using System.Numerics;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;

BenchmarkRunner.Run<ArrayAdd>();

public class ArrayAdd
{
    private static readonly int[] Numbers = Enumerable.Repeat(1, 512).ToArray();

    [Benchmark(Baseline = true)]
    public int GetSumNaive()
    {
        var result = 0;
        for (var index = 0; index < Numbers.Length; index++)
        {
            var i = Numbers[index];
            result += i;
        }

        return result;
    }

    [Benchmark]
    public int SumLINQ() => Numbers.Sum();

    [Benchmark]
    public int SumPLINQ() => Numbers.AsParallel().Sum();


    [Benchmark]
    public int SIMDVectors()
    {
        // This depends on your hardware
        // It basically says on how many entries can we performance this single operation
        // aka how big is "multiple"
        var vectorSize = Vector<int>.Count;
        var accVector = Vector<int>.Zero;

        // We are tiling the original list by the hardware vector size
        for (var i = 0; i <= Numbers.Length - vectorSize; i += vectorSize)
        {
            var v = new Vector<int>(Numbers, i);
            accVector = Vector.Add(accVector, v);
        }

        // Scalar-Product of our vector against the Unit vector is its sum
        var result = Vector.Dot(accVector, Vector<int>.One);
        return result;
    }
}