Java optimizes parallel computing with Fork and Join

The example of this paper shares the specific code of Java using Fork/Join to optimize parallel computing for your reference. The specific content is as follows

Java code:

package Threads;

import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveAction;

/**
 * Created by Frank
 */
public class RecursiveActionDemo extends RecursiveAction {

  static int[] raw = {19, 3, 0, -1, 57, 24, 65, Integer.MAX_VALUE, 42, 0, 3, 5};
  static int[] sorted = null;
  int[] source;
  int[] dest;
  int length;
  int start;
  final static int THRESHOLD = 4;

  public static void main(String[] args) {
    sorted = new int[raw.length];

    ForkJoinPool pool = new ForkJoinPool();
    pool.invoke(new RecursiveActionDemo(raw, 0, raw.length, sorted));

    System.out.println('[');
    for (int i : sorted) {
      System.out.println(i + ",");
    }
    System.out.println(']');
  }

  public RecursiveActionDemo(int[] source, int start, int length, int[] dest) {
    this.source = source;
    this.dest = dest;
    this.length = length;
    this.start = start;
  }

  @Override
  protected void compute() {
    System.out.println("ForkJoinDemo.compute()");
    if (length < THRESHOLD) {  //  Direct calculation 
      for (int i = start; i < start + length; i++) {
        dest[i] = source[i] * source[i];
      }
    } else { //  Divide and conquer 
      int split = length / 2;
      /**
       * invokeAll Repeated calls fork and join Until it's done. 
       */
      invokeAll(new RecursiveActionDemo(source, start, split, dest), new RecursiveActionDemo(source, start + split, length - split, dest));
    }
  }
}