java - ExecutorService 多线程性能低

Question

我正在尝试执行一个简单的计算(它调用 Math.random() 10000000 次)。令人惊讶的是，以简单的方法运行它比使用 ExecutorService 执行得更快。

我在 ExecutorService's surprising performance break-even point --- rules of thumb? 阅读了另一个主题并尝试通过使用批处理执行 Callable 来跟踪答案，但性能仍然很差

如何根据我当前的代码提高性能？

import java.util.*;
import java.util.concurrent.*;

public class MainTest {
    public static void main(String[]args) throws Exception {
        new MainTest().start();;
    }

    final List<Worker> workermulti = new ArrayList<Worker>();
    final List<Worker> workersingle = new ArrayList<Worker>();
    final int count=10000000;

    public void start() throws Exception {
        int n=2;

        workersingle.add(new Worker(1));
        for (int i=0;i<n;i++) {
            // worker will only do count/n job
            workermulti.add(new Worker(n));
        }

        ExecutorService serviceSingle = Executors.newSingleThreadExecutor();
        ExecutorService serviceMulti = Executors.newFixedThreadPool(n);
        long s,e;
        int tests=10;
        List<Long> simple = new ArrayList<Long>();
        List<Long> single = new ArrayList<Long>();
        List<Long> multi = new ArrayList<Long>();

        for (int i=0;i<tests;i++) {
            // simple
            s = System.currentTimeMillis();
            simple();
            e = System.currentTimeMillis();
            simple.add(e-s);

            // single thread
            s = System.currentTimeMillis();
               serviceSingle.invokeAll(workersingle); // single thread
            e = System.currentTimeMillis();
            single.add(e-s);

            // multi thread
            s = System.currentTimeMillis();
               serviceMulti.invokeAll(workermulti);
            e = System.currentTimeMillis();
            multi.add(e-s);
        }
        long avgSimple=sum(simple)/tests;
        long avgSingle=sum(single)/tests;
        long avgMulti=sum(multi)/tests;
        System.out.println("Average simple: "+avgSimple+" ms");
        System.out.println("Average single thread: "+avgSingle+" ms");
        System.out.println("Average multi thread: "+avgMulti+" ms");

        serviceSingle.shutdown();
        serviceMulti.shutdown();
    }

    long sum(List<Long> list) {
        long sum=0;
        for (long l : list) {
            sum+=l;
        }
        return sum;
    }

    private void simple() {
        for (int i=0;i<count;i++){
            Math.random();
        }
    }

    class Worker implements Callable<Void> {
        int n;

        public Worker(int n) {
            this.n=n;
        }

        @Override
        public Void call() throws Exception {
            // divide count with n to perform batch execution
            for (int i=0;i<(count/n);i++) {
                Math.random();
            }
            return null;
        }
    }
}

这段代码的输出

Average simple: 920 ms
Average single thread: 1034 ms
Average multi thread: 1393 ms

编辑:由于 Math.random() 是同步方法，性能受到影响。在为每个线程使用新的 Random 对象更改 Math.random() 后，性能得到改善

新代码的输出(在将每个线程的 Math.random() 替换为 Random 之后)

Average simple: 928 ms
Average single thread: 1046 ms
Average multi thread: 642 ms

Answer 1

Math.random()是同步的。 synchronized 的全部意义在于减慢速度，以免它们发生冲突。使用不同步的东西和/或给每个线程自己的对象来处理，比如一个新的 Random .