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Concepts

This library has 3 layers:

1. ScalarOp
   provides generalized and backward-compatibility-enhanced operators and Math/MathF functions.

2. VectorOp
   provides SIMD parallelized APIs which are corresponding with each method in ScalarOp and Vector<T> specific operations.

3. Vectorization
   provides span based sequential operation. Their APIs are declared as strategy pattern, you can select simple loop or SIMD vectorized operation.

Usage

Generalized System.Numerics.Vector<T> calculations

internal class GeneralizeMathFunc : IExample { public void Run(TextWriter logger) { var x = new Vector<double>([0.0, 1.0, 2.0, 3.0]); var sin_x_pi = VectorOp.Sin(VectorOp.Multiply(x, VectorOp.Const<double>.PI)); logger.WriteLine(sin_x_pi); } }

Simply vectirozation

internal class VoctorizeSimply : IExample { public void Run(TextWriter logger) { var x = Enumerable.Range(0, 256).Select(i => (double)i).ToArray(); var tmp = new double[x.Length]; var ans = new double[x.Length]; Vectorization.SIMD.Multiply<double>(x, Math.PI, tmp); Vectorization.SIMD.Sin<double>(tmp, ans); logger.WriteLine(string.Join(", ", ans)); } }

Vectorization for any function

internal class CalculateVectorized : IExample { public void Run(TextWriter logger) { var x = Enumerable.Range(0, 256).Select(i => (float)i).ToArray(); var y = Enumerable.Range(0, 256).Select(i => (float)i).ToArray(); var z = Enumerable.Range(0, 256).Select(i => (float)i).ToArray(); var ans = new float[256]; Vectorization.SIMD.Calculate<float, Formula>(x, y, z, ans); logger.WriteLine(string.Join(", ", ans)); } } file readonly struct Formula : IVectorFormula3<float> { public float Calculate(float x1, float x2, float x3) => x1 * x1 + x2 * x2 + x3 * x3; public Vector<float> Calculate(Vector<float> x1, Vector<float> x2, Vector<float> x3) => x1 * x1 + x2 * x2 + x3 * x3; }

Vectorization for any function with interceptor (EXPERIMENTAL)

Required to reference SmartVectorDotNet.Generators

internal class CalculateVectorizedInterceptor : IExample { public void Run(TextWriter logger) { int[] x = [.. Enumerable.Range(0, 1000).Select(i => (int)i)]; var y = new int[x.Length]; var z = new int[x.Length]; var vectorization = new InterceptVectorization(logger); vectorization.Calculate( static x => x * x, x.AsSpan(), y.AsSpan() ); vectorization.Calculate( static (x, y) => ScalarOp.Add(x, y), x.AsSpan(), y.AsSpan(), z.AsSpan() ); logger.WriteLine(string.Join(", ", z.Take(10))); } } file class InterceptVectorization(TextWriter logger) : SimdVectorization { protected override void CalculateCore<T, TFormula>(TFormula formula, ReadOnlySpan<T> x1, Span<T> ans) { logger.WriteLine("Intercepterd by CalculateCore`2(formula, x1, ans)"); base.CalculateCore(formula, x1, ans); } protected override void CalculateCore<T, TFormula>(TFormula formula, ReadOnlySpan<T> x1, ReadOnlySpan<T> x2, Span<T> ans) { logger.WriteLine("Intercepterd by CalculateCore`2(formula, x1, x2, ans)"); base.CalculateCore(formula, x1, x2, ans); } }

Release notes

v0.1.0

• first releases

v0.1.1

• supports custom formula vectorization
• adds ParallelVectorization to parallelize vector operation