问题描述
我目前有一些问题需要理解,为什么在某些情况下Java中的并行化似乎效率低下.在以下代码中,我构建了4个使用ThreadPool执行的相同任务.
I currently have some problems to understand why in some cases, parallelization in Java seems infficient. In the following code, I build 4 identical tasks that are executed using a ThreadPool.
在我的Core i5(2核,4线程)上,如果将工作程序数设置为1,则计算机大约需要5700毫秒,并使用25%的处理器.如果将工作程序数设置为4,则可以观察到100%的CPU使用率,但是...计算时间是相同的:5700ms,而我希望它可以减少4倍.
On my Core i5 (2 core, 4 thread), if I set the number of workers to 1, the computer needs around 5700ms and use 25% of the processor.If I set the number of workers to 4, then I observe 100% of CPU usage but... the time of computation is the same: 5700ms, while I expect it to be 4 times lower.
为什么?正常吗?
(当然,我的实际任务更加复杂,但是该示例似乎可以重现该问题).预先感谢您的回答.
(Of course my real task is more complicated, but the example seems to reproduce the problem). Thank you by advance for your answers.
这是代码:
public class Test {
public static void main(String[] args) {
int nb_workers=1;
ExecutorService executor=Executors.newFixedThreadPool(nb_workers);
long tic=System.currentTimeMillis();
for(int i=0; i<4;i++){
WorkerTest wt=new WorkerTest();
executor.execute(wt);
}
executor.shutdown();
try {
executor.awaitTermination(1000, TimeUnit.SECONDS);
} catch (InterruptedException e) {e.printStackTrace();}
System.out.println(System.currentTimeMillis()-tic);
}
public static class WorkerTest implements Runnable {
@Override
public void run() {
double[] array=new double[10000000];
for (int i=0;i<array.length;i++){
array[i]=Math.tanh(Math.random());
}
}
}
}
推荐答案
提示是您正在调用Math.random
,它使用Random
的单个全局实例.因此,您的所有4个线程都在争用一种资源.
The clue is that you are calling Math.random
which uses a single global instance of Random
. So, all your 4 threads compete for the one resource.
使用线程本地Random
对象将使您的执行真正并行:
Using a thread local Random
object will make your execution really parallel:
Random random = new Random();
double[] array = new double[10000000];
for (int i = 0; i < array.length; i++) {
array[i] = Math.tanh(random.nextDouble());
}
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