
-call instance System.Span<char> System.Span<char>::Slice(int32, int32)
+call instance System.Span<char> System.Span<char>::Slice(int32)
ret
Searching and Comparing
Searching in one way, shape, or form is one of the most common things programs do. And when it comes to searching text, regular expressions are an extremely common and helpful way to specify and perform said search. .NET’s regex support has improved by leaps and bounds over the years, with significant investments in .NET 5 and .NET 7 and then every release since, including .NET 11.
When a
Regex
instance is created, it needs to parse the incoming regular expression pattern and turn it into a form it can utilize for performing the actual searches. The regex language is very expressive and enables multiple ways of specifying the same pattern, some more efficient to process than others, so as part of parsing,
Regex
applies a variety of simplifications and optimizations over the parsed tree in order to put it into an ideal form, as well as to learn facts about the pattern to further optimize later processing (such as discovering a minimum and maximum length of any possible match). Each of these transformations can in turn expose more opportunity for other transformations, but based on the order the transformations are applied, sometimes those opportunities can be missed. In .NET 11,
dotnet/runtime#125289
gives compiled and source-generated regexes one final cleanup pass after the whole-pattern optimizations have reshaped the pattern. Consider the pattern
[ab]+c[ab]+|[ab]+
. On input containing a long run of
a
s with no
c
, the .NET 10 source-generated matcher first scans the whole run for the first alternative, fails when it doesn’t find the
c
, and then scans the same run again for the second alternative. The final cleanup pass factors out the common
[ab]+
, leaving
c[ab]+
as an optional suffix:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Text.RegularExpressions;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class Benchmarks
{
private readonly string _input = new('a', 4096);
[Benchmark]
public bool SharedPrefix() => SharedPrefixRegex().IsMatch(_input);
[GeneratedRegex("[ab]+c[ab]+|[ab]+")]
private static partial Regex SharedPrefixRegex();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SharedPrefix
|
.NET 10.0
|
550.9 ns
|
1.00
|
|
SharedPrefix
|
.NET 11.0
|
282.8 ns
|
0.51
|
Beyond doing additional passes, several other changes improve what those
analysis passes can see. For example, for a pattern like
(http|https)
with
ordinal ignore-case matching, for uninteresting reasons previously the engine
would extract a prefix of
"htt"
, even though it could have extracted
"http"
.
dotnet/runtime#124881
improves that, enabling the engine to skip far more false candidates. The
input here contains 25,000
"htt"
prefixes that aren’t followed by a
p
before the final match:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Text.RegularExpressions;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class Benchmarks
{
private readonly string _input = string.Concat(Enumerable.Repeat("httx", 25_000)) + "https";
[Benchmark]
public bool IgnoreCaseAlternation() => Http.IsMatch(_input);
[GeneratedRegex("(http|https)", RegexOptions.IgnoreCase)]
private static partial Regex Http { get; }
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
IgnoreCaseAlternation
|
.NET 10.0
|
415.0 μs
|
1.00
|
|
IgnoreCaseAlternation
|
.NET 11.0
|
7.012 μs
|
0.017
|
When those transformation passes are looking for various patterns, sometimes small
things obscure what they’re trying to see, and they miss optimizations.
dotnet/runtime#124842
improves a case where captures were getting in the way of identifying a
searchable prefix. For a pattern like
\b(in)\b
with
RegexOptions.IgnoreCase
, it will now discover it can search for
ordinal-ignore-case
"in"
.
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Text.RegularExpressions;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class Benchmarks
{
private readonly string _input = string.Concat(Enumerable.Repeat("xn ", 33_333)) + "in";
[Benchmark]
public bool IgnoreCaseCapturedPrefix() => CapturedPrefix.IsMatch(_input);
[GeneratedRegex(@"\b(in)\b", RegexOptions.IgnoreCase)]
private static partial Regex CapturedPrefix { get; }
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
IgnoreCaseCapturedPrefix
|
.NET 10.0
|
277.7 μs
|
1.00
|
|
IgnoreCaseCapturedPrefix
|
.NET 11.0
|
7.286 μs
|
0.026
|
As these cases highlight, one of the most impactful things we can do for regular expression processing is improve the engine’s ability to find things to search for as the next possible place a match could apply, and to optimize that search.
dotnet/runtime#124736
does that. For compiled, source-generated, and
NonBacktracking
regexes, it improves how the engine is able to search for one of several literal prefixes. For
agggtaaa|tttaccct
, for example, the .NET 10 source generator first searched for
[ag]
at offset 3 and then checked nearby characters for
[gt]
. That’s a weak filter for an input full of
a
characters, where almost every position becomes a candidate. The .NET 11 generator instead searches for the complete
agggtaaa
and
tttaccct
strings with
SearchValues<string>
. A frequency heuristic selects this approach only for case-sensitive alternatives where whole-string searching is expected to reject more false candidates than the available character-set filter.
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Text.RegularExpressions;
BenchmarkSwitcher.FromAssembly(typeof(RegexPrefixBenchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class RegexPrefixBenchmarks
{
private const string Pattern = "agggtaaa|tttaccct";
private readonly string _match = new string('a', 100_000) + "tttaccct";
private readonly string _miss = new('a', 100_000);
[Benchmark]
public bool Match() => Generated.IsMatch(_match);
[Benchmark]
public bool Miss() => Generated.IsMatch(_miss);
[GeneratedRegex(Pattern)]
private static partial Regex Generated { get; }
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Match
|
.NET 10.0
|
861.9 μs
|
1.00
|
|
Match
|
.NET 11.0
|
9.251 μs
|
0.011
|
|
Miss
|
.NET 10.0
|
861.4 μs
|
1.00
|
|
Miss
|
.NET 11.0
|
9.647 μs
|
0.011
|
Of course, searching for the next place to match isn’t the only opportunity for improvement. Once you’ve found that place, you need to try to match, and we want to optimize that further, too.
Consider the pattern
\b\w+n\b
. The
\w+
can match
n
, which means we can’t automatically treat this loop as being atomic. Normally, after matching the loop greedily and failing to match
n
, we’d need to backtrack looking for the next viable place to match the
n
. But if what comes after the
n
(in this case, a boundary) can’t possibly match the loop, we can avoid doing that search.
dotnet/runtime#125636
teaches the compiled and source-generated engines to prove that and test the final position directly rather than searching backward through the loop’s existing match. The same idea applies to other loops followed by a literal when the engine can prove that trying earlier positions can’t change the result.
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Running;
using System.Text.RegularExpressions;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class Benchmarks
{
private const int WordLength = 5000;
private readonly string _matchingWord = new string('a', WordLength - 1) + "n";
private readonly string _nonMatchingWord = new string('a', WordLength - 1) + "b";
[GeneratedRegex(@"\b\w+n\b")]
private static partial Regex Generated { get; }
[Benchmark]
public bool Matching() => Generated.IsMatch(_matchingWord);
[Benchmark]
public bool NonMatching() => Generated.IsMatch(_nonMatchingWord);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Matching
|
.NET 10.0
|
3.441 μs
|
1.00
|
|
Matching
|
.NET 11.0
|
3.118 μs
|
0.91
|
|
NonMatching
|
.NET 10.0
|
83.656 μs
|
1.00
|
|
NonMatching
|
.NET 11.0
|
69.984 μs
|
0.84
|
A match can sometimes be ruled out before examining any of the input’s
characters. When matching starts at position zero, a fixed-length pattern with
a leading
\A
or non-multiline
^
and a trailing
\z
can match only when the
whole input has exactly that length.
dotnet/runtime#120916
emits
that length check up front for the compiled and source-generated engines when
the computed maximum length equals the minimum required length. Here, the
pattern requires exactly 512 characters while the input contains 513:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Text.RegularExpressions;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public partial class Benchmarks
{
private readonly string _tooLong = new('a', 513);
[GeneratedRegex(@"\A[a-z]{512}\z")]
private static partial Regex Generated { get; }
[Benchmark]
public bool AnchoredReject() => Generated.IsMatch(_tooLong);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
AnchoredReject
|
.NET 10.0
|
41.06 ns
|
1.00
|
|
AnchoredReject
|
.NET 11.0
|
16.05 ns
|
0.39
|
In general, we’ve tried to keep the compilers behind
RegexOptions.Compiled
(which emits IL) and the source generator (which emits C#) as close to 1:1 as possible. There are a few cases, however, where they have diverged from each other, generally where one was able to easily utilize some feature of the target language the other didn’t have. A good example is with alternations. If several left-to-right atomic branches each begin with a different literal character, the engine can read that character and jump straight to the matching branch rather than testing each branch in order. With C#, we emitted a
switch
, which the C# compiler could then lower to IL using various strategies. For IL, in .NET 10 and earlier, without the C# compiler to provide those optimizations, we just skipped the optimization. Now in .NET 11,
dotnet/runtime#122959
emits a similar implementation to what the C# compiler would have, bringing this optimization to
RegexOptions.Compiled
.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Text.RegularExpressions;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _input = string.Concat(Enumerable.Repeat("p15", 10_000));
private readonly Regex _regex = new(@"(?>a0|b1|c2|d3|e4|f5|g6|h7|i8|j9|k10|l11|m12|n13|o14|p15)", RegexOptions.Compiled);
[Benchmark]
public int DispatchToFinalBranch() => _regex.Count(_input);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
DispatchToFinalBranch
|
.NET 10.0
|
233.9 μs
|
1.00
|
|
DispatchToFinalBranch
|
.NET 11.0
|
159.5 μs
|
0.68
|
Another of the few differences between compiled and source-generated regexes had to do with backreferences. A case-sensitive backreference, such as the
\1
in
([a-z]+)-\1
, asks whether the next input equals text that was previously captured in the match. Source-generated regexes were using the optimized
SequenceEqual
to do that comparison, whereas
RegexOptions.Compiled
wasn’t. With
dotnet/runtime#123914
in .NET 11, now it does.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Text.RegularExpressions;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _input = new string('a', 256) + "-" + new string('a', 256);
private readonly Regex _regex = new(@"^([a-z]{256})-\1$", RegexOptions.Compiled);
[Benchmark]
public bool Backreference() => _regex.IsMatch(_input);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Backreference
|
.NET 10.0
|
168.4 ns
|
1.00
|
|
Backreference
|
.NET 11.0
|
49.59 ns
|
0.29
|
Searching isn’t limited to
Regex
, of course. Many other methods in .NET help finding things and comparing things, some of which get notable bumps in .NET 11.
The
Ascii
class provides optimized helpers for validating and manipulating ASCII text. Members like
Equals
are already vectorized in .NET 10, but in .NET 11,
dotnet/runtime#123115
improves that implementation by ensuring that inputs of length 8 through 15 can be vectorized, as well.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using BenchmarkDotNet.Attributes;
using System.Text;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Params(8, 15)]
public int Length { get; set; }
private byte[] _bytes = [];
private char[] _charsMatching = [];
[GlobalSetup]
public void Setup()
{
_bytes = new byte[Length];
_charsMatching = new char[Length];
for (int i = 0; i < Length; i++)
{
byte b = (byte)('a' + (i % 26));
_bytes[i] = b;
_charsMatching[i] = (char)b;
}
}
[Benchmark]
public bool Equals_Matching() => Ascii.Equals(_bytes, _charsMatching);
}
|
Method
|
Runtime
|
Length
|
Mean
|
Ratio
|
|
Equals_Matching
|
.NET 10.0
|
8
|
3.834 ns
|
1.00
|
|
Equals_Matching
|
.NET 11.0
|
8
|
1.966 ns
|
0.51
|
|
Equals_Matching
|
.NET 10.0
|
15
|
6.177 ns
|
1.00
|
|
Equals_Matching
|
.NET 11.0
|
15
|
2.398 ns
|
0.39
|
dotnet/runtime#130644
also improves equality performance, in this case with
SequenceEqual
over a
span of
Guid
or
Int128
. Previously,
SequenceEqual
treated these as
arbitrary structures and compared them one element at a time. The PR teaches
the runtime that their fixed bitwise representations are suitable for
comparison as raw bytes. That enables the same optimized memory-comparison
path used for primitive types, including JIT unrolling and vectorization:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Guid[] _guids1 = new Guid[2];
private readonly Guid[] _guids2 = new Guid[2];
private readonly Int128[] _int128s1 = new Int128[2];
private readonly Int128[] _int128s2 = new Int128[2];
[Benchmark]
public bool GuidEqual() => _guids1.AsSpan().SequenceEqual(_guids2);
[Benchmark]
public bool Int128Equal() => _int128s1.AsSpan().SequenceEqual(_int128s2);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
GuidEqual
|
.NET 10.0
|
2.960 ns
|
1.00
|
|
GuidEqual
|
.NET 11.0
|
2.077 ns
|
0.70
|
|
Int128Equal
|
.NET 10.0
|
3.547 ns
|
1.00
|
|
Int128Equal
|
.NET 11.0
|
2.077 ns
|
0.59
|
Another improvement in .NET 11 is to
string.Split
.
Before
string.Split
can produce the resulting strings, it first needs to
find the characters that separate them and record their positions. In .NET 10, that search is
already vectorized: rather than examine one UTF-16 character at a time, it
loads a vector’s worth, compares all of its lanes against the separator in
parallel, and turns the comparison result into a mask identifying any matches.
It then advances to the next vector, or uses the mask to record the matching
positions. In .NET 11, on x86/x64,
dotnet/runtime#125379
from
@hamarb123
makes the no-match path cheaper
for ASCII separators. It loads two vectors of UTF-16 characters, packs their
16-bit elements into one vector of bytes, and checks that combined vector for
the separator. If there isn’t a match, it has skipped twice as much input with
one packed comparison; only a possible match requires the full 16-bit
comparisons needed to determine its exact position. (This same packing technique
is already employed elsewhere, such as in various
SearchValues<T>
implementations.)
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _input = new('a', 16_384);
[Benchmark]
public int SplitNoSeparators() => _input.Split(',').Length;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SplitNoSeparators
|
.NET 10.0
|
786.0 ns
|
1.00
|
|
SplitNoSeparators
|
.NET 11.0
|
404.7 ns
|
0.51
|
A related Arm64 text-search improvement comes from
dotnet/runtime#126678
.
A vector comparison produces a vector whose elements are all zero for
non-matches and all one bits for matches. Finding the first or last match then
requires condensing those bits into a scalar value and counting its leading or
trailing zeros. On x86, the runtime can use a movemask instruction for that
condensing step. Arm64 has no direct equivalent, and the old implementation
needed a sequence of shifts, widening operations, and a horizontal add to achieve it.
The .NET 11 implementation now uses
shrn
, Arm64’s shift-right-and-narrow
instruction, to pack the relevant bits directly.
SearchValues<char>
uses these helpers, so the following benchmark reaches
the affected code while searching for a match at the end of the input.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Buffers;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[DisassemblyDiagnoser(maxDepth: 3)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int Length = 8_192;
private static readonly SearchValues<char> s_vowels = SearchValues.Create("aeiouAEIOU");
private static readonly string s_input = new string('x', Length - 1) + 'e';
[Benchmark]
public int IndexOfAny() => s_input.AsSpan().IndexOfAny(s_vowels);
}
The .NET 10 match-index path requires this sequence:
; Arm64
; .NET 10
cmeq v16.16b, v16.16b, #0
movi v17.16b, #0x80
and v16.16b, v16.16b, v17.16b
ldr q17, [MASK]
ushl v16.16b, v16.16b, v17.16b
uxtl2 v17.8h, v16.16b
shl v17.8h, v17.8h, #8
uaddw v16.8h, v17.8h, v16.8b
addv h16, v16.8h
umov w2, v16.h[0]
mvn w2, w2
rbit w2, w2
clz w2, w2
In .NET 11, the equivalent work is simpler:
; Arm64
; .NET 11
cmeq v16.16b, v16.16b, #0
mvn v16.16b, v16.16b
shrn v16.8b, v16.8h, #4
fmov x2, d16
rbit x2, x2
clz x2, x2
lsr w2, w2, #2
MemoryExtensions
already provides span-based searches for one or more values
with
IndexOfAny
, and for contiguous ranges with
IndexOfAnyInRange
, along
with
Except
,
Contains
, and last-index variants of these operations. For
example,
span.IndexOfAnyInRange('0', '9')
finds the next ASCII digit.
Whitespace is also common to search for, but the characters recognized by
char.IsWhiteSpace
are spread across multiple parts of Unicode rather than
forming one contiguous range. To avoid requiring every caller to construct
the same
SearchValues<char>
,
dotnet/runtime#111439
from
@AlexRadch
adds
ContainsAnyWhiteSpace
,
IndexOfAnyWhiteSpace
,
IndexOfAnyExceptWhiteSpace
,
LastIndexOfAnyWhiteSpace
, and
LastIndexOfAnyExceptWhiteSpace
for
ReadOnlySpan<char>
. Their shared
SearchValues<char>
-based implementation vectorizes these searches for
parsers, validators, trimming code, and other text-processing code.
This is, however, a good example of how vectorization isn’t always a win. Take
trimming. To trim leading whitespace, code needs to find the first character
that isn’t whitespace. That character could be deep into the string, but in
the most common case, there’s little or nothing to trim. A scalar loop can
then return after inspecting just one or two characters, whereas the
vectorized helper has fixed setup cost. It’s still worth vectorizing, because
that overhead is small and the benefits when there is a lot to scan can be
significant. Something to keep in mind.
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly string _input = new(' ', 256);
[Benchmark(Baseline = true)]
public int Scalar()
{
ReadOnlySpan<char> input = _input;
for (int i = 0; i < input.Length; i++)
{
if (!char.IsWhiteSpace(input[i]))
return i;
}
return -1;
}
[Benchmark]
public int Vectorized() => _input.AsSpan().IndexOfAnyExceptWhiteSpace();
}
|
Method
|
Mean
|
Ratio
|
|
Scalar
|
127.87 ns
|
1.00
|
|
Vectorized
|
13.14 ns
|
0.10
|
This method is a particularly good fit when needing to validate that input does not contain any whitespace; that requires searching the entirety of input, which is where the vectorization in these methods shines. As an example of this,
dotnet/runtime#127123
uses it to accelerate the parsing of the
"X"
GUID format:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly string s_noWhitespace =
Guid.Parse("a8098c1a-f86e-11da-bd1a-00112444be1e").ToString("X");
[Benchmark]
public Guid ParseExactX() => Guid.ParseExact(s_noWhitespace, "X");
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ParseExactX
|
.NET 10.0
|
120.6 ns
|
1.00
|
|
ParseExactX
|
.NET 11.0
|
87.10 ns
|
0.72
|
Closely related to searching is sorting. Years ago, sorting methods for
Span<T>
were added to
MemoryExtensions
. Interestingly, the method wasn’t added as
Sort<T>
but rather as
Sort<T, TComparer>
where
TComparer : IComparer<T>
. That signature enables a caller to provide a struct comparer without allocating a delegate or class-based comparer. Because the comparer is a constrained value type, the JIT should also be able to inline the comparison into the hot sorting loop. In practice, the implementation boxed the struct into an
IComparer<T>
, both allocating and turning every comparison back into an interface call. This was known at the time, but avoiding the box used generic implementation techniques that then carried too much runtime and code-size cost. Those supporting costs have since been addressed, so
dotnet/runtime#116109
from
@2A5F
now carries a value-type comparer through
Span<T>.Sort
without boxing it. The JIT can specialize the sorting routine for that comparer and inline the comparison.
The generic specialization does increase generated code and very large comparer structs can be more expensive to copy; this optimization is aimed at the small stateless or lightly stateful structs for which the API was designed.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly int[] _source = Enumerable.Range(0, 512).Select(i => (i * 257) % 512).ToArray();
private int[] _values = [];
[IterationSetup]
public void Setup() => _values = (int[])_source.Clone();
[Benchmark]
public void Sort() => _values.AsSpan().Sort(new DescendingComparer());
private readonly struct DescendingComparer : IComparer<int>
{
public int Compare(int x, int y) => y.CompareTo(x);
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
|
Sort
|
.NET 10.0
|
11.62 μs
|
1.00
|
88 B
|
|
Sort
|
.NET 11.0
|
3.533 μs
|
0.30
|
–
|
Collections and LINQ
Much of the collection and LINQ work in .NET 11 comes from taking better
advantage of information that’s already available. A collection often knows
much more than an
IEnumerable<T>
can express: its count, its contiguous
storage, its comparer, or the layout of its hash table. Similarly, a LINQ
iterator can know how many elements it represents or how its operations were
composed. Preserving that information can avoid enumeration, temporary
storage, repeated hashing, and other work a general-purpose implementation
would otherwise need to perform.
dotnet/runtime#119896
from
@prozolic
changes
ImmutableArray.Create
to use
Array.Copy
rather than a hand-written element loop. A general element-by-element copy repeatedly performs indexing and assignment, while the runtime can specialize
Array.Copy
for the element type and size. For blittable data, it can use optimized bulk memory copies, and for reference types, which need GC write barriers, it performs the required write barriers in the runtime’s tuned copy helpers. The change therefore both simplifies the managed code and gives
ImmutableArray
access to those optimized implementations.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Collections.Immutable;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private readonly int[] _source = Enumerable.Range(0, 1_000).ToArray();
[Benchmark]
public ImmutableArray<int> CreateSlice() => ImmutableArray.Create(_source, 0, _source.Length);
}
This in particular makes larger copies much faster.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
CreateSlice
|
.NET 10.0
|
552.5 ns
|
1.00
|
|
CreateSlice
|
.NET 11.0
|
277.7 ns
|
0.50
|
dotnet/runtime#118932
from
@prozolic
similarly keeps
ImmutableArrayExtensions.SequenceEqual
on optimized paths when the other sequence is an array, list, or another
ICollection<T>
.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Collections.Immutable;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private ImmutableArray<int> _immutable;
private List<int> _list = [];
[GlobalSetup]
public void Setup()
{
int[] values = Enumerable.Range(0, 1_000).ToArray();
_immutable = ImmutableArray.Create(values);
_list = [.. values];
}
[Benchmark]
public bool SequenceEqual() => _immutable.SequenceEqual(_list);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SequenceEqual
|
.NET 10.0
|
925.8 ns
|
1.00
|
|
SequenceEqual
|
.NET 11.0
|
122.2 ns
|
0.13
|
Array.FindAll
has the opposite job: it produces a new collection. For a small result, its temporary storage used to cost more than the result itself.
dotnet/runtime#120336
from
@Henr1k80
has
Array.FindAll
collect its first four matches in an inline stack buffer rather than an intermediate
List<T>
:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private int[] _data = [];
[Params(4, 5)]
public int Size { get; set; }
[GlobalSetup]
public void Setup() => _data = Enumerable.Range(0, Size).ToArray();
[Benchmark]
public int[] FindAllMatch() => Array.FindAll(_data, static _ => true);
}
|
Method
|
Runtime
|
Size
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
FindAllMatch
|
.NET 10.0
|
4
|
27.61 ns
|
1.00
|
112 B
|
1.00
|
|
FindAllMatch
|
.NET 11.0
|
4
|
9.212 ns
|
0.33
|
40 B
|
0.36
|
|
FindAllMatch
|
.NET 10.0
|
5
|
36.93 ns
|
1.00
|
176 B
|
1.00
|
|
FindAllMatch
|
.NET 11.0
|
5
|
11.102 ns
|
0.30
|
48 B
|
0.27
|
Dictionary<TKey, TValue>.Remove
had also missed an optimization already used by lookup and insertion.
dotnet/runtime#125884
gives value-type keys a streamlined loop for the common default-comparer case. Because that path doesn’t need a virtual comparer call, the JIT can keep more of the operation’s state in registers; reference-type keys and custom comparers continue to use the general path.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly Guid[] _keys = Enumerable.Range(0, 512).Select(i => new Guid(i, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)).ToArray();
private Dictionary<Guid, int> _dictionary = [];
[IterationSetup]
public void Setup() => _dictionary = _keys.ToDictionary(key => key, key => key.GetHashCode());
[Benchmark(OperationsPerInvoke = 512)]
public void Remove()
{
foreach (Guid key in _keys)
_dictionary.Remove(key);
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Remove
|
.NET 10.0
|
5.285 ns
|
1.00
|
|
Remove
|
.NET 11.0
|
4.321 ns
|
0.82
|
dotnet/runtime#125893
changes
HashSet<T>
‘s internal chain walks to test the entry index against the array length with an unsigned comparison. That proves the subsequent array access is in range, allowing the JIT to remove its bounds check.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly HashSet<int> _set = Enumerable.Range(0, 4096).ToHashSet();
private readonly int[] _probes = Enumerable.Range(0, 4096).ToArray();
[Benchmark]
public int ContainsHits()
{
int count = 0;
foreach (int value in _probes)
count += _set.Contains(value) ? 1 : 0;
return count;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ContainsHits
|
.NET 10.0
|
7.870 μs
|
1.00
|
|
ContainsHits
|
.NET 11.0
|
7.388 μs
|
0.94
|
dotnet/runtime#128988
from
@prozolic
removes a second hash-table lookup when removing a matching key-value pair from
OrderedDictionary<TKey, TValue>
through
ICollection<KeyValuePair<TKey, TValue>>
. That interface operation must first find the key and verify that its stored value equals the supplied value. Once both checks have succeeded, the implementation already has the entry index needed for removal. Looking up the key again unnecessarily repeats its hash computation and collision-chain walk, so the updated path removes the known entry directly.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Collections.Generic;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private const int N = 10_000;
private OrderedDictionary<string, int> _dict = [];
private KeyValuePair<string, int>[] _pairs = Enumerable.Range(0, N)
.Select(i => new KeyValuePair<string, int>($"key{i}", i))
.ToArray();
[IterationSetup]
public void IterationSetup() => _dict = new OrderedDictionary<string, int>(_pairs);
[Benchmark]
public int Remove_ExplicitInterface()
{
ICollection<KeyValuePair<string, int>> col = _dict;
int removed = 0;
foreach (var pair in _pairs)
if (col.Remove(pair))
removed++;
return removed;
}
}
For 10,000 entries:
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Remove_ExplicitInterface
|
.NET 10.0
|
220.7 ms
|
1.00
|
|
Remove_ExplicitInterface
|
.NET 11.0
|
179.0 ms
|
0.81
|
dotnet/runtime#122952
goes further when two hash tables have compatible layouts. Normally,
UnionWith
enumerates the source and inserts every element independently, recomputing hashes, checking for duplicates, and potentially resizing the destination along the way. If the destination is empty and both sets use compatible comparers, every source entry is already unique under exactly the equality rules the destination needs.
UnionWith
can therefore use the existing
HashSet<T>
copy-constructor fast path to clone the populated storage rather than rebuilding the same table entry by entry.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Collections.Generic;
using System.Linq;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private readonly HashSet<int> _source = new(Enumerable.Range(0, 4_096));
[Benchmark]
public HashSet<int> FreshDestinationUnionWith()
{
HashSet<int> destination = [];
destination.UnionWith(_source);
return destination;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
FreshDestinationUnionWith
|
.NET 10.0
|
46.207 μs
|
1.00
|
252.27 KB
|
1.00
|
|
FreshDestinationUnionWith
|
.NET 11.0
|
2.433 μs
|
0.05
|
76.07 KB
|
0.30
|
dotnet/runtime#128300
from
@AndrewP-GH
also helps with collection construction. Building a
FrozenDictionary<TKey, TValue>
first requires collecting the input elements into a regular
Dictionary<TKey, TValue>
if they’re not already in one. That temporary dictionary resolves duplicate keys before the final frozen representation is chosen, but in .NET 10 it was growing incrementally even when the source’s count was readily available. This PR uses that count as the
dictionary’s initial capacity, avoiding repeated allocation, copying, and
rehashing as it’s populated.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System.Collections.Concurrent;
using System.Collections.Frozen;
using System.Collections.Generic;
using System.Collections.Immutable;
using System.Linq;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly KeyValuePair<int, int>[] _array =
Enumerable.Range(0, 4096).Select(i => new KeyValuePair<int, int>(i, i)).ToArray();
[Benchmark]
public FrozenDictionary<int, int> FromArray() => _array.ToFrozenDictionary();
}
|
Method
|
Runtime
|
Allocated
|
Alloc Ratio
|
|
FromArray
|
.NET 10.0
|
347.17 KB
|
1.00
|
|
FromArray
|
.NET 11.0
|
127.16 KB
|
0.37
|
SetEquals
asks whether two sets contain the same values, regardless of insertion order. The general implementation needs a temporary mutable set so it can account for duplicates and arbitrary enumeration order. When the other input is already a hash set with a compatible comparer, though, that reconstruction is unnecessary.
dotnet/runtime#126309
from
@aw0lid
adds to
ImmutableHashSet<T>.SetEquals
direct zero-allocation paths for compatible
ImmutableHashSet<T>
and
HashSet<T>
inputs; with an identical comparer, the sets can be considered equal if they have the same count and if every element from one is found in the other.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Collections.Immutable;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private ImmutableHashSet<int> _set = ImmutableHashSet<int>.Empty;
private ImmutableHashSet<int> _immutable = ImmutableHashSet<int>.Empty;
private HashSet<int> _mutable = [];
[GlobalSetup]
public void Setup()
{
int[] items = Enumerable.Range(0, 10_000).ToArray();
_set = ImmutableHashSet.CreateRange(items);
_immutable = ImmutableHashSet.CreateRange(items);
_mutable = new(items);
}
[Benchmark]
public bool EqualImmutableHashSet() => _set.SetEquals(_immutable);
[Benchmark]
public bool EqualHashSet() => _set.SetEquals(_mutable);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
EqualImmutableHashSet
|
.NET 10.0
|
775.6 μs
|
1.00
|
158.16 KB
|
1.00
|
|
EqualImmutableHashSet
|
.NET 11.0
|
559.7 μs
|
0.72
|
–
|
0
|
|
EqualHashSet
|
.NET 10.0
|
478.6 μs
|
1.00
|
157.99 KB
|
1.00
|
|
EqualHashSet
|
.NET 11.0
|
230.9 μs
|
0.48
|
–
|
0
|
Sorted sets have a related case.
SetEquals
can be passed any
IEnumerable<T>
. That sequence might be unordered and might contain duplicate values, so
ImmutableSortedSet<T>
previously copied it into a temporary
SortedSet<T>
before performing the comparison. However, when the input is another sorted set using the same ordering comparer, both sets contain unique values and enumerate those values
in the same order. Equality can then be determined by first comparing their
counts and, if those match, advancing both enumerators together. The first
unequal pair proves the sets are different, and reaching the end without finding
a difference proves they’re equal.
dotnet/runtime#126549
from
@aw0lid
recognizes this case for
ImmutableSortedSet<T>
, avoiding the temporary
SortedSet<T>
and comparing the two sorted sequences directly in one linear pass:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Collections.Generic;
using System.Collections.Immutable;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private const int N = 10_000;
private ImmutableSortedSet<int> _set = ImmutableSortedSet<int>.Empty;
private ImmutableSortedSet<int> _equalSet = ImmutableSortedSet<int>.Empty;
[GlobalSetup]
public void Setup()
{
var items = new int[N];
for (int i = 0; i < N; i++) items[i] = i;
_set = ImmutableSortedSet.CreateRange(items);
_equalSet = ImmutableSortedSet.CreateRange(items);
}
[Benchmark]
public bool SetEquals_EqualImmutableSortedSet() => _set.SetEquals(_equalSet);
}
For 10,000 elements:
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
SetEquals_EqualImmutableSortedSet
|
.NET 10.0
|
767.7 μs
|
1.00
|
430.02 KB
|
1.00
|
|
SetEquals_EqualImmutableSortedSet
|
.NET 11.0
|
117.6 μs
|
0.15
|
–
|
0
|
SortedSet<T>
already enjoyed an optimization for that case in .NET 10, but it’s not left out of .NET 11 improvements.
SortedSet<T>.GetViewBetween
returns a
SortedSet<T>
view, effectively a slice of another
SortedSet<T>
, a live window onto a range of another set: changes through the view affect the original set. Clearing a view therefore can’t replace the view with an empty collection; it must find and remove every original node in that range.
dotnet/runtime#126410
from
@prozolic
reduces the temporary storage used for that operation. The implementation pre-sizes the list of elements to remove and walks it by index rather than repeatedly removing from and shrinking the temporary list.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private const int N = 10_000;
private SortedSet<int> _fullSet = [];
[IterationSetup]
public void Setup() => _fullSet = new SortedSet<int>(Enumerable.Range(0, N));
[Benchmark]
public int GetViewBetweenThenClear()
{
SortedSet<int> view = _fullSet.GetViewBetween(0, N - 1);
view.Clear();
return _fullSet.Count;
}
}
|
Method
|
Runtime
|
Allocated
|
Alloc Ratio
|
|
GetViewBetweenThenClear
|
.NET 10.0
|
193.15 KB
|
1.00
|
|
GetViewBetweenThenClear
|
.NET 11.0
|
103.93 KB
|
0.54
|
Collections are frequently consumed through LINQ. Although its operators work
in terms of the general
IEnumerable<T>
abstraction, LINQ’s internal
iterators can preserve useful facts about their sources and the operations
already applied. Those facts can sometimes answer a query without enumerating
the source at all.
For example, consider
source.Append(x).Skip(10).LastOrDefault()
. LINQ queries are lazy, so the actual search begins only when
LastOrDefault
asks the
Skip
iterator for its last element. If
source.Append(x)
contains ten or fewer elements,
Skip(10)
necessarily removes all of them, leaving an empty sequence from
which
LastOrDefault
must return the default value.
Append
,
Prepend
, and
Concat
iterators can cheaply report their total count when their underlying
sources can do so.
dotnet/runtime#123306
from
@prozolic
teaches the last-element path for
Skip
to compare that count with the number being skipped and immediately
report that there is no element, rather than searching a sequence it already
knows is empty.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Linq;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private readonly int[] _source = [1, 2, 3, 4, 5];
[Benchmark]
public int AppendSkipLastOrDefault() => _source.Append(6).Skip(10).LastOrDefault();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
AppendSkipLastOrDefault
|
.NET 10.0
|
44.89 ns
|
1.00
|
144 B
|
1.00
|
|
AppendSkipLastOrDefault
|
.NET 11.0
|
16.32 ns
|
0.36
|
112 B
|
0.78
|
.NET 11 also improve’s LINQ’s
Enumerable.Sum
.
Sum
already uses SIMD. The
main loop processes four vectors at a time, alternating between two
accumulators so that the additions don’t require extra moves. However,
Sum
also promises to throw if the result overflows. Alongside each vector addition,
the implementation uses the signs of the two inputs and the result to update
another vector that tracks whether any lane overflowed. After every
group of four vectors, the loop tests that tracking vector and branches to the
throwing path if needed. Overflow is rare, though, so on the common path that test and branch almost always just
confirm that nothing happened.
dotnet/runtime#127429
removes that repeated work in .NET 11. It accumulates the overflow information
across all of the vector processing and tests it once after the vector loops
have completed. The checked-overflow behavior remains the same, but the normal
path no longer needs to stop and check after every four vectors. The PR also
simplifies how the method walks the input, replacing unsafe reference and index
arithmetic with span-based vector loads, progressively slicing off the elements
already processed, and using a
foreach
for the final scalar elements.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Linq;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private const int N = 32;
private int[] _intData = [];
[GlobalSetup]
public void Setup()
{
Random rng = new(42);
_intData = Enumerable.Range(0, N).Select(_ => rng.Next(-1_000, 1_000)).ToArray();
}
[Benchmark]
public int SumInt() => _intData.Sum();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SumInt
|
.NET 10.0
|
5.609 ns
|
1.00
|
|
SumInt
|
.NET 11.0
|
4.731 ns
|
0.84
|
Enumerable
‘s
Min
and
Max
already examined many values at once with SIMD, but they still finished
byte
,
sbyte
,
short
, and
ushort
inputs by copying the final vector to the stack and checking its values one by one.
dotnet/runtime#127995
keeps that final step in vector instructions, using shuffles to combine the lanes. Smaller element types pack more values into each vector, so they benefit most from no longer finishing the search one value at a time.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private byte[] _bytes = [];
[Params(16, 64)]
public int Length { get; set; }
[GlobalSetup]
public void Setup() => _bytes = Enumerable.Range(0, Length).Select(i => (byte)i).ToArray();
[Benchmark]
public byte MaxByte() => _bytes.Max();
}
|
Method
|
Runtime
|
Length
|
Mean
|
Ratio
|
|
MaxByte
|
.NET 10.0
|
16
|
7.546 ns
|
1.00
|
|
MaxByte
|
.NET 11.0
|
16
|
2.176 ns
|
0.29
|
|
MaxByte
|
.NET 10.0
|
64
|
7.827 ns
|
1.00
|
|
MaxByte
|
.NET 11.0
|
64
|
2.059 ns
|
0.26
|
Since its inception, LINQ has had
Join
and
GroupJoin
, and .NET 10
introduced the long-requested
LeftJoin
and
RightJoin
. In .NET 11,
dotnet/runtime#127236
adds
FullJoin
. The operators differ
in which unmatched elements they retain and how they represent the matches:
-
Join
emits only pairs whose keys match.
-
GroupJoin
emits every left element together with a sequence containing its
matching right elements; that sequence is empty when there are no matches.
-
LeftJoin
emits the matching pairs and also unmatched left elements, paired
with a default value for the right.
-
RightJoin
does the inverse, emitting the matching pairs and also unmatched right elements, paired with a default value for the left.
-
FullJoin
emits the matching pairs and the unmatched elements from both
inputs, using a default value for whichever side is missing.
Before .NET 11, applications typically approximated it by combining
GroupJoin
,
SelectMany
, and
Concat
, then searching the first input again
to find right-side elements without a match. The built-in operator avoids both
that composition of iterators and the repeated search.
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Running;
using System.Collections.Generic;
using System.Linq;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private const int N = 10_000;
private List<(int Id, string Name)> _left = Enumerable.Range(0, N).Select(i => (i, $"item{i}")).ToList();
private List<(int Id, decimal Amount)> _right = Enumerable.Range(N / 4, N).Select(i => (i, (decimal)i * 1.5m)).ToList();
[Benchmark(Baseline = true)]
public int FullJoin_Manual() =>
_left.GroupJoin(_right, l => l.Id, r => r.Id, (l, rs) => (l, rs))
.SelectMany(x => x.rs.DefaultIfEmpty(), (x, r) => (x.l, r))
.Concat(_right
.Where(r => !_left.Any(l => l.Id == r.Id))
.Select(r => (l: default((int Id, string Name)), r)))
.Count();
[Benchmark]
public int FullJoin_New() => _left.FullJoin(_right, l => l.Id, r => r.Id).Count();
}
For 10,000 elements in each input:
|
Method
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
FullJoin_Manual
|
27.615 ms
|
1.00
|
3.23 MB
|
1.00
|
|
FullJoin_New
|
1.702 ms
|
0.06
|
1.56 MB
|
0.48
|
The earlier
Skip
example showed how many LINQ optimizations come from one operator flowing information to subsequent operators that can then be used for additional optimization. This is typically done by adding that additional information to properties on the concrete internal
IEnumerable<T>
implementations used by
System.Linq
. Synchronous
Enumerable
has accumulated many such specialized iterators over many releases, focusing in particular on places where algorithmic complexity could be significantly reduced.
AsyncEnumerable
, introduced “in the box” in .NET 10, initially had much less of that machinery; for asynchronous sequences dominated by I/O, it often wouldn’t matter.
Concatenation is an important exception. Prior to .NET 11, every call to
AsyncEnumerable.Append
created a new iterator around the sequence produced
by the previous call. Consider a chain with just three appended values:
var sequence = AsyncEnumerable.Empty<int>()
.Append(0)
.Append(1)
.Append(2);
To produce
0
, enumeration needs to pass through all three nested iterators.
Producing
1
passes through two, and producing
2
passes through one. Thus,
yielding three values involves roughly
3 + 2 + 1
iterator steps. With 1,000
appends, that grows to
1,000 + 999 + ... + 1
, or approximately 500,000
steps, rather than approximately 1,000. In general, enumerating N values
requires O(N^2) work. Several years back
Enumerable
addressed this by special-casing the various concatenation enumerables to flow enough information through to make iterating the chain O(N) rather than O(N^2), and in .NET 11,
dotnet/runtime#122389
applies that to
AsyncEnumerable
as well. The operators accumulate the extra elements or sequences in one flat representation instead of adding another wrapper for each LINQ operator.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Linq;
using System.Threading.Tasks;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
[Benchmark]
public async Task<int> AppendChain()
{
var seq = AsyncEnumerable.Empty<int>();
for (int i = 0; i < 1_000; i++) seq = seq.Append(i);
return await seq.SumAsync();
}
}
For a chain of 1,000 appended elements:
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
AppendChain
|
.NET 10.0
|
8.253 ms
|
1.00
|
187.57 KB
|
1.00
|
|
AppendChain
|
.NET 11.0
|
28.49 μs
|
0.00345
|
136.77 KB
|
0.73
|
I/O
I/O performance is often equated with the speed of the underlying device, but
the transfer itself is only one part of an operation. A cached file read may
complete in microseconds, many redirected pipes may be active concurrently,
and compression may operate entirely on data already in memory. In cases like
these, the managed overhead around the operation can be as important as the
time spent moving the data.
That overhead includes setting up the appropriate synchronous or asynchronous
OS mechanism, keeping state alive until an operation completes,
allocating and copying temporary buffers, and adapting between the caller’s
data and stream-based APIs. .NET 11 removes work from each of these layers.
On Windows, “overlapped I/O” is the asynchronous model in which an operation begins now and the operating system posts its completion later. Any time .NET performs I/O as part of an asynchronous operation on Windows, it strives to use a corresponding overlapped I/O API rather than using a synchronous API asynchronously (i.e. queuing a work item that blocks a thread pool thread doing the I/O). However, there have been some stragglers. Redirected child-process output previously used synchronous pipe handles, so
ReadToEndAsync
on the stream from a
Process
‘s stdout or stderr
Stream
still needed a thread-pool thread blocked in a native read for each stdout or stderr pipe. In .NET 11,
dotnet/runtime#125643
instead opens the parent’s stdout and stderr ends for overlapped reads, while leaving the child ends synchronous (as console applications expect).
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Diagnostics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
using BenchmarkDotNet.Running;
if (args is ["--emit"])
{
Console.Write(new string('x', 8 * 1024 * 1024));
return;
}
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[SimpleJob(launchCount: 1, warmupCount: 3, iterationCount: 10)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
[Benchmark]
public Task ReadOutputConcurrently() =>
Task.WhenAll(Enumerable.Range(0, 16).Select(_ => RunProcess()));
private static async Task RunProcess()
{
var psi = new ProcessStartInfo("dotnet")
{
RedirectStandardOutput = true,
UseShellExecute = false,
};
psi.ArgumentList.Add(typeof(Benchmarks).Assembly.Location);
psi.ArgumentList.Add("--emit");
using Process process = Process.Start(psi)!;
_ = await process.StandardOutput.ReadToEndAsync();
await process.WaitForExitAsync();
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ReadOutputConcurrently
|
.NET 10.0
|
587.8 ms
|
1.00
|
|
ReadOutputConcurrently
|
.NET 11.0
|
541.8 ms
|
0.92
|
We often refer to the mechanism being fixed as “async over sync.” The opposite
case, “sync over async,” can be even worse, as it means blocking one thread
while waiting for another to do some work; that provides one of the necessary
ingredients for cycles and deadlocks, and is a leading cause of scalability
bottlenecks in services, so we try to stamp out “sync over async” whenever
possible. In cases where we can’t avoid it, though, we can at least make it
better.
RandomAccess.Read
provides one such opportunity when it’s used with a
Windows file handle opened for asynchronous I/O. Windows requires specifying at the time of file opening whether I/O will be overlapped or not, and if it is, Windows still requires a read to use its
OVERLAPPED
mechanism, even in a synchronous
Read
case where the API’s caller is going to block until that read completes. While we can’t avoid that overlapped I/O, we can still make the operation cheaper. Previously, .NET both gave the operation an event for the calling thread to wait on and registered an I/O-completion callback. Instead,
dotnet/runtime#126845
uses a
documented Windows convention: setting the low bit of
OVERLAPPED.hEvent
instructs Windows to signal the event when the operation completes but not to
also queue a completion packet to the I/O completion port. The calling thread
can wait on an event cached by the file handle, retrieve the result, and
perform the cleanup itself. This removes the callback, its coordination, and
the per-operation allocation while still performing the same synchronous
wait.
// Windows:
// dotnet run -c Release -f net10.0 --filter "*RandomAccessBenchmarks*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using Microsoft.Win32.SafeHandles;
BenchmarkSwitcher.FromAssembly(typeof(RandomAccessBenchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class RandomAccessBenchmarks
{
private string _path = "";
private SafeFileHandle _handle = null!;
private readonly byte[] _buffer = new byte[4_096];
[GlobalSetup]
public void Setup()
{
_path = Path.Combine(Path.GetTempPath(), $"net11-random-access-{Guid.NewGuid():N}.tmp");
File.WriteAllBytes(_path, new byte[1024 * 1024]);
_handle = File.OpenHandle(_path, FileMode.Open, FileAccess.Read, FileShare.Read, FileOptions.Asynchronous | FileOptions.RandomAccess);
}
[GlobalCleanup]
public void Cleanup()
{
_handle.Dispose();
File.Delete(_path);
}
[Benchmark]
public int Read4K() => RandomAccess.Read(_handle, _buffer, fileOffset: 0);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Read4K
|
.NET 10.0
|
4.564 μs
|
1.00
|
176 B
|
1.00
|
|
Read4K
|
.NET 11.0
|
2.747 μs
|
0.60
|
–
|
0
|
There are smaller allocation wins at higher layers as well. For example,
dotnet/runtime#121508
makes assigning
TextWriter.NewLine
to its existing value a no-op and shares arrays for the standard
"\n"
and
"\r\n"
values, avoiding a fresh
char[]
conversion.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly StringWriter _writer = new();
[Benchmark]
public void SetSameValue() => _writer.NewLine = Environment.NewLine;
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
|
SetSameValue
|
.NET 10.0
|
8.281 ns
|
1.00
|
32 B
|
|
SetSameValue
|
.NET 11.0
|
2.168 ns
|
0.26
|
–
|
Archive and file APIs remove similar temporary allocations. A GNU tar header
has fixed-size fields for an entry’s name and link target. When either doesn’t
fit,
TarWriter
emits an additional metadata record containing the long
value. In .NET 10,
TarWriter
first encoded that value into a newly allocated
byte array, then wrote the bytes and a null terminator into a new
MemoryStream
. Because the stream didn’t know the final size, it allocated
and grew its own backing array as the data was written. With
dotnet/runtime#123835
, .NET 11
instead computes the exact UTF-8 size including the terminator, allocates one
array of that size, encodes directly into it, and constructs the
MemoryStream
over that array. This removes both the temporary encoded array
and the stream’s growth and copying.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Formats.Tar;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly MemoryStream _destination = new();
private readonly GnuTarEntry _entry = new(TarEntryType.RegularFile, new string('a', 256));
[Benchmark]
public long WriteLongName()
{
_destination.SetLength(0);
using TarWriter writer = new(_destination, TarEntryFormat.Gnu, leaveOpen: true);
writer.WriteEntry(_entry);
return _destination.Length;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
WriteLongName
|
.NET 10.0
|
731.1 ns
|
1.00
|
1.36 KB
|
1.00
|
|
WriteLongName
|
.NET 11.0
|
616.7 ns
|
0.84
|
608 B
|
0.44
|
ZipArchive
similarly eliminates temporary buffers. ZIP archives end with a
central directory describing their entries. Reading that directory allocated
a new 4 KB buffer for every
ZipArchive
, along with additional arrays in a
few paths that needed to combine or slice data. With
dotnet/runtime#123836
, .NET 11
now rents the central-directory buffer from
ArrayPool<byte>
and uses spans
and memory in place of the additional arrays and several open-coded loops.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.IO.Compression;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private byte[] _archive = [];
[GlobalSetup]
public void Setup()
{
using MemoryStream destination = new();
using (ZipArchive archive = new(destination, ZipArchiveMode.Create, leaveOpen: true))
{
ZipArchiveEntry entry = archive.CreateEntry("entry.txt");
using Stream stream = entry.Open();
stream.WriteByte(42);
}
_archive = destination.ToArray();
}
[Benchmark]
public int ReadCentralDirectory()
{
using MemoryStream source = new(_archive, writable: false);
using ZipArchive archive = new(source, ZipArchiveMode.Read);
return archive.Entries.Count;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
ReadCentralDirectory
|
.NET 10.0
|
553.5 ns
|
1.00
|
5.05 KB
|
1.00
|
|
ReadCentralDirectory
|
.NET 11.0
|
258.1 ns
|
0.47
|
1.13 KB
|
0.22
|
As a final example,
FileInfo.MoveTo
performs a source-directory existence check before moving the file. It had been constructing a
DirectoryInfo
solely to read its
Exists
property, which is wasteful when
Directory.Exists
exists and can do it without the allocation.
dotnet/runtime#123893
in .NET 11 switches to use that.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private string _directory = "";
private string _firstPath = "";
private string _secondPath = "";
private FileInfo _file = null!;
private bool _atFirstPath;
[GlobalSetup]
public void Setup()
{
_directory = Path.Combine(Path.GetTempPath(), $"net11-file-move-{Guid.NewGuid():N}");
Directory.CreateDirectory(_directory);
_firstPath = Path.Combine(_directory, "first.tmp");
_secondPath = Path.Combine(_directory, "second.tmp");
File.WriteAllBytes(_firstPath, [42]);
_file = new(_firstPath);
_atFirstPath = true;
}
[GlobalCleanup]
public void Cleanup() => Directory.Delete(_directory, recursive: true);
[Benchmark]
public string MoveTo()
{
_file.MoveTo(_atFirstPath ? _secondPath : _firstPath, overwrite: true);
_atFirstPath = !_atFirstPath;
return _file.FullName;
}
}
|
Method
|
Runtime
|
Allocated
|
Alloc Ratio
|
|
MoveTo
|
.NET 10.0
|
332 B
|
1.00
|
|
MoveTo
|
.NET 11.0
|
236 B
|
0.71
|
.NET provides great high-level abstractions for working with all manner of
data and I/O. One of the most prominent is
Stream
, which provides a simple,
flexible mechanism for reading and writing many different data sources and
formats:
MemoryStream
,
FileStream
,
CryptoStream
,
ZLibStream
,
SslStream
, and on and on. For folks that really care about maximizing
performance, however, sometimes you want to go a bit lower-level and deal
directly with the underlying primitives. For example, the various compression
streams,
ZLibStream
,
DeflateStream
,
GZipStream
, and
BrotliStream
, all
maintain buffers that hold input and output data waiting to be read or written.
But what if the caller already owns its input and output buffers, or wants to
use a pool for them? In .NET 11,
dotnet/runtime#123145
exposes
the underlying
DeflateEncoder
/
DeflateDecoder
,
ZLibEncoder
/
ZLibDecoder
, and
GZipEncoder
/
GZipDecoder
types, following
the existing
BrotliEncoder
and
BrotliDecoder
pattern. The stream types are wrappers around these encoders and decoders, and in
.NET 11 you can now use them directly. They support chunked
Compress
,
Decompress
, and
Flush
operations as well as one-shot
TryCompress
and
TryDecompress
, enabling callers to supply and reuse their own buffers rather
than going through adapter streams and their buffers.
Networking
Networking is the bread-and-butter of many applications and sits directly on the hot path of scalable services. Improvements throughout the stack add up quickly.
At the bottom of the stack, connections and sockets establish and carry the
byte stream. A socket doesn’t actually connect to a host name; it connects to
an IP address and port. Resolving a host name may produce multiple candidate
addresses, including one or more IPv4 addresses from DNS A records and one or
more IPv6 addresses from AAAA records. When
SocketAsyncEventArgs.RemoteEndPoint
is a
DnsEndPoint
, the existing
Socket.ConnectAsync
implementation performs that resolution and tries the resulting addresses in sequence. It starts a connection to the first address, and only if that attempt fails does it move on to the next. This works well when the first address is reachable. A failed TCP connection isn’t always reported quickly, however. If packets sent over that route are simply dropped, the attempt may remain pending until a timeout even though another address for the same host could have connected immediately.
This problem is especially visible on machines with both IPv4 and IPv6.
Clients generally want to prefer IPv6 when it works, but a broken or
misconfigured IPv6 path can make an application wait through a long
timeout before trying IPv4. The technique commonly known as
Happy Eyeballs
addresses this by
overlapping connection attempts. Rather than putting all the latency of one
candidate in front of the next, it starts another attempt after a short delay
and uses the first connection that succeeds. The remaining attempts are then
canceled or discarded. That consumes some additional resources, but it can
greatly reduce the long tail of connection establishment.
In .NET 11,
dotnet/runtime#106374
adds an opt-in, Happy-Eyeballs-like strategy to the static
Socket.ConnectAsync
overload that accepts a
SocketAsyncEventArgs
. The new overload accepts
a
ConnectAlgorithm
, where
ConnectAlgorithm.Default
preserves the existing
sequential behavior, while
ConnectAlgorithm.Parallel
requests the new
strategy. When parallel connection is requested for an address-family-unspecified
DnsEndPoint
on a machine that supports both IPv4 and IPv6, .NET starts
separate IPv4 and IPv6 DNS queries and runs a connection loop for each family
concurrently. Addresses within each family are still tried sequentially, but
the two families no longer wait on each other. The first successful connection
becomes the
ConnectSocket
, and a connection subsequently established by the
other family is disposed. If one family fails, the other is allowed to
continue; the operation reports failure only after neither can connect.
Parallel mode can briefly establish two connections, while the default remains
cheaper when the first candidate connects promptly.
Given the nature of the change, it’s a little hard to create a real benchmark
for this, but we can get creative. Here I’ve created IPv4
and IPv6 listeners on the same port, but arranged the benchmark to only accept
from the IPv4 listener. On my machine,
localhost
resolves to
::1
before
127.0.0.1
, so the client sockets by default would first try the IPv6 address
and only when it fails try the IPv4 one. The benchmark setup fills the IPv6
listener’s accept backlog, such that additional client connect requests will
stall.
// Windows
// dotnet run -c Release -f net11.0 --filter "*"
using System.Net;
using System.Net.Sockets;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Engines;
using BenchmarkDotNet.Running;
BenchmarkRunner.Run<Benchmarks>();
[SimpleJob(RunStrategy.Throughput, launchCount: 1, warmupCount: 2, iterationCount: 8, invocationCount: 1)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private Socket _ipv6Listener = null!;
private Socket _ipv4Listener = null!;
private List<Socket> _backlogClients = [];
private CancellationTokenSource _cancellation = null!;
private Task _ipv4AcceptLoop = null!;
private Task? _releaseOne;
private int _port;
[IterationSetup(Target = nameof(Default))]
public void SetupDefault() => Setup(releaseIPv6: true);
[IterationSetup(Target = nameof(Parallel))]
public void SetupParallel() => Setup(releaseIPv6: false);
[IterationCleanup]
public void Cleanup()
{
_releaseOne?.GetAwaiter().GetResult();
_cancellation.Cancel();
_ipv4Listener.Dispose();
_ipv6Listener.Dispose();
try
{
_ipv4AcceptLoop.GetAwaiter().GetResult();
}
catch { }
foreach (Socket socket in _backlogClients)
{
socket.Dispose();
}
_cancellation.Dispose();
}
[Benchmark(Baseline = true)]
public async Task Default()
{
using Socket socket = await ConnectAsync(ConnectAlgorithm.Default);
}
[Benchmark]
public async Task Parallel()
{
using Socket socket = await ConnectAsync(ConnectAlgorithm.Parallel);
}
private void Setup(bool releaseIPv6)
{
if (Dns.GetHostAddresses("localhost")[0].AddressFamily != AddressFamily.InterNetworkV6)
{
throw new InvalidOperationException("This benchmark requires localhost to prefer IPv6.");
}
_ipv6Listener = new(AddressFamily.InterNetworkV6, SocketType.Stream, ProtocolType.Tcp)
{
DualMode = false,
};
_ipv6Listener.Bind(new IPEndPoint(IPAddress.IPv6Loopback, 0));
_port = ((IPEndPoint)_ipv6Listener.LocalEndPoint!).Port;
_ipv6Listener.Listen(1);
_ipv4Listener = new(AddressFamily.InterNetwork, SocketType.Stream, ProtocolType.Tcp);
_ipv4Listener.Bind(new IPEndPoint(IPAddress.Loopback, _port));
_ipv4Listener.Listen(128);
_cancellation = new();
_ipv4AcceptLoop = AcceptLoopAsync(_ipv4Listener, _cancellation.Token);
_backlogClients = [];
bool stalled = false;
for (int i = 0; i < 128; i++)
{
Socket socket = new(AddressFamily.InterNetworkV6, SocketType.Stream, ProtocolType.Tcp);
Task connect = socket.ConnectAsync(new IPEndPoint(IPAddress.IPv6Loopback, _port));
if (!connect.Wait(TimeSpan.FromMilliseconds(100)))
{
socket.Dispose();
stalled = true;
break;
}
connect.GetAwaiter().GetResult();
_backlogClients.Add(socket);
}
if (!stalled)
{
throw new InvalidOperationException("Unable to saturate the IPv6 accept backlog.");
}
_releaseOne = releaseIPv6 ?
Task.Run(async () =>
{
await Task.Delay(100);
using Socket socket = await _ipv6Listener.AcceptAsync();
}) :
null;
}
private Task<Socket> ConnectAsync(ConnectAlgorithm algorithm)
{
TaskCompletionSource<Socket> completion = new(TaskCreationOptions.RunContinuationsAsynchronously);
var args = new SocketAsyncEventArgs
{
RemoteEndPoint = new DnsEndPoint("localhost", _port),
};
args.Completed += Complete;
if (!Socket.ConnectAsync(SocketType.Stream, ProtocolType.Tcp, args, algorithm))
{
Complete(null, args);
}
return completion.Task;
void Complete(object? sender, SocketAsyncEventArgs e)
{
e.Completed -= Complete;
if (e.SocketError == SocketError.Success)
{
completion.SetResult(e.ConnectSocket!);
}
else
{
completion.SetException(new SocketException((int)e.SocketError));
}
e.Dispose();
}
}
private static async Task AcceptLoopAsync(Socket listener, CancellationToken cancellationToken)
{
while (true)
{
using Socket socket = await listener.AcceptAsync(cancellationToken);
}
}
}
With this setup, the parallel algorithm isn’t held up by the stalled IPv6
attempt. It connects to the IPv4 listener in just over a millisecond, whereas
the default algorithm spends approximately half a second waiting for the IPv6
connection to make progress:
|
Method
|
Mean
|
Ratio
|
|
Default
|
511.054 ms
|
1.000
|
|
Parallel
|
1.060 ms
|
0.002
|
A bit synthetic, but it conveys the idea.
Another interesting improvement around sockets has to do with
Socket.Blocking
. “Berkeley sockets”, which is what all modern stacks implement, implement the notion of blocking / non-blocking modes. Typically by default, as is the case with .NET, sockets are in blocking mode. That means, for example, a
recv()
/
Socket.Receive
operation will synchronously block until data is available (or the socket closes). The other option is non-blocking; a socket in non-blocking mode will always return immediately from a
recv
operation, regardless of whether there’s data to read or not. If the operation would have blocked in blocking mode, in non-blocking mode it’ll instead return an error code, EAGAIN or EWOULDBLOCK, which the consuming application can then use to, for example, decide to try again later.
Enter .NET asynchronous operations. On Windows, the Windows sockets APIs provided overlapped APIs that the .NET
Socket
APIs can and do employ. But on Unix, we have the standard
recv
and friends functions. We also have mechanisms like
epoll
(Linux) and
kqueue
(macOS) that let us efficiently and synchronously wait for large numbers of file descriptors to have some activity. As such, on Unix, .NET implements asynchronous socket operations by putting a
Socket
into a non-blocking state, trying the synchronous operation (e.g.
recv
for a
Socket.ReceiveAsync
), and then if the operation couldn’t complete yet and we get back an EAGAIN/EWOULDBLOCK, data about the operation gets queued into
epoll
/
kqueue
-based machinery that will signal when the operation should be retried. This is very similar conceptually to how overlapped I/O works on Windows with I/O completion ports.
Now here’s the rub. To implement asynchronous operations on sockets, we need to flip the socket into non-blocking mode… what do we then do if, say, someone does
Socket.ReceiveAsync
but then follows that up with
Socket.Send
. The socket was flipped into non-blocking mode for the first operation… do we flip it back for the second? It turns out that’s really risky to do, with race conditions making it hard and expensive to get right due to multi-threaded use (expensive because we’d need extra synchronization). When first bringing up .NET on Linux, we made the decision that the flip would be a one-way trip: once non-blocking, always non-blocking. We flip the first time an asynchronous operation is performed, and we leave it there.
What, then, do we do if someone does in fact issue a synchronous
Receive
/
Send
after it’s already been flipped? We simulate the blocking ourselves with sync over async, basically doing the asynchronous operation and blocking on it to complete. Internally we’re able to do it cheaper than actually creating a task and blocking on it, but as a mechanism it’s basically the same.
We were comfortable with this approach in the early days on the theory that if someone starts using asynchronous operations, they’re likely to continue to, and for the odd synchronous operation here and there after that, it’s not a big deal. That has largely proven out over the many years since… except for one case.
Turns out in some systems it’s reasonably common for the initial connect to be asynchronous but then followed only by synchronous sends and receives. This ends up paying that overhead on all operations: you do
ConnectAsync
, we flip the socket to be non-blocking, and then every
Receive
/
Send
after that ends up paying the emulation costs. But there’s good news. It turns out this is also a case where we can easily and safely flip back: we can flip back to blocking before handing back control from
ConnectAsync
. For the static
ConnectAsync
overloads, the caller won’t even have a reference to the connected
Socket
until
ConnectAsync
gives it to them, and for the instance overloads, it’s defined to be erroneous to use such send/receive operations on the
Socket
concurrent with
ConnectAsync
. As such, in all cases, we can just flip it back to blocking before completing the task representing the operation. That’s exactly what
dotnet/runtime#124200
does now in .NET 11.
// Linux:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Net;
using System.Net.Sockets;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int OperationsPerInvoke = 1_000;
private readonly byte[] _buffer = new byte[1];
private Socket _listener = null!;
private Socket _client = null!;
private Socket _server = null!;
private Task _echoLoop = null!;
[GlobalSetup]
public async Task Setup()
{
_listener = new(AddressFamily.InterNetwork, SocketType.Stream, ProtocolType.Tcp);
_listener.Bind(new IPEndPoint(IPAddress.Loopback, 0));
_listener.Listen(1);
Task<Socket> accept = _listener.AcceptAsync();
_client = new(AddressFamily.InterNetwork, SocketType.Stream, ProtocolType.Tcp);
await _client.ConnectAsync(_listener.LocalEndPoint!);
_server = await accept;
_echoLoop = Task.Run(EchoLoop);
}
[GlobalCleanup]
public async Task Cleanup()
{
_client.Dispose();
try
{
await _echoLoop;
}
catch { }
_server.Dispose();
_listener.Dispose();
}
[Benchmark(OperationsPerInvoke = OperationsPerInvoke)]
public void SynchronousRoundTripAfterConnectAsync()
{
for (int i = 0; i < OperationsPerInvoke; i++)
{
_client.Send(_buffer);
_client.Receive(_buffer);
}
}
private void EchoLoop()
{
var buffer = new byte[1];
while (_server.Receive(buffer) != 0)
_server.Send(buffer);
}
}
The background socket echoes each byte. When the client calls
Receive
before the reply is available, .NET 10 must emulate the wait with the Unix
socket poller, whereas .NET 11 can wait in the native blocking
recv
call.
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
SynchronousRoundTripAfterConnectAsync
|
.NET 10.0
|
199.2 μs
|
1.00
|
|
SynchronousRoundTripAfterConnectAsync
|
.NET 11.0
|
161.6 μs
|
0.81
|
Windows has a different concern around its asynchronous socket operations.
I mentioned that Windows supplies functions that utilize overlapped I/O. These APIs, e.g.
AcceptEx
,
ConnectEx
,
DisconnectEx
, and
WSARecvMsg
, are
extension functions supplied by the installed Winsock provider. .NET looks up
their function pointers dynamically and caches them based on the socket’s
address family, socket type, and protocol. Each
Socket
instance consults that cache the first time it needs one of these functions. In .NET 10, that cache was a small global
List<T>
guarded by a lock. The list rarely contains more than a handful of entries and almost every lookup finds an entry that was initialized earlier, but even those read-only hits acquired the same lock. When many sockets began their first asynchronous operation concurrently, all of those lookups were forced through the lock one at a time.
dotnet/runtime#124997
changes
the cache to a copy-on-write array. The common read path takes a snapshot of
the array and scans it without locking. A miss still acquires a lock,
double-checks the latest array, and publishes a new array containing the
additional entry. Because entries are added only when a new combination of
address family, socket type, and protocol is encountered, misses are rare and
the warmed path no longer serializes.
Once you have the socket connection, often the next step is to layer in TLS,
with
SslStream
. During client-certificate negotiation, a server can include
in its
CertificateRequest
message the distinguished names of certificate
authorities whose certificates it will accept.
SslStream
turns each encoded
X.500 name into an
X500DistinguishedName
, ultimately making the names
available to certificate-selection logic. In .NET 10, that involved allocating
a
byte[]
for every name. On Windows, the implementation created a span over
the native SSPI buffer and then called
ToArray
; on macOS, it copied each
Core Foundation
CFData
value into a new managed array.
The
X500DistinguishedName(ReadOnlySpan<byte>)
constructor has existed since
.NET 5, but both of these
SslStream
paths predated it and weren’t updated
when it was added. With
dotnet/runtime#123904
, .NET 11
removes those intermediate arrays. Both implementations instead pass a
ReadOnlySpan<byte>
over the native encoding directly to the
X500DistinguishedName
constructor. The macOS implementation keeps the
CFData
handle alive while that span is in use, but the per-authority managed
copy is no longer needed.
Once a client certificate has been selected, macOS requires
SslStream
to
package the native handles for the leaf certificate and its intermediate
certificates into a Core Foundation array. In .NET 10,
SslStream
first
allocated an
IntPtr[]
large enough for the entire chain, populated it with
those handles, and then used the array to create the native
CFArray
.
dotnet/runtime#123905
in .NET 11 changes the interop layer to accept a
ReadOnlySpan<IntPtr>
instead.
SslStream
builds the handle list in a
Span<IntPtr>
, using
stackalloc
for
chains of up to 128 certificates and falling back to a managed array only for
larger chains. Typical certificate chains are far smaller than that, so the
usual setup path no longer allocates the temporary
IntPtr[]
at all.
A larger Linux change removes copies from the steady-state encrypted-data
path.
SslStream
uses OpenSSL, and OpenSSL traditionally exchanges data with
its caller through in-memory buffers known as BIOs. In .NET 10, encryption
first wrote ciphertext into an OpenSSL memory BIO, after which .NET copied it
into the buffer to send. Decryption went in the other direction: .NET copied
received ciphertext into a memory BIO, and after OpenSSL decrypted it,
SslStream
copied the plaintext from its own buffer into the caller’s buffer.
dotnet/runtime#128245
replaces
those memory BIOs with a custom BIO that can point directly at managed buffers.
In .NET 11, OpenSSL can write encrypted output directly into the buffer
SslStream
will send and, in the common case, write decrypted plaintext
directly into the buffer supplied by the caller. The change also combines the
setup, OpenSSL operation, and cleanup into one native call rather than four.
OpenSSL still performs its own internal TLS processing, and
SslStream
retains
a fallback buffer for unusual cases such as TLS alerts or output that doesn’t
fit, but the normal application-data path avoids the extra staging copies.
The following benchmark provides a way to reproduce the impact using
only public APIs. It establishes a TLS 1.3 connection once, outside the
measurement, and then sends one 16-KB TLS record in each direction:
// Linux:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Net;
using System.Net.Security;
using System.Net.Sockets;
using System.Security.Authentication;
using System.Security.Cryptography;
using System.Security.Cryptography.X509Certificates;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int MessageSize = 16 * 1024;
private readonly byte[] _sendBuffer = new byte[MessageSize];
private readonly byte[] _receiveBuffer = new byte[MessageSize];
private RSA _rsa = null!;
private X509Certificate2 _certificate = null!;
private SslStream _client = null!;
private SslStream _server = null!;
[GlobalSetup]
public async Task Setup()
{
Random.Shared.NextBytes(_sendBuffer);
_rsa = RSA.Create(2048);
var request = new CertificateRequest("CN=localhost", _rsa, HashAlgorithmName.SHA256, RSASignaturePadding.Pkcs1);
using X509Certificate2 temporary = request.CreateSelfSigned(DateTimeOffset.UtcNow.AddDays(-1), DateTimeOffset.UtcNow.AddDays(1));
_certificate = X509CertificateLoader.LoadPkcs12(temporary.Export(X509ContentType.Pfx), password: null, X509KeyStorageFlags.Exportable);
using TcpListener listener = new(IPAddress.Loopback, 0);
listener.Start();
Socket clientSocket = new(AddressFamily.InterNetwork, SocketType.Stream, ProtocolType.Tcp)
{
NoDelay = true,
};
Task<Socket> accept = listener.AcceptSocketAsync();
await clientSocket.ConnectAsync(listener.LocalEndpoint);
Socket serverSocket = await accept;
serverSocket.NoDelay = true;
_client = new(new NetworkStream(clientSocket, ownsSocket: true), leaveInnerStreamOpen: false, (_, _, _, _) => true);
_server = new(new NetworkStream(serverSocket, ownsSocket: true), leaveInnerStreamOpen: false);
using CancellationTokenSource timeout = new(TimeSpan.FromSeconds(30));
Task clientAuthentication = _client.AuthenticateAsClientAsync(
new SslClientAuthenticationOptions
{
TargetHost = "localhost",
EnabledSslProtocols = SslProtocols.Tls13,
},
timeout.Token);
Task serverAuthentication = _server.AuthenticateAsServerAsync(
new SslServerAuthenticationOptions
{
ServerCertificate = _certificate,
EnabledSslProtocols = SslProtocols.Tls13,
},
timeout.Token);
await Task.WhenAll(clientAuthentication, serverAuthentication);
}
[Benchmark]
public async Task RoundTrip()
{
await _client.WriteAsync(_sendBuffer);
await _server.ReadExactlyAsync(_receiveBuffer);
await _server.WriteAsync(_sendBuffer);
await _client.ReadExactlyAsync(_receiveBuffer);
}
[GlobalCleanup]
public void Cleanup()
{
_client.Dispose();
_server.Dispose();
_certificate.Dispose();
_rsa.Dispose();
}
}
On Ubuntu 24.04 x64 under WSL 2, the 16-KB round trip improves by 16%:
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
RoundTrip
|
.NET 10.0
|
68.04 μs
|
1.00
|
|
RoundTrip
|
.NET 11.0
|
57.39 μs
|
0.84
|
Moving up the stack,
HttpClient
‘s core HTTP implementation in
SocketsHttpHandler
layers protocol processing on top of TLS and the
underlying sockets. With
AutomaticDecompression
enabled,
SocketsHttpHandler
advertises
supported encodings on the request, checks the response’s final
Content-Encoding
, and, when it recognizes gzip, deflate, or Brotli, presents
an
HttpContent
whose stream decodes the compressed transport bytes as the
caller reads them.
dotnet/runtime#122676
precomputes the combined
Accept-Encoding
value when the handler is created. In the common case where the caller hasn’t supplied that header, it adds the combined value directly, avoiding an
HttpHeaderValueCollection
, its backing list and header-storage object, and an enumeration of the collection for each enabled algorithm. On the response side,
TryGetValues
avoids materializing a collection when there is no
Content-Encoding
. When decompression is needed, the wrapper takes ownership of the original content-header collection, removes the now-invalid
Content-Length
and the encoding it consumes, and retains any preceding encodings without copying every header into a new collection.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.IO.Compression;
using System.Net;
using System.Net.Sockets;
using System.Text;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD","Mean","Ratio")]
public class Benchmarks
{
private TcpListener _listener = new(IPAddress.Loopback, 0);
private CancellationTokenSource _cts = new();
private Task _server = null!;
private HttpClient _client = null!;
[GlobalSetup]
public async Task Setup()
{
_listener.Start();
_server = ServeAsync(_cts.Token);
_client = new(new SocketsHttpHandler { AutomaticDecompression = DecompressionMethods.GZip })
{
BaseAddress = new Uri($"http://127.0.0.1:{((IPEndPoint)_listener.LocalEndpoint).Port}")
};
await GetAsync();
}
[Benchmark]
public async Task<int> GetAsync()
{
using HttpResponseMessage response = await _client.GetAsync("/", HttpCompletionOption.ResponseHeadersRead);
await response.Content.CopyToAsync(Stream.Null);
return (int)response.StatusCode;
}
[GlobalCleanup]
public async Task Cleanup()
{
_client.Dispose();
_cts.Cancel();
try
{
await _server;
}
catch { }
_listener.Stop();
_cts.Dispose();
}
private async Task ServeAsync(CancellationToken cancellationToken)
{
byte[] body = Compress(new byte[1024]);
byte[] headers = Encoding.ASCII.GetBytes(
$"HTTP/1.1 200 OK\r\nContent-Encoding: gzip\r\n" +
$"Content-Length: {body.Length}\r\n\r\n");
while (true)
{
using TcpClient connection = await _listener.AcceptTcpClientAsync(cancellationToken);
NetworkStream stream = connection.GetStream();
byte[] request = new byte[4096];
while (await ReadRequestAsync(stream, request, cancellationToken))
{
await stream.WriteAsync(headers, cancellationToken);
await stream.WriteAsync(body, cancellationToken);
}
}
}
private static async Task<bool> ReadRequestAsync(Stream stream, byte[] buffer, CancellationToken cancellationToken)
{
int length = 0;
while (length < buffer.Length)
{
int read = await stream.ReadAsync(buffer.AsMemory(length), cancellationToken);
if (read == 0)
return false;
length += read;
if (buffer.AsSpan(0, length).IndexOf("\r\n\r\n"u8) >= 0)
{
return true;
}
}
throw new InvalidOperationException("Request headers are too large.");
}
private static byte[] Compress(byte[] data)
{
using MemoryStream output = new();
using (GZipStream gzip = new(output, CompressionLevel.SmallestSize, leaveOpen: true))
{
gzip.Write(data);
}
return output.ToArray();
}
}
|
Method
|
Runtime
|
Allocated
|
Alloc Ratio
|
|
GetAsync
|
.NET 10.0
|
3.44 KB
|
1.00
|
|
GetAsync
|
.NET 11.0
|
2.87 KB
|
0.83
|
SocketsHttpHandler
saw other improvements. HTTP content often consists of a single value, but sometimes a request or response needs to carry several independent pieces together in one body. Multipart content provides that packaging. For example, an HTML form submission might contain a few text fields and a file; each becomes a separate part with its own headers and content, while the collection of parts is sent as one HTTP message body. The receiver needs to know where one part ends and the next begins, so the
message uses a boundary: a token chosen to be unlikely to occur in the content
itself. In .NET 10,
MultipartContent
retained the boundary as a string. Each time the content was
serialized, it rebuilt the opening and closing delimiter strings, encoded them
into bytes, and separately wrote the pieces of the delimiters between parts.
In .NET 11,
dotnet/runtime#124963
instead constructs and
encodes the opening and closing delimiters once, when the
MultipartContent
is
created. The serialization
paths can then reuse and directly write those cached bytes.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Net.Http;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private readonly MultipartContent _content = new("mixed", "net11-boundary");
[Benchmark]
public Task Serialize() => _content.CopyToAsync(Stream.Null);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Serialize
|
.NET 10.0
|
78.49 ns
|
1.00
|
296 B
|
1.00
|
|
Serialize
|
.NET 11.0
|
41.90 ns
|
0.53
|
64 B
|
0.22
|
Several allocation reductions remove collections created only to populate or inspect another collection. For example,
dotnet/runtime#122677
writes HTTP/3 trailers directly into the final
HttpResponseHeaders
collection, eliminating a temporary
List
of tuples. Trailers are headers sent after the response body, commonly carrying information such as checksums that isn’t known when the initial headers are written.
Other paths only need a transient view over existing storage.
dotnet/runtime#131142
has
SocketsHttpHandler
inspect available HTTP/2 and HTTP/3 connections through
spans, avoiding a copy of each list to an array during idle-connection
eviction.
dotnet/runtime#123034
similarly changes
HeaderUtilities.DumpHeaders
, which is used as part of
ToString
on header collections, to take a
params ReadOnlySpan<HttpHeaders?>
, removing a small array allocation from
HttpRequestMessage.ToString()
and
HttpResponseMessage.ToString()
.
Improvements in .NET 11 also show up for
Uri
. Consider
https://user@example.com:8443/files/report%20Q3?q=%E4%BD%A0%E5%A5%BD#summary
.
Before
Uri
can expose
Scheme
,
UserInfo
,
Host
,
Port
,
AbsolutePath
,
Query
, and
Fragment
, it first locates delimiters such as
:
,
/
,
@
,
?
, and
#
. It then validates each delimited component. ASCII can usually
remain as-is,
%20
needs unescaping or preservation according to the
component, and the percent-encoded UTF-8 in the query needs decoding and
Unicode-aware canonicalization. With
dotnet/runtime#124433
, .NET 11 uses
IndexOfAny
and
SearchValues
for more of the delimiter-finding work, examining long spans a vector at a time rather than character by character. And once the component boundaries are known,
dotnet/runtime#119435
replaces repeated reserved-character and unsafe-character tests with a single optimized
SearchValues
lookup.
// dotnet run -c Release -f net10.0 --filter "*UriScanningBenchmarks*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(UriScanningBenchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class UriScanningBenchmarks
{
private readonly string _longHost = $"https://{new string('a', 64)}.example.com/path";
private readonly string _escapedAscii =
"https://example.com/" +
string.Concat(Enumerable.Range('a', 26).Select(i => $"%{i:X2}"));
[Benchmark]
public Uri LongHost() => new(_longHost);
[Benchmark]
public Uri EscapedAscii() => new(_escapedAscii);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
LongHost
|
.NET 10.0
|
218.1 ns
|
1.00
|
56 B
|
1.00
|
|
LongHost
|
.NET 11.0
|
112.9 ns
|
0.52
|
56 B
|
1.00
|
|
EscapedAscii
|
.NET 10.0
|
442.6 ns
|
1.00
|
448 B
|
1.00
|
|
EscapedAscii
|
.NET 11.0
|
208.1 ns
|
0.47
|
368 B
|
0.82
|
After finding a component,
Uri
checks whether its text is already in
canonical form or needs to be escaped or normalized. Letters and digits are
by far the most common characters, but in .NET 10 they still flowed through
the more general character tests. Some callers could also repeat a
canonicalization check whose answer parsing had already established.
dotnet/runtime#121270
adds a
fast path for ASCII letters and digits and records the earlier result so that
.NET 11 can avoid performing the same check again.
// dotnet run -c Release -f net10.0 --filter "*UriCanonicalizationBenchmarks*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(UriCanonicalizationBenchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class UriCanonicalizationBenchmarks
{
private const string Address = "https://example.com/api/items/42?view=summary#details";
[Benchmark]
public Uri Parse() => new(Address);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Parse
|
.NET 10.0
|
61.86 ns
|
1.00
|
56 B
|
1.00
|
|
Parse
|
.NET 11.0
|
44.64 ns
|
0.72
|
56 B
|
1.00
|
Non-ASCII input can require several parts of a URI to be normalized. For
example, Unicode characters may need to be preserved or percent-encoded
differently depending on whether they occur in the path, query, or fragment.
In .NET 10, parsing and rebuilding were interleaved:
Uri
normalized each of
those components separately and repeatedly extended its stored string as it
went. In addition to making the offset bookkeeping complicated, those
individual normalization results and string concatenations could create
roughly five temporary strings. In .NET 11,
dotnet/runtime#122038
separates
that rebuilding work from the subsequent validation.
Uri
normalizes the path, query, and fragment into one builder, creates the final
string once, and then validates the component boundaries in that completed
string. The host is still handled separately, but the remaining components no
longer each produce intermediate strings.
// dotnet run -c Release -f net10.0 --filter "*UriNormalizationBenchmarks*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(UriNormalizationBenchmarks).Assembly).Run(args);
[MemoryDiagnoser(false)]
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class UriNormalizationBenchmarks
{
private const string Address =
"https://dot.net/abc/defghijklmno/pqrstuv/wxyz" +
"?arch=x64&os=linux&type=release#hello\uD83C\uDF49";
[Benchmark]
public Uri Parse() => new(Address);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Parse
|
.NET 10.0
|
547.6 ns
|
1.00
|
936 B
|
1.00
|
|
Parse
|
.NET 11.0
|
386.9 ns
|
0.71
|
432 B
|
0.46
|
JSON
JSON readers and writers spend much of their time scanning text: writers look
for characters that need escaping, while readers look for whitespace and token
boundaries. .NET 11 makes several of those scans more efficient.
When using the default encoder,
Utf8JsonWriter
needs to locate characters
such as quotation marks and control characters that can’t be copied directly
into JSON. In .NET 10, that search was routed through
JavaScriptEncoder.Default
.
dotnet/runtime#129781
instead gives .NET 11 precomputed
SearchValues
sets for the default escaping
rules, allowing the writer to search the input directly. Once it finds a character to escape, the writer must emit a sequence such as
\"
or
\u0022
. In .NET 10, the escaping helper received the entire
remaining destination and performed repeated bounds checks as it wrote each
byte or character.
dotnet/runtime#129803
passes only the range known to be writable. The JIT can then prove once that
the escape fits and remove the checks from the individual stores.
// dotnet run -c Release -f net10.0 --filter "*JsonWriterBenchmarks*" --runtimes net10.0 net11.0
using System.Text.Json;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(JsonWriterBenchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class JsonWriterBenchmarks
{
private static readonly string s_fullyEscaped = new('"', 2_048);
[Benchmark]
public byte[] Write() => JsonSerializer.SerializeToUtf8Bytes(s_fullyEscaped);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Write
|
.NET 10.0
|
30.83 μs
|
1.00
|
|
Write
|
.NET 11.0
|
7.875 μs
|
0.26
|
On the reading side, insignificant whitespace is allowed between JSON tokens.
Indented documents can contain long runs of spaces and newlines, and in
.NET 10
Utf8JsonReader
examined those bytes one at a time.
dotnet/runtime#129701
changes
SkipWhiteSpace
to use
IndexOfAnyExcept
with a
SearchValues
set containing
the four JSON whitespace bytes. .NET 11 can therefore skip a whole run at
once, stopping at the next byte that might begin a token.
// dotnet run -c Release -f net10.0 --filter "*JsonReaderBenchmarks*" --runtimes net10.0 net11.0
using System.Text.Json;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(JsonReaderBenchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class JsonReaderBenchmarks
{
private static readonly Payload s_value = new(new string('a', 2_048), Enumerable.Range(0, 256).ToArray());
private static readonly byte[] s_json = JsonSerializer.SerializeToUtf8Bytes(s_value, new JsonSerializerOptions { WriteIndented = true });
[Benchmark]
public int Read()
{
Utf8JsonReader reader = new(s_json);
int tokens = 0;
while (reader.Read()) tokens++;
return tokens;
}
private sealed record Payload(string Message, int[] Values);
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Read
|
.NET 10.0
|
7.418 μs
|
1.00
|
|
Read
|
.NET 11.0
|
5.945 μs
|
0.80
|
Diagnostics
Creating an
Activity
, polling metrics, and logging all add overhead beyond what
the application is otherwise trying to accomplish. That cost is deliberately
paid to make production systems understandable, but observability code also
sits on paths that can execute for every request, dependency call, or log
event. Small fixed costs there can really add up, and disabled or
unobserved instrumentation needs to be “pay for play” so applications don’t
incur meaningful costs for diagnostics they aren’t currently collecting.
Let’s start with distributed tracing. A trace follows a request as it travels
through an application and potentially across multiple services. Each
operation along the way can be represented by an
Activity
; the activities
have their own span IDs, but share a trace ID that lets a tracing system
correlate them as parts of the same request. The W3C Trace Context standard
defines how those identifiers are carried between services, including in an
HTTP
traceparent
header. Its trace ID is represented as 32 lowercase
hexadecimal characters, and it can’t be all zeroes. Applications may need to parse and validate that identifier for every request.
In .NET 10,
DiagnosticSource
did so with a loop that checked each character
both for whether it was hexadecimal and whether it was non-zero.
In .NET 11,
dotnet/runtime#119673
replaces
that loop with two
ContainsAnyExcept
searches: one detects a character
outside
0
–
9
and
a
–
f
, while the other determines whether the entire ID
is zeroes. Those searches can examine multiple characters at a time.
W3CPropagator
had similar hand-written loops for validating trace-state and
baggage characters. In addition to replacing those loops with
SearchValues<char>
, the same PR changes baggage encoding to search for the
first character that requires escaping. If there isn’t one, as is common, it
can append the whole value at once rather than checking and appending every
character individually.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Diagnostics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly DistributedContextPropagator s_propagator =
DistributedContextPropagator.CreateW3CPropagator();
private readonly Activity _activity = new("Test");
[GlobalSetup]
public void Setup()
{
_activity.AddBaggage("a", "aaaaabbbbbcccccddddd");
_activity.Start();
}
[Benchmark]
public void ExtractTraceParent() =>
s_propagator.ExtractTraceIdAndState(
null,
static (object? carrier, string name, out string? value, out IEnumerable<string>? values) =>
{
value = name == "traceparent" ? "00-0af7651916cd43dd8448eb211c80319c-b9c7c989f97918e1-01" : null;
values = null;
},
out _, out _);
[Benchmark]
public void InjectBaggage() => s_propagator.Inject(_activity, null, static (object? carrier, string name, string value) => { });
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
ExtractTraceParent
|
.NET 10.0
|
45.41 ns
|
1.00
|
|
ExtractTraceParent
|
.NET 11.0
|
9.137 ns
|
0.20
|
|
InjectBaggage
|
.NET 10.0
|
96.69 ns
|
1.00
|
|
InjectBaggage
|
.NET 11.0
|
47.895 ns
|
0.50
|
Process APIs present a different kind of diagnostics overhead. Launching a
process requires translating managed arguments and environment variables into
the representation expected by the operating system, while inspection often
crosses into native APIs to retrieve only a small piece of information.
At the lowest level, a new process on Unix receives its command-line arguments
and environment as
argv
and
envp
. Each is a null-terminated array of
pointers to null-terminated strings; the entries in
argv
are the executable
and its arguments, while each entry in
envp
has the form
key=value
.
ProcessStartInfo
, however, exposes managed strings and a managed environment
dictionary, so
Process.Start
needs to marshal all of that data into the
native representation. In .NET 10, building
envp
first concatenated every key and value into a new managed
key=value
string and collected those strings into an intermediate array. Both
argv
and
envp
were then constructed with a native allocation for the pointer array and another allocation for each UTF-8 string. With
dotnet/runtime#126201
, .NET 11
instead makes one pass to count the pointers and calculate the total number of
UTF-8 bytes required. It then allocates one native block for
argv
and one for
envp
, with each block containing both its pointer table and all of its string
data, and writes the data directly into those blocks. That avoids the
intermediate managed strings and array, as well as all of the per-string native
allocations and frees.
There’s then the question of how the operating system actually creates the
process. The traditional Unix model uses
fork
to create a child that is
initially a logical copy of the parent, followed by
exec
in the child to
replace that copy with the requested executable. Copy-on-write means
fork
doesn’t immediately copy all of the parent’s memory, but the operating system
still needs to duplicate process state and page tables, work that can become
significant for a large, multithreaded application. In .NET 10,
Process.Start
used this
fork
-then-
exec
path on macOS. With
dotnet/runtime#126063
, .NET 11
uses
posix_spawn
for the common case.
posix_spawn
asks the operating system
to create the new process and load its executable as one operation, while
still describing the required standard-input/output/error redirection, working
directory, and signal state. A launch that requests different user or group
credentials still uses
fork
and
exec
, as macOS’s
posix_spawn
facilities
can’t perform the required
setuid
and
setgid
operations.
// Run on Linux and macOS:
// dotnet run -c Release -f net10.0 --filter "*ProcessLaunchBenchmarks*" --runtimes net10.0 net11.0
using System.Diagnostics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(
typeof(ProcessLaunchBenchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class ProcessLaunchBenchmarks
{
private readonly ProcessStartInfo _plain = CreateStartInfo();
private readonly ProcessStartInfo _withEnvironment = CreateStartInfo(includeEnvironment: true);
[Benchmark]
public void StartWithEnvironment() => StartAndWait(_withEnvironment);
[Benchmark]
public void StartAndWaitForExit() => StartAndWait(_plain);
private static ProcessStartInfo CreateStartInfo(bool includeEnvironment = false)
{
ProcessStartInfo psi = new("whoami")
{
RedirectStandardOutput = true,
UseShellExecute = false,
};
if (includeEnvironment)
{
for (int i = 0; i < 256; i++)
psi.Environment[$"NET11PERF_{i}"] = new string('x', 32);
}
return psi;
}
private static void StartAndWait(ProcessStartInfo psi)
{
using Process process = Process.Start(psi)!;
process.WaitForExit();
}
}
Process creation dominates the elapsed time in this benchmark, but the
environment-marshalling allocation reduction is clear.
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
StartWithEnvironment
|
.NET 10.0
|
1.484 ms
|
1.00
|
48.16 KB
|
1.00
|
|
StartWithEnvironment
|
.NET 11.0
|
1.435 ms
|
0.97
|
14.48 KB
|
0.30
|
|
|
|
|
|
|
|
|
StartAndWaitForExit
|
.NET 10.0
|
1.371 ms
|
1.00
|
16.95 KB
|
1.00
|
|
StartAndWaitForExit
|
.NET 11.0
|
1.362 ms
|
0.99
|
14.48 KB
|
0.85
|
Once a process is running, a
Process
instance can expose a bunch of information about it. Much of that OS data is gathered and cached together
in an internal
ProcessInfo
object so that properties needing it can share the work. In .NET 10 on Linux and macOS, however, asking only for
ProcessName
triggered the machinery to populate the whole object and everything on it, which was unnecessarily costly if you only needed the name.
Process.ToString()
includes the process name, so it incurred the same cost. In .NET 11,
dotnet/runtime#126449
from
@tmds
adds a narrower operating-system query for the
name.
ProcessName
and
ToString()
can use that to query without
collecting the rest of the process metadata.
// Run on Linux and macOS:
// dotnet run -c Release -f net10.0 --filter "*ProcessNameBenchmarks*" --runtimes net10.0 net11.0
using System.Diagnostics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(ProcessNameBenchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class ProcessNameBenchmarks
{
[Benchmark]
public string GetProcessName()
{
using Process process = Process.GetProcessById(Environment.ProcessId);
return process.ProcessName;
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
GetProcessName
|
.NET 10.0
|
332.13 μs
|
1.00
|
|
GetProcessName
|
.NET 11.0
|
11.90 μs
|
0.04
|
Process
can also query processes on another Windows machine. APIs such as
GetProcesses(string machineName)
accept a machine name, and the remote path
uses Windows performance-counter infrastructure to retrieve the information.
That support in turn depends on additional components, including remote
Registry access. None of that should be necessary for an application that only
starts or inspects processes on its own machine. In .NET 10, however, several local-only APIs delegated to overloads that also supported remote machines. For example,
GetProcessById(int)
called the machine-name overload with
"."
, and other helpers selected between local and remote implementations at run time. Even when the application always took the local branch, the trimmer saw a call path to both implementations and needed to preserve the remote-process and
PerformanceCounter
code. As a result, even a Native AOT application that did little more than call
Process.Start
could carry that unused support in its executable. In .NET 11,
dotnet/runtime#126338
gives
the local APIs dedicated paths that don’t reference the remote implementation.
The remote implementation is instead reached through a delegate initialized
only when an API is actually asked to operate on another machine. Remote
process inspection continues to work, but if an application uses only local
process APIs, .NET 11’s trimmer can now prove that the remote machinery and its
dependencies are unreachable and remove them, resulting in significantly smaller binary size.
// Add to the csproj's PropertyGroup:
// <PublishAot>true</PublishAot>
// <InvariantGlobalization>true</InvariantGlobalization>
// <AssemblyName>ProcessSize</AssemblyName>
using System.Diagnostics;
using Process process = Process.Start(new ProcessStartInfo("cmd.exe", "/c exit")
{
UseShellExecute = false
})!;
process.WaitForExit();
You can then publish both targets and inspect the resulting executable:
# dotnet publish -c Release -f net10.0 -r win-x64 -o publish-net10
# dotnet publish -c Release -f net11.0 -r win-x64 -o publish-net11
# Get-Item .\publish-net10\ProcessSize.exe, .\publish-net11\ProcessSize.exe |
# ForEach-Object { "$($_.Directory.Name): $($_.Length) bytes" }
|
Runtime
|
Executable size
|
|
.NET 10.0
|
1,599,488 bytes
|
|
.NET 11.0
|
1,326,080 bytes
|
Metrics report numerical information about an application, such as the number
of requests processed or the current depth of a queue. With
System.Diagnostics.Metrics
, a
Meter
creates instruments that produce those
measurements, and a listener such as an OpenTelemetry provider consumes them.
Some instruments are updated by the application whenever an event occurs. An
observable instrument instead registers a callback that computes its current
value when a listener asks to collect it. That pull model is useful for values
like queue depth: the application doesn’t need to record every change, only to
report the depth when it’s observed. The callback for an
ObservableGauge<T>
,
ObservableCounter<T>
, or
ObservableUpDownCounter<T>
can return a
T
, a
Measurement<T>
, or an
IEnumerable<Measurement<T>>
. A
Measurement<T>
pairs the value with any
associated tags, and the enumerable form allows one callback to report
multiple tagged values. The first two forms always produce exactly one
measurement. In .NET 10,
ObservableInstrument<T>
nevertheless normalized those
single-value forms into the enumerable model. Every time a listener collected
the instrument, it invoked the callback, put the result into a new one-element
Measurement<T>[]
, and then enumerated that array to report the value. With
dotnet/runtime#128039
from
@unsafePtr
, .NET 11 recognizes the built-in
single-value forms and sends their result directly to
MeterListener.NotifyMeasurement
, avoiding both the array and its enumeration.
The enumerable form retains its existing path: the application owns that
sequence, and it may legitimately contain any number of measurements.
// dotnet run -c Release -f net10.0 --filter "*ObservableBenchmarks*" --runtimes net10.0 net11.0
using System.Diagnostics.Metrics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(ObservableBenchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class ObservableBenchmarks
{
private int _queueLength = 42;
private Meter _meter = new("Sample.Service");
private ObservableGauge<int> _gauge = null!;
private MeterListener _listener = new();
[GlobalSetup]
public void Setup()
{
_gauge = _meter.CreateObservableGauge("queue.length", () => _queueLength);
_listener.InstrumentPublished = (instrument, listener) =>
{
if (instrument.Meter == _meter)
listener.EnableMeasurementEvents(instrument);
};
_listener.SetMeasurementEventCallback<int>( static (instrument, measurement, tags, state) => { });
_listener.Start();
}
[GlobalCleanup]
public void Cleanup()
{
_listener.Dispose();
_meter.Dispose();
}
[Benchmark]
public void Record() => _listener.RecordObservableInstruments();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Record
|
.NET 10.0
|
17.16 ns
|
1.00
|
72 B
|
1.00
|
|
Record
|
.NET 11.0
|
4.511 ns
|
0.26
|
–
|
0
|
In previous iterations of Performance Improvements in .NET, I’ve discussed
“false sharing.” Modern processors move data between memory and their caches
in fixed-size chunks known as cache lines, commonly 64 bytes. Before a core can
write to a location, it needs exclusive ownership of the cache line containing
that location, invalidating copies of the same line held by other cores. That matters even when the cores aren’t updating the same value. Imagine two
long
fields next to each other in memory, with one core repeatedly updating
the first and another core repeatedly updating the second. The fields are
logically independent, but if they occupy the same cache line, each core’s
write invalidates the line for the other. Ownership of the line continually
bounces between the cores, limiting scalability despite there being no
sharing conceptually. Hence, “false sharing.”
System.Runtime.Caching.MemoryCache
maintains performance counters for
operations such as gets, hits, misses, adds, removes, and trims. In .NET 10,
those counters were stored as elements in a small
long[]
. The array header,
including its length, and several unrelated counters could all occupy the same
cache line. Under load, cores performing different cache operations would
therefore contend for ownership of that line as they updated different
counters. Accessing a counter through the array also meant loading the array
length for a bounds check.
dotnet/runtime#131470
addresses this in .NET 11 by
replacing the array with named fields and laying those fields out across separate
cache lines. Counters that an operation naturally updates together can remain
together, while unrelated counters are kept apart. That deliberately spends a
small amount of additional memory on padding in order to reduce cache-line
bouncing under contention, while the named fields also avoid the array bounds
checks.
// Run separately so each target uses its matching System.Runtime.Caching package:
// dotnet run -c Release -f net10.0 --filter "*"
// dotnet run -c Release -f net11.0 --filter "*"
using System.Runtime.Caching;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int ThreadCount = 32;
private const int TotalOperations = 256_000;
private readonly MemoryCache _cache = new("Benchmark");
[GlobalSetup]
public void Setup() => _cache.Set("key", 42, DateTimeOffset.MaxValue);
[GlobalCleanup]
public void Cleanup() => _cache.Dispose();
[Benchmark(OperationsPerInvoke = TotalOperations)]
public void Get()
{
Parallel.For(0, ThreadCount, new ParallelOptions
{
MaxDegreeOfParallelism = ThreadCount
}, _ =>
{
for (int i = 0; i < TotalOperations / ThreadCount; i++)
_cache.Get("key");
});
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Get
|
.NET 10.0
|
75.83 ns
|
1.00
|
|
Get
|
.NET 11.0
|
51.76 ns
|
0.68
|
Logging is another per-event diagnostics path.
Microsoft.Extensions.Logging’s EventSource provider shrank its cost when the
JsonMessage
keyword is on.
dotnet/runtime#131229
reuses a
[ThreadStatic]
MemoryStream
and
Utf8JsonWriter
in
EventSourceLogger.ToJson
, avoiding both allocations on every logged event,
leaving primarily the returned JSON string. Buffers larger than 1 KB aren’t
retained on the thread.
// Add a FrameworkReference to Microsoft.AspNetCore.App.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Diagnostics.Tracing;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using Microsoft.Extensions.Logging;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private JsonLoggingListener _listener = null!;
private ILoggerFactory _factory = null!;
private ILogger _logger = null!;
[GlobalSetup]
public void Setup()
{
_listener = new JsonLoggingListener();
_factory = LoggerFactory.Create(builder => builder.AddEventSourceLogger());
_logger = _factory.CreateLogger("Sample");
}
[GlobalCleanup]
public void Cleanup()
{
_factory.Dispose();
_listener.Dispose();
}
[Benchmark]
public void Log() => _logger.LogInformation("Processed {Count} items for {Customer}", 42, "Contoso");
private sealed class JsonLoggingListener : EventListener
{
protected override void OnEventSourceCreated(EventSource eventSource)
{
if (eventSource.Name == "Microsoft-Extensions-Logging")
EnableEvents(eventSource, EventLevel.LogAlways, (EventKeywords)8); // JsonMessage
}
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
Log
|
.NET 10.0
|
506.4 ns
|
1.00
|
1.92 KB
|
1.00
|
|
Log
|
.NET 11.0
|
400.5 ns
|
0.79
|
1.15 KB
|
0.60
|
Cryptography
ASN.1 is the binary data-description format used by
certificates, public and private keys, and many other cryptographic structures.
Its encodings are nested: reading a sequence produces another reader over the
sequence’s contents, which may itself contain more sequences.
dotnet/runtime#125254
adds
ValueAsnReader
, a span-based
ref struct
counterpart to
AsnReader
.
dotnet/runtime#125346
further applies that representation to
selected RSA, PKCS/CMS, ECC, and X.509 decoders.
And
dotnet/runtime#125528
carries it through generated
key loaders so parsing layers can pass views of the original data by reference
rather than wrapping the same bytes in new reader objects.
// dotnet run -c Release -f net11.0 --filter "*"
using BenchmarkDotNet.Running;
using System.Formats.Asn1;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly byte[] s_der =
[
0x30, 0x0F,
0x30, 0x03, 0x02, 0x01, 0x01,
0x30, 0x03, 0x02, 0x01, 0x02,
0x30, 0x03, 0x02, 0x01, 0x03,
];
[Benchmark(Baseline = true)]
public int ReadWithEscapingAsnReader()
{
AsnReader outer = CreateReader();
AsnReader sequence = ReadSequence(outer);
int count = 0;
while (sequence.HasData)
{
AsnReader child = ReadSequence(sequence);
_ = child.ReadIntegerBytes();
child.ThrowIfNotEmpty();
count++;
}
outer.ThrowIfNotEmpty();
return count;
}
[Benchmark]
public int ReadWithValueAsnReader()
{
ValueAsnReader outer = new(s_der, AsnEncodingRules.DER);
ValueAsnReader sequence = outer.ReadSequence();
int count = 0;
while (sequence.HasData)
{
ValueAsnReader child = sequence.ReadSequence();
_ = child.ReadIntegerBytes();
child.ThrowIfNotEmpty();
count++;
}
outer.ThrowIfNotEmpty();
return count;
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static AsnReader CreateReader() => new(s_der, AsnEncodingRules.DER);
[MethodImpl(MethodImplOptions.NoInlining)]
private static AsnReader ReadSequence(AsnReader reader) => reader.ReadSequence();
}
|
Method
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
ReadWithEscapingAsnReader
|
79.81 ns
|
1.00
|
240 B
|
1.00
|
|
ReadWithValueAsnReader
|
31.05 ns
|
0.39
|
–
|
0.00
|
Some ASN.1 values add text validation to that parsing work. ASN.1 defines
several text types with restricted character sets.
IA5String
is ASCII, while
VisibleString
permits the printable ASCII characters from space through
~
.
Encoding or decoding one must both copy the data and reject characters outside
the allowed range.
dotnet/runtime#131109
vectorizes that validation and
transcoding for
IA5String
and
VisibleString
, checking and copying multiple
characters at once.
dotnet/runtime#131170
then applies the same approach
to big-endian UCS-2
BMPString
.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Formats.Asn1;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly string s_text = new('A', 1024);
private readonly char[] _destination = new char[1024];
private readonly AsnWriter _writer = new(AsnEncodingRules.DER);
private readonly byte[] _encoded = EncodeText();
[Benchmark]
public int Read()
{
AsnDecoder.TryReadCharacterString(
_encoded,
_destination,
AsnEncodingRules.DER,
UniversalTagNumber.VisibleString,
out _,
out int charsWritten);
return charsWritten;
}
[Benchmark]
public int Write()
{
_writer.Reset();
_writer.WriteCharacterString(UniversalTagNumber.VisibleString, s_text);
return _writer.GetEncodedLength();
}
private static byte[] EncodeText()
{
AsnWriter writer = new(AsnEncodingRules.DER);
writer.WriteCharacterString(UniversalTagNumber.VisibleString, s_text);
return writer.Encode();
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Read
|
.NET 10.0
|
1.243 μs
|
1.00
|
|
Read
|
.NET 11.0
|
112.7 ns
|
0.091
|
|
Write
|
.NET 10.0
|
1.556 μs
|
1.00
|
|
Write
|
.NET 11.0
|
152.8 ns
|
0.098
|
dotnet/runtime#131616
takes that further and extends the approach to the non-contiguous character sets of
PrintableString
and
NumericString
. The validation has more than one accepted range, but it can still classify a vector of characters at a time and fall back to the scalar checks only where necessary:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Formats.Asn1;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private static readonly string s_text = new('A', 1024);
private readonly char[] _destination = new char[1024];
private readonly AsnWriter _writer = new(AsnEncodingRules.DER);
private readonly byte[] _encoded = EncodeText();
[Benchmark]
public int Read()
{
AsnDecoder.TryReadCharacterString(
_encoded,
_destination,
AsnEncodingRules.DER,
UniversalTagNumber.PrintableString,
out _,
out int charsWritten);
return charsWritten;
}
[Benchmark]
public int Write()
{
_writer.Reset();
_writer.WriteCharacterString(UniversalTagNumber.PrintableString, s_text);
return _writer.GetEncodedLength();
}
private static byte[] EncodeText()
{
AsnWriter writer = new(AsnEncodingRules.DER);
writer.WriteCharacterString(UniversalTagNumber.PrintableString, s_text);
return writer.Encode();
}
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
|
Read
|
.NET 10.0
|
1.242 μs
|
1.00
|
|
Read
|
.NET 11.0
|
263.9 ns
|
0.21
|
|
Write
|
.NET 10.0
|
1.555 μs
|
1.00
|
|
Write
|
.NET 11.0
|
428.3 ns
|
0.28
|
Once all input is available, hashing needn’t retain reusable state. SHA-1 is no
longer suitable for security decisions such as signing new content, but .NET
still needs it for compatibility identifiers such as an assembly’s public-key
token.
dotnet/runtime#120674
adds a one-shot path to the internal implementation used for those non-secret
purposes. Its hash state, work area, and padding buffer can live on the stack.
AssemblyName.GetPublicKeyToken()
now uses the one-shot path as it has
the complete public key available for a single operation:
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using System.Reflection;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "RatioSD", "Median")]
public class Benchmarks
{
private static readonly AssemblyName s_an = typeof(object).Assembly.GetName();
[Benchmark]
public byte[]? GetPublicKeyToken() => ((AssemblyName)s_an.Clone()).GetPublicKeyToken();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
GetPublicKeyToken
|
.NET 10.0
|
1.458 μs
|
1.00
|
664 B
|
1.00
|
|
GetPublicKeyToken
|
.NET 11.0
|
721.4 ns
|
0.49
|
296 B
|
0.45
|
AES key wrap is used to encrypt cryptographic keys before they’re stored or
sent elsewhere. Wrapping or unwrapping one key requires applying AES many
times. In .NET 10 on Windows and Apple platforms, the implementation performed
each of those steps through a general-purpose helper that created a native AES
cipher, processed one block, and then destroyed the cipher. The public
Aes
object could be reused, but internally a single key-wrap operation still
repeated that native setup and cleanup, with the number of repetitions growing
with the size of the key material.
dotnet/runtime#129921
from
@vcsjones
changes the Windows implementation to
create one native cipher and reuse it for the entire wrap or unwrap operation.
dotnet/runtime#129911
does the same for Apple’s
implementation.
// dotnet run -c Release -f net10.0 --filter "*" --runtimes net10.0 net11.0
using BenchmarkDotNet.Running;
using System.Security.Cryptography;
using BenchmarkDotNet.Attributes;
BenchmarkSwitcher.FromAssembly(typeof(Benchmarks).Assembly).Run(args);
[MemoryDiagnoser(false), HideColumns("Job", "Error", "StdDev", "Median", "RatioSD")]
public class Benchmarks
{
private const int PlaintextLength = 4096;
private static readonly byte[] s_key = new byte[32]; // Fixed AES-256 key.
private readonly Aes _aes = Aes.Create();
private byte[] _plaintext = [];
private byte[] _ciphertext = [];
private byte[] _encryptDestination = [];
private byte[] _decryptDestination = [];
[GlobalSetup]
public void Setup()
{
_aes.Key = s_key;
_plaintext = new byte[PlaintextLength];
new Random(42).NextBytes(_plaintext);
int wrappedLength = Aes.GetKeyWrapPaddedLength(PlaintextLength);
_ciphertext = new byte[wrappedLength];
_aes.EncryptKeyWrapPadded(_plaintext, _ciphertext);
_encryptDestination = new byte[wrappedLength];
_decryptDestination = new byte[PlaintextLength];
}
[Benchmark]
public byte[] EncryptKeyWrapPadded()
{
_aes.EncryptKeyWrapPadded(_plaintext, _encryptDestination);
return _encryptDestination;
}
[Benchmark]
public int DecryptKeyWrapPadded()
{
_aes.TryDecryptKeyWrapPadded(_ciphertext, _decryptDestination, out int written);
return written;
}
[GlobalCleanup]
public void Cleanup() => _aes.Dispose();
}
|
Method
|
Runtime
|
Mean
|
Ratio
|
Allocated
|
Alloc Ratio
|
|
EncryptKeyWrapPadded
|
.NET 10.0
|
2.497 ms
|
1.00
|
264 KB
|
1.00
|
|
EncryptKeyWrapPadded
|
.NET 11.0
|
111.3 μs
|
0.045
|
88 B
|
0.00033
|
|
DecryptKeyWrapPadded
|
.NET 10.0
|
2.473 ms
|
1.00
|
264 KB
|
1.00
|
|
DecryptKeyWrapPadded
|
.NET 11.0
|
123.5 μs
|
0.050
|
88 B
|
0.00033
|
Certificate validation can be dominated by work outside the signature math.
For example, during revocation checking on Linux, a downloaded certificate
revocation list (CRL) is persisted to disk. A later chain build could therefore
avoid the network, but it still needed to open the file, read it, parse the
encoded CRL, and create a new native handle.
For .NET 11,
dotnet/runtime#123562
adds a
bounded in-memory cache of parsed CRLs. A repeated lookup can reuse the native
CRL handle directly, while least-recently-used eviction and GC-assisted aging
prevent the cache from retaining entries indefinitely.
Authority Information Access (AIA) presents a related problem. A certificate
can name a URL from which a missing issuer certificate may be downloaded, and
multiple concurrent chain builds may all discover the same missing issuer.
dotnet/runtime#130456
reuses
the cache infrastructure so those builds share one asynchronous download
rather than issuing duplicate requests. Failed downloads aren’t cached, old
successful responses are refreshed in the background, and Linux now limits
each chain build to two AIA downloads, matching Windows and bounding the amount
of network work one chain can trigger.
What’s Next?
Whew! Several hundred performance improvements later, .NET 11 is indeed one
louder. If any of the examples in this post look
like code in your applications, please try the latest
.NET 11 release candidate
and measure your own workloads. If something got faster, we’d love to hear about it. If something got slower, we’d also love to hear about it. And if you have ideas for how .NET 12 can be turned up even louder, we’re all ears.
Happy coding!
.jpg)
Amazon’s Trainium chip was originally designed for AI training. However, Amazon Web Services chose to break up AI inference into two parts, with Trainium running the more computationally complex portion and Cerebras’s wafer-scale engine taking on the more memory-intensive portion.
Amazon
Tensordyne’s unique approach to AI inference combines a logarithmic number format with bespoke hardware in the company’s Napier chip.
Tensordyne
In Fort Meade, Md., an NSA data center hosted one of the world’s fastest computers of its time—although not often discussed, because of its sensitive, high-security code breaking and cipher hunting work.
National Cryptologic Museum
IBM’s Harvest system, custom-built for the NSA for code breaking, paired the IBM 7030 Stretch mainframe with a bespoke data-stream processor. Stretch handled ordinary computing and input/output, including the Tractor automated tape library. Both units shared two kinds of memory: a large main bank and a smaller, faster bank. When Stretch switched to streaming mode, Harvest drew two streams of data, P and Q, from memory, processed them in parallel, and returned the results as a third stream, called R.
Chris Philpot
IBM’s Frances Allen helped design Alpha, Harvest’s custom-built programming language.
IBM
IBM’s James H. Pomerene was chief engineer of Harvest, supervising its custom-designed circuits that’d been optimized for algorithms used in many cryptographic jobs.
IEEE
IBM’s Fred Brooks Jr. was a key co-architect of Harvest’s hardware system.
An IBM technician holds one of the data cassettes used with Harvest’s automated Tractor tape drives.
IBM
A Harvest operator types on one of the main system consoles, a repurposed IBM Selectric typewriter.
IBM
A placard commemorates the 1976 decommissioning of IBM’s Harvest computer at the NSA’s headquarters in Fort Meade, Md.
National Cryptologic Museum
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