Omgo's Blog

October 24, 2010

parallel quicksort with java fork join framework JSR 166y

Filed under: Core Java — aswin @ 9:39 pm
Fork Join (jsr 166y) framework is slated for Java 7 and is absolutely cool and is no surprise coming from Doug Lea.  I had to try something out with it since the packages compiled on java 6 is also availalbe. 

I tried parallizing the quicksort algorithm using this and looks like it compiles and even produces right results!!!  The important part here is the use of Phaser, a resettable CountdownLatch if you would.  So basically you create a Phaser and pass it along to the root (first) RecursiveAction object.
Each of the RecursiveAction object (in this example an instance of ParallelQuckSort) increments the Phaser counter by using the regiter() method and when they are done their work (sorting or spawning children to do
that) they "arrive" and "unregister" at the Phaser bringing down the phaser counter by one. When all the RecursiveAction (spawned by the recursion) are done, the root one waiting on the Phaser lock would resume and return to the client, at which
point the array would have been sorted. 

Any way here it is the source for what I have done, any comments and suggestions are welcome.
package test.aswin.concurrency.forkjoin;

import jsr166y.*;
import jsr166y.Phaser;

import java.util.Arrays;

 * Example of using JSR 166 Y for a simple parallel quick sort.
public class ParallelQuickSort extends RecursiveAction {
    Phaser phaser;
    int[] arr = null;
    int left;
    int right;

    ParallelQuickSort(Phaser phaser, int[] arr) {
        this(phaser, arr, 0, arr.length - 1);

    ParallelQuickSort(Phaser phaser, int[] arr, int left, int right) {
        this.phaser = phaser;
        this.arr = arr;
        this.left = left;
        this.right = right;
        phaser.register();  //important

    private ParallelQuickSort leftSorter(int pivotI) {
        return new ParallelQuickSort(phaser, arr, left, --pivotI);

    private ParallelQuickSort rightSorter(int pivotI) {
        return new ParallelQuickSort(phaser, arr, pivotI, right);

    private void recurSort(int leftI, int rightI) {
        if (rightI - leftI > 7) {
            int pIdx = partition(leftI, rightI, getPivot(arr, leftI, rightI));
            recurSort(leftI, pIdx - 1);
            recurSort(pIdx, rightI);
        } else if (rightI - leftI > 0) {
            insertionSort(leftI, rightI);

    protected void compute() {
        if (right - left > 1000) {   // if more than 1000 (totally arbitrary number i chose) try doing it parallelly
            int pIdx = partition(left, right, getPivot(arr, left, right));

        } else if (right - left > 7) {  // less than 1000 sort recursively in this thread
            recurSort(left, right);

        } else if (right - left > 0) {  //if less than 7 try simple insertion sort
            insertionSort(left, right);

        if (isRoot()) { //if this instance is the root one (the one that started the sort process), wait for others
                        // to complete.
        } else {  // all not root one just arrive and de register not waiting for others.

    /** Patition the array segment based on the pivot   **/
    private int partition(int startI, int endI, int pivot) {
        for (int si = startI - 1, ei = endI + 1; ; ) {
            for (; arr[++si] < pivot;) ;
            for (; ei > startI && arr[--ei] > pivot ; ) ;
            if (si >= ei) {
                return si;
            swap(si, ei);

    private void insertionSort(int leftI, int rightI) {
        for (int i = leftI; i < rightI + 1; i++)
            for (int j = i; j > leftI && arr[j - 1] > arr[j]; j--)
                swap(j, j - 1);


    private void swap(int startI, int endI) {
        int temp = arr[startI];
        arr[startI] = arr[endI];
        arr[endI] = temp;

     * Check to see if this instance is the root, i.e the first one used to sort the array.
     * @return
    private boolean isRoot() {
        return arr.length == (right - left) + 1;

     * copied from java.util.Arrays
    private int getPivot(int[] arr, int startI, int endI) {
        int len = (endI - startI) + 1;
        // Choose a partition element, v
        int m = startI + (len >> 1);       // Small arrays, middle element
        if (len > 7) {
            int l = startI;
            int n = startI + len - 1;
            if (len > 40) {        // Big arrays, pseudomedian of 9
                int s = len / 8;
                l = med3(arr, l, l + s, l + 2 * s);
                m = med3(arr, m - s, m, m + s);
                n = med3(arr, n - 2 * s, n - s, n);
            m = med3(arr, l, m, n); // Mid-size, med of 3
        int v = arr[m];
        return v;

     * copied from java.util.Arrays
    private static int med3(int x[], int a, int b, int c) {
        return (x[a] < x[b] ?
                (x[b] < x[c] ? b : x[a] < x[c] ? c : a) :
                (x[b] > x[c] ? b : x[a] > x[c] ? c : a));

    public static void main(String[] args) throws InterruptedException {
        int[] arr = ArrayUtils.generateRandom(1000000);
        ForkJoinPool pool = new ForkJoinPool();

        for (int i = 0; i < 10; i++) {
            System.out.println("Sarting " + i);
            int[] arrclone1 = arr.clone();
            int[] arrclone2 = arr.clone();

            long l = System.nanoTime();
            System.out.printf("Times for seq %,8d%n", (System.nanoTime() - l));

/*          // sorted (asc and desc) are faster than unsorted one, while trying parallel sort
            for (int left=0,right=arrclone1.length-1; left<right; left++, right--) {
                // exchange the first and last
                int temp = arrclone1[left]; arrclone1[left]  = arrclone1[right]; arrclone1[right] = temp;

            l = System.nanoTime();
            Phaser phaser = new Phaser();
            pool.invoke(new ParallelQuickSort(phaser, arrclone2));
            System.out.printf("Times %,8d%n", (System.nanoTime() - l));
            System.out.println("Is sorted :>" + ArrayUtils.isSorted(arrclone2, true));
One thing I tried and failed was to parallelize the partition operation which is single threaded in this example. The thing I wrote for that worked, but had horrible performance so I am not including it here. What I
did basically was to have two threads parallely swapping even and odd indexed items respectively. I think processor locality of the data and synchronizing the elements across cpu cache may be the issue, but I am
investigating it further and with help of the experts out there, may find out why it is perforing bad. If anyone wants to help me out with this, please let me know :)


October 18, 2010

scala simple number guess application using case pattern guards

Filed under: scala — aswin @ 11:15 pm

There are millions of examples out there on all this, but here is a little program that shows the case pattern guards and function literals

class NumGuessCase(guess: Int) {

  def guessNum(read: () => Int, disp: String => Unit): Unit = _guessNum(read, disp)

  private def _guessNum(read: () => Int, disp: String => Unit, times: Int = 0): Unit = {
    disp("Please enter guess :> ")    
    read() match {
      case `guess` => disp("You guessed right in " + (times+1)); 
      case a if a > guess => disp ("You guessed too high");
                _guessNum(read, disp, times+1)
      case a if a < guess => disp ("You guessed too low");
                _guessNum(read, disp, times+1)


The guessNum method takes two arguments, read, and disp. Parameter “read” is a function which when invoked should return the user’s guess. “disp” (display) represents a function which is responsible for the output of the messages by the guessNum function. So the client of the guessNum can pass in as arguments a function that accepts user input and another one that displays the messages back to user and in our case we just use system console for this interaction (see the NumGuesCase companion object shown below).

The part I was testing out was the case pattern guards, the second case statement would match only if the pattern guard (“a > guess”) returns true. We could have used a default catch all pattern (“_”) as the last case statement. The first statement uses a variable pattern and is why you have to use the ` (backquote) symbol.

object NumGuesCase extends Application {
  new NumGuessCase(new java.util.Random().nextInt(100)).guessNum(readInt,println)

This is how you would use the guessNum method, just pass in a readInt and println method. Scala compiler would capture these methods as Fuction objects and pass it to our guessNum method and since they both Type check with the Function signature it works.

If anyone is trying this out , please be aware of the missing main method bug (pre 2.8.0) as detailed out here

October 17, 2010

Something really big is cooking at JBOSS

Filed under: rumour — aswin @ 1:27 am

Its been quite some time since I have seen any activity from Gavin King (Hibernate, JBOSS). He has blogged that he is working on something really big, important and cool. I have a feeling that they are collaborating with some company on this and my guess is JREBEL. Lets see if its true.

Blog at