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eiriktsarpaliseiriktsarpalis
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Add TensorPrimitives benchmarks.
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Lines changed: 270 additions & 5 deletions

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‎src/benchmarks/micro/MicroBenchmarks.csproj‎

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<PackageReference Include="System.Numerics.Vectors" Version="4.5.0" />
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<PackageReference Include="System.Threading.Tasks.Extensions" Version="4.5.4" />
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</ItemGroup>
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<ItemGroup Condition="'$(TargetFrameworkIdentifier)' == '.NETCoreApp' And '$(_TargetFrameworkVersionWithoutV)' &gt;= '8.0'">
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<!-- we want both net8.0 and net9.0 targets to use the 9.0.0 version of the NuGet package (since this is where the generic math APIs were first added) -->
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<PackageReference Include="System.Numerics.Tensors" Version="$(SystemThreadingChannelsPackageVersion)" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\harness\BenchmarkDotNet.Extensions\BenchmarkDotNet.Extensions.csproj" />
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</ItemGroup>
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<ItemGroup Condition=" '$(TargetFrameworkIdentifier)' == '.NETFramework' Or ('$(TargetFrameworkIdentifier)' == '.NETCoreApp' And '$(_TargetFrameworkVersionWithoutV)' &lt; '8.0')">
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<Compile Remove="libraries\System.Buffers\SearchValuesByteTests.cs" />
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<Compile Remove="libraries\System.Buffers\SearchValuesCharTests.cs" />
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<Compile Remove="libraries\System.Text.Encoding\Perf.Ascii.cs" />
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<Compile Remove="libraries\System.Buffers\SearchValuesByteTests.cs" />
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<Compile Remove="libraries\System.Buffers\SearchValuesCharTests.cs" />
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<Compile Remove="libraries\System.Text.Encoding\Perf.Ascii.cs" />
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<Compile Remove="libraries\System.Numerics.Tensors\*.cs" />
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</ItemGroup>
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<!-- This is not removing things from older Net versions, it is removing from newer Net versions -->

‎src/benchmarks/micro/libraries/System.Numerics.Tensors/Perf_BinaryIntegerTensorPrimitives.cs‎

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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using BenchmarkDotNet.Attributes;
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using BenchmarkDotNet.Extensions;
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using MicroBenchmarks;
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namespace System.Numerics.Tensors.Tests
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{
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[BenchmarkCategory(Categories.Libraries, Categories.SIMD, Categories.JIT)]
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[GenericTypeArguments(typeof(int))]
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public class Perf_BinaryIntegerTensorPrimitives<T>
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where T : unmanaged, IBinaryInteger<T>
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{
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[Params(128, 6 * 512 + 7)]
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public int BufferLength;
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private T[] _source1;
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private T[] _destination;
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[GlobalSetup]
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public void Init()
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{
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_source1 = ValuesGenerator.Array<T>(BufferLength, seed: 42);
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_destination = new T[BufferLength];
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}
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#region Unary Operations
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[Benchmark]
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public void LeadingZeroCount() => TensorPrimitives.LeadingZeroCount<T>(_source1, _destination);
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[Benchmark]
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public void OnesComplement() => TensorPrimitives.OnesComplement<T>(_source1, _destination);
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[Benchmark]
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public void PopCount() => TensorPrimitives.PopCount<T>(_source1, _destination);
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[Benchmark]
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public void ShiftLeft() => TensorPrimitives.ShiftLeft<T>(_source1, shiftAmount: 3, _destination);
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[Benchmark]
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public void TrailingZeroCount() => TensorPrimitives.TrailingZeroCount<T>(_source1, _destination);
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#endregion
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}
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}

‎src/benchmarks/micro/libraries/System.Numerics.Tensors/Perf_FloatingPointTensorPrimitives.cs‎

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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using BenchmarkDotNet.Attributes;
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using BenchmarkDotNet.Extensions;
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using MicroBenchmarks;
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using System.Linq;
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namespace System.Numerics.Tensors.Tests
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{
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[BenchmarkCategory(Categories.Libraries, Categories.SIMD, Categories.JIT)]
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[GenericTypeArguments(typeof(float))]
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[GenericTypeArguments(typeof(double))]
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public class Perf_FloatingPointTensorPrimitives<T>
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where T : unmanaged, IFloatingPointIeee754<T>
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{
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[Params(128, 6 * 512 + 7)]
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public int BufferLength;
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private T[] _source1;
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private T[] _source2;
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private T[] _source3;
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private T _scalar1;
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private T[] _ones;
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private T[] _destination;
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[GlobalSetup]
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public void Init()
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{
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_source1 = ValuesGenerator.Array<T>(BufferLength, seed: 42);
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_source2 = ValuesGenerator.Array<T>(BufferLength, seed: 43);
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_source3 = ValuesGenerator.Array<T>(BufferLength, seed: 44);
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_scalar1 = ValuesGenerator.Value<T>(seed: 45);
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_ones = Enumerable.Repeat(T.One, BufferLength).ToArray();
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_destination = new T[BufferLength];
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}
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#region Unary Operations
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[Benchmark]
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public void AtanPi() => TensorPrimitives.AtanPi<T>(_source1, _destination);
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[Benchmark]
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public void Exp() => TensorPrimitives.Exp<T>(_source1, _destination);
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[Benchmark]
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public void Log() => TensorPrimitives.Log<T>(_source1, _destination);
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[Benchmark]
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public void Round() => TensorPrimitives.Round<T>(_source1, _destination);
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[Benchmark]
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public void Sin() => TensorPrimitives.Sin<T>(_source1, _destination);
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[Benchmark]
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public void Sinh() => TensorPrimitives.Sinh<T>(_source1, _destination);
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[Benchmark]
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public void Sigmoid() => TensorPrimitives.Sigmoid<T>(_source1, _destination);
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[Benchmark]
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public void Sqrt() => TensorPrimitives.Sqrt<T>(_source1, _destination);
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[Benchmark]
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public void Truncate() => TensorPrimitives.Truncate<T>(_source1, _destination);
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#endregion
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#region Binary/Ternary Operations
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[Benchmark]
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public void FusedMultiplyAdd_Vectors() => TensorPrimitives.FusedMultiplyAdd<T>(_source1, _source2, _source3, _destination);
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[Benchmark]
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public void FusedMultiplyAdd_ScalarAddend() => TensorPrimitives.FusedMultiplyAdd(_source1, _scalar1, _source2, _destination);
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[Benchmark]
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public void FusedMultiplyAdd_ScalarMultiplier() => TensorPrimitives.FusedMultiplyAdd(_source1, _source2, _scalar1, _destination);
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[Benchmark]
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public void Ieee754Remainder_Vector() => TensorPrimitives.Ieee754Remainder<T>(_source1, _source2, _destination);
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[Benchmark]
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public void Ieee754Remainder_ScalarDividend() => TensorPrimitives.Ieee754Remainder(_scalar1, _source1, _destination);
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[Benchmark]
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public void Ieee754Remainder_ScalarDivisor() => TensorPrimitives.Ieee754Remainder(_source1, _scalar1, _destination);
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[Benchmark]
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public void Pow_Vectors() => TensorPrimitives.Pow<T>(_source1, _ones, _destination);
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[Benchmark]
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public void Pow_ScalarBase() => TensorPrimitives.Pow(_scalar1, _ones, _destination);
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[Benchmark]
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public void Pow_ScalarExponent() => TensorPrimitives.Pow(_source1, T.One, _destination);
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#endregion
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#region Reducers
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[Benchmark]
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public T CosineSimilarity() => TensorPrimitives.CosineSimilarity<T>(_source1, _source2);
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[Benchmark]
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public T Distance() => TensorPrimitives.Distance<T>(_source1, _source2);
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#endregion
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}
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}

‎src/benchmarks/micro/libraries/System.Numerics.Tensors/Perf_NumberTensorPrimitives.cs‎

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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using BenchmarkDotNet.Attributes;
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using BenchmarkDotNet.Extensions;
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using MicroBenchmarks;
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using System.Linq;
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namespace System.Numerics.Tensors.Tests
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{
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[BenchmarkCategory(Categories.Libraries, Categories.SIMD, Categories.JIT)]
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[GenericTypeArguments(typeof(int))]
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[GenericTypeArguments(typeof(float))]
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[GenericTypeArguments(typeof(double))]
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public class Perf_NumberTensorPrimitives<T>
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where T : INumber<T>, IBitwiseOperators<T, T, T>
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{
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[Params(128, 6 * 512 + 7)]
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public int BufferLength;
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private T[] _source1;
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private T[] _source2;
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private T[] _source3;
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private T _scalar1;
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private T[] _ones;
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private T[] _destination;
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[GlobalSetup]
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public void Init()
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{
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_source1 = ValuesGenerator.Array<T>(BufferLength, seed: 42);
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_source2 = ValuesGenerator.Array<T>(BufferLength, seed: 43);
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_source3 = ValuesGenerator.Array<T>(BufferLength, seed: 44);
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_scalar1 = ValuesGenerator.Value<T>(seed: 45);
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_ones = Enumerable.Repeat(T.One, BufferLength).ToArray();
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_destination = new T[BufferLength];
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}
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#region Unary Operations
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[Benchmark]
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public void Abs() => TensorPrimitives.Abs<T>(_source1, _destination);
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[Benchmark]
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public void Negate() => TensorPrimitives.Abs<T>(_source1, _destination);
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#endregion
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#region Binary/Ternary Operations
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[Benchmark]
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public void Add_Vector() => TensorPrimitives.Add<T>(_source1, _source2, _destination);
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[Benchmark]
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public void Add_Scalar() => TensorPrimitives.Add(_source1, _scalar1, _destination);
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[Benchmark]
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public void AddMultiply_Vectors() => TensorPrimitives.AddMultiply<T>(_source1, _source2, _source3, _destination);
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[Benchmark]
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public void AddMultiply_ScalarAddend() => TensorPrimitives.AddMultiply(_source1, _scalar1, _source2, _destination);
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[Benchmark]
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public void AddMultiply_ScalarMultiplier() => TensorPrimitives.AddMultiply(_source1, _source2, _scalar1, _destination);
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[Benchmark]
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public void BitwiseAnd_Vector() => TensorPrimitives.BitwiseAnd<T>(_source1, _source2, _destination);
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[Benchmark]
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public void BitwiseAnd_Scalar() => TensorPrimitives.BitwiseAnd(_source1, _scalar1, _destination);
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[Benchmark]
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public void Divide_Vector() => TensorPrimitives.Divide<T>(_source1, _ones, _destination);
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[Benchmark]
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public void Divide_Scalar() => TensorPrimitives.Divide(_source1, T.One, _destination);
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[Benchmark]
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public void Max_Vector() => TensorPrimitives.Max<T>(_source1, _source2, _destination);
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[Benchmark]
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public void Max_Scalar() => TensorPrimitives.Max(_source1, _scalar1, _destination);
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[Benchmark]
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public void MaxMagnitude_Vector() => TensorPrimitives.MaxMagnitude<T>(_source1, _source2, _destination);
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[Benchmark]
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public void MaxMagnitude_Scalar() => TensorPrimitives.MaxMagnitude(_source1, _scalar1, _destination);
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#endregion
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#region Reducers
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[Benchmark]
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public T Max() => TensorPrimitives.Max<T>(_source1);
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[Benchmark]
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public T SumOfMagnitudes() => TensorPrimitives.SumOfMagnitudes<T>(_ones);
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[Benchmark]
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public T SumOfSquares() => TensorPrimitives.SumOfSquares<T>(_ones);
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[Benchmark]
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public int IndexOfMax() => TensorPrimitives.IndexOfMax<T>(_source1);
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#endregion
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}
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}

‎src/harness/BenchmarkDotNet.Extensions/ValuesGenerator.cs‎

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/// For byte and sbyte values are built from Random.NextBytes, for other types GenerateValue is used
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/// to generate a random value in the appropriate range
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/// </summary>
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public static T[] Array<T>(int count)
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public static T[] Array<T>(int count, int? seed = null)
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{
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var result = new T[count];
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var random = new Random(Seed);
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var random = new Random(seed ?? Seed);
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if (typeof(T) == typeof(byte) || typeof(T) == typeof(sbyte))
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{
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return result;
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}
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public static T Value<T>(int? seed = null)
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{
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var random = new Random(seed ?? Seed);
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return GenerateValue<T>(random);
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}
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public static readonly byte[] s_encodingMap = {
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65, 66, 67, 68, 69, 70, 71, 72, //A..H
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73, 74, 75, 76, 77, 78, 79, 80, //I..P

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