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// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
// See the LICENSE file in the project root for more information.
// Adapted from spectral-norm C# .NET Core #3 program
// http://benchmarksgame.alioth.debian.org/u64q/program.php?test=spectralnorm&lang=csharpcore&id=3
// aka (as of 2017-09-01) rev 1.1 of https://alioth.debian.org/scm/viewvc.php/benchmarksgame/bench/spectralnorm/spectralnorm.csharp-3.csharp?root=benchmarksgame&view=log
// Best-scoring C# .NET Core version as of 2017-09-01
/* The Computer Language Benchmarks Game
http://benchmarksgame.alioth.debian.org/
contributed by Isaac Gouy
modified by Josh Goldfoot, based on the Java version by The Anh Tran
*/
using System;
using System.Runtime.CompilerServices;
using System.Threading;
using System.Threading.Tasks;
using BenchmarkDotNet.Attributes;
using MicroBenchmarks;
namespace BenchmarksGame
{
[MaxIterationCount(40)] // the default 20 is not enough, the benchmark has multimodal distribution and needs more runs
[BenchmarkCategory(Categories.CoreCLR, Categories.BenchmarksGame)]
public class SpectralNorm_3
{
[Benchmark(Description = nameof(SpectralNorm_3))]
public double RunBench() => Bench(100);
[MethodImpl(MethodImplOptions.NoInlining)]
private static double Bench(int n)
{
double[] u = new double[n];
double[] v = new double[n];
double[] tmp = new double[n];
// create unit vector
for (int i = 0; i < n; i++)
u[i] = 1.0;
int nthread = Environment.ProcessorCount;
int chunk = n / nthread;
var barrier = new Barrier(nthread);
Approximate[] ap = new Approximate[nthread];
for (int i = 0; i < nthread; i++)
{
int r1 = i * chunk;
int r2 = (i < (nthread - 1)) ? r1 + chunk : n;
ap[i] = new Approximate(u, v, tmp, r1, r2, barrier);
}
double vBv = 0, vv = 0;
for (int i = 0; i < nthread; i++)
{
ap[i].t.Wait();
vBv += ap[i].m_vBv;
vv += ap[i].m_vv;
}
return Math.Sqrt(vBv / vv);
}
}
public class Approximate
{
private Barrier barrier;
public Task t;
private double[] _u;
private double[] _v;
private double[] _tmp;
private int range_begin, range_end;
public double m_vBv, m_vv;
public Approximate(double[] u, double[] v, double[] tmp, int rbegin, int rend, Barrier b)
{
m_vBv = 0;
m_vv = 0;
_u = u;
_v = v;
_tmp = tmp;
range_begin = rbegin;
range_end = rend;
barrier = b;
t = Task.Run(() => run());
}
private void run()
{
// 20 steps of the power method
for (int i = 0; i < 10; i++)
{
MultiplyAtAv(_u, _tmp, _v);
MultiplyAtAv(_v, _tmp, _u);
}
for (int i = range_begin; i < range_end; i++)
{
m_vBv += _u[i] * _v[i];
m_vv += _v[i] * _v[i];
}
}
/* return element i,j of infinite matrix A */
private double eval_A(int i, int j)
{
return 1.0 / ((i + j) * (i + j + 1) / 2 + i + 1);
}
/* multiply vector v by matrix A, each thread evaluate its range only */
private void MultiplyAv(double[] v, double[] Av)
{
for (int i = range_begin; i < range_end; i++)
{
double sum = 0;
for (int j = 0; j < v.Length; j++)
sum += eval_A(i, j) * v[j];
Av[i] = sum;
}
}
/* multiply vector v by matrix A transposed */
private void MultiplyAtv(double[] v, double[] Atv)
{
for (int i = range_begin; i < range_end; i++)
{
double sum = 0;
for (int j = 0; j < v.Length; j++)
sum += eval_A(j, i) * v[j];
Atv[i] = sum;
}
}
/* multiply vector v by matrix A and then by matrix A transposed */
private void MultiplyAtAv(double[] v, double[] tmp, double[] AtAv)
{
MultiplyAv(v, tmp);
// all thread must syn at completion
barrier.SignalAndWait();
MultiplyAtv(tmp, AtAv);
// all thread must syn at completion
barrier.SignalAndWait();
}
}
}