parallelintSumBenchmark

package org.sample;

import static java.util.Arrays.setAll;
import static java.util.concurrent.TimeUnit.MILLISECONDS;

import java.util.Arrays;
import java.util.concurrent.TimeUnit;

import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.GenerateMicroBenchmark;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.Mode;
import org.openjdk.jmh.annotations.OperationsPerInvocation;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import org.openjdk.jmh.annotations.Scope;
import org.openjdk.jmh.annotations.Setup;
import org.openjdk.jmh.annotations.State;
import org.openjdk.jmh.annotations.Threads;
import org.openjdk.jmh.annotations.Warmup;

@OutputTimeUnit(TimeUnit.MILLISECONDS)
@BenchmarkMode(Mode.AverageTime)
@OperationsPerInvocation(1)
@Warmup(iterations = 10, time = 500, timeUnit=MILLISECONDS)
@Measurement(iterations = 20, time = 500, timeUnit=MILLISECONDS)
@State(Scope.Thread)
@Threads(1)
@Fork(1)
public class Measure
{
  static final int[] ds = new int[1<<20];
  static { setAll(ds, i->(int)(Math.random()*(1<<7))); }

  int multiplier;
  @Setup public void x() { multiplier = (int)(Math.random()*10); }

  @GenerateMicroBenchmark public double sequential() {
    return Arrays.stream(ds).map(d -> multiplier*5*d).sum();
  }
  @GenerateMicroBenchmark public double parallel() {
    return Arrays.stream(ds).parallel().map(d -> multiplier*5*d).sum();
  }
  @GenerateMicroBenchmark public double unorderedParallel() {
    return Arrays.stream(ds).unordered().parallel().map(d -> multiplier*5*d).sum();
  }
}