QuanTAlib/lib/core/simd/SimdExtensions.Notebook.dib

#!meta

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#!csharp

// Reference the library
#r "..\..\bin\QuanTAlib.dll"

using System;
using System.Linq;
using System.Numerics;
using QuanTAlib;

// 1. Check Hardware Support
Console.WriteLine($"SIMD Hardware Acceleration: {Vector.IsHardwareAccelerated}");
Console.WriteLine($"Vector<double> Count: {Vector<double>.Count}");

#!csharp

// 2. Basic Operations
// Demonstrate Sum, Min, Max, Average using SIMD extensions

// Define data locally in this cell
double[] data = new double[1000];
for (int i = 0; i < data.Length; i++) data[i] = i;

// We use explicit static method calls with .AsSpan() to ensure correct overload resolution
// and avoid creating top-level ReadOnlySpan variables (which causes CS8345).

double sum = SimdExtensions.SumSIMD(data.AsSpan());
double minVal = SimdExtensions.MinSIMD(data.AsSpan());
double maxVal = SimdExtensions.MaxSIMD(data.AsSpan());
double avg = SimdExtensions.AverageSIMD(data.AsSpan());

Console.WriteLine($"Sum: {sum}");
Console.WriteLine($"Min: {minVal}");
Console.WriteLine($"Max: {maxVal}");
Console.WriteLine($"Average: {avg}");

#!csharp

// 3. Advanced Statistics

double[] dataStats = new double[1000];
for (int i = 0; i < dataStats.Length; i++) dataStats[i] = i;

double variance = SimdExtensions.VarianceSIMD(dataStats.AsSpan());
double stdDev = SimdExtensions.StdDevSIMD(dataStats.AsSpan());

Console.WriteLine($"Variance: {variance:F4}");
Console.WriteLine($"Standard Deviation: {stdDev:F4}");

#!csharp

// 4. Combined Operations

double[] dataComb = new double[1000];
for (int i = 0; i < dataComb.Length; i++) dataComb[i] = i;

var (min, max) = SimdExtensions.MinMaxSIMD(dataComb.AsSpan());
Console.WriteLine($"Min: {min}, Max: {max}");

#!csharp

// 5. Performance Comparison (Simple Benchmark)

int size = 1_000_000;
double[] largeData = new double[size];
Random rnd = new Random(42);
for (int i = 0; i < size; i++) largeData[i] = rnd.NextDouble();

// Warmup
SimdExtensions.SumSIMD(largeData.AsSpan());

// Measure SIMD
long start = DateTime.UtcNow.Ticks;
double sumSimd = SimdExtensions.SumSIMD(largeData.AsSpan());
long end = DateTime.UtcNow.Ticks;
double simdTime = (end - start) / 10000.0; // ms

// Measure Scalar (LINQ Sum as proxy for scalar loop)
start = DateTime.UtcNow.Ticks;
double sumScalar = largeData.Sum();
end = DateTime.UtcNow.Ticks;
double scalarTime = (end - start) / 10000.0; // ms

Console.WriteLine($"Array Size: {size:N0}");
Console.WriteLine($"SIMD Time: {simdTime:F4} ms");
Console.WriteLine($"Scalar Time: {scalarTime:F4} ms");
Console.WriteLine($"Speedup: {scalarTime / simdTime:F2}x");