如何使用ForkJoinPool在Java中使用多个内核？

Question

因此，我试图了解ForkJoinPool的工作方式。我正在尝试使用大约200万个元素的大数组来获得更好的性能，然后添加它们的倒数。我了解ForkJoinPool.commpnPool（）。invoke（task）;调用compute（），如果任务不小，它将把任务分叉到两个任务中，然后进行计算，然后将它们加入。到目前为止，我们正在使用两个核心。

但是，如果我想在多个内核上执行此操作，该如何实现，并获得比通常的单线程运行好4倍的性能？下面是我的默认ForkJoinPool（）代码：

@Override
        protected void compute() {
            // TODO
            if (endIndexExclusive - startIndexInclusive <= seq_count) {
                for (int i = startIndexInclusive; i < endIndexExclusive; i++)
                    value += 1 / input[i];
            } else {

                ReciprocalArraySumTask left = new ReciprocalArraySumTask(startIndexInclusive,
                        (endIndexExclusive + startIndexInclusive) / 2, input);
                ReciprocalArraySumTask right = new ReciprocalArraySumTask((endIndexExclusive + startIndexInclusive) / 2,
                        endIndexExclusive, input);
                left.fork();
                right.compute();
                left.join();
                value = left.value + right.value;
            }
        }
    }


protected static double parArraySum(final double[] input) {
        assert input.length % 2 == 0;

        double sum = 0;

        // Compute sum of reciprocals of array elements
        ReciprocalArraySumTask task = new ReciprocalArraySumTask(0, input.length, input);
        ForkJoinPool.commonPool().invoke(task);
        return task.getValue();
    }

//Here I am trying to achieve with 4 cores
protected static double parManyTaskArraySum(final double[] input,
                                                final int numTasks) {
        double sum = 0;
        System.out.println("Total tasks = " + numTasks);
        System.setProperty("java.util.concurrent.ForkJoinPool.common.parallelism", String.valueOf(numTasks));
        // Compute sum of reciprocals of array elements
        int chunkSize = ReciprocalArraySum.getChunkSize(numTasks, input.length);
        System.out.println("Chunk size = " + chunkSize);
        ReciprocalArraySumTask task = new ReciprocalArraySumTask(0, input.length, input);
        ForkJoinPool pool = new ForkJoinPool();
//        pool.
        ForkJoinPool.commonPool().invoke(task);
        return task.getValue();
    }

Answer 1

您想使用4个核心，但是您要提供的工作将仅需要两个核心。在下面的示例中，getChunkStartInclusive和getChunkEndExclusive方法给出了每个块的开始和结束索引的范围。我相信以下代码可以解决您的问题，并为您提供一些实现想法。

protected static double parManyTaskArraySum(final double[] input,
        final int numTasks) {
    double sum = 0;
    System.setProperty("java.util.concurrent.ForkJoinPool.common.parallelism", String.valueOf(numTasks));
    List<ReciprocalArraySumTask> ts = new ArrayList<ReciprocalArraySumTask>(numTasks);

    int i;
    for (i = 0; i < numTasks - 1 ; i++) {
        ts.add(new ReciprocalArraySumTask(getChunkStartInclusive(i,numTasks,input.length),getChunkEndExclusive(i,numTasks,input.length),input));
        ts.get(i).fork();
    }
    ts.add( new ReciprocalArraySumTask(getChunkStartInclusive(i, numTasks, input.length), getChunkEndExclusive(i, numTasks, input.length), input));
    ts.get(i).compute();

    for (int j = 0; j < numTasks - 1; j++) {
        ts.get(j).join();
    }

    for (int j = 0; j < numTasks; j++) {
        sum += ts.get(j).getValue();
    }
    return sum;
}