What is the easiest way to parallelize a task in java?

I would recommend taking a look at ExecutorService.

In particular, something like this:

ExecutorService EXEC = Executors.newCachedThreadPool();List<Callable<Result>> tasks = new ArrayList<Callable<Result>>();for (final Object object: objects) {    Callable<Result> c = new Callable<Result>() {        @Override        public Result call() throws Exception {            return compute(object);        }    };    tasks.add(c);}List<Future<Result>> results = EXEC.invokeAll(tasks);

Note that using newCachedThreadPool could be bad if objects is a big list. A cached thread pool could create a thread per task! You may want to use newFixedThreadPool(n) where n is something reasonable (like the number of cores you have, assuming compute() is CPU bound).

Here's full code that actually runs:

import java.util.ArrayList;import java.util.List;import java.util.Random;import java.util.concurrent.Callable;import java.util.concurrent.ExecutionException;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;import java.util.concurrent.Future;public class ExecutorServiceExample {    private static final Random PRNG = new Random();    private static class Result {        private final int wait;        public Result(int code) {            this.wait = code;        }    }    public static Result compute(Object obj) throws InterruptedException {        int wait = PRNG.nextInt(3000);        Thread.sleep(wait);        return new Result(wait);    }    public static void main(String[] args) throws InterruptedException,        ExecutionException {        List<Object> objects = new ArrayList<Object>();        for (int i = 0; i < 100; i++) {            objects.add(new Object());        }        List<Callable<Result>> tasks = new ArrayList<Callable<Result>>();        for (final Object object : objects) {            Callable<Result> c = new Callable<Result>() {                @Override                public Result call() throws Exception {                    return compute(object);                }            };            tasks.add(c);        }        ExecutorService exec = Executors.newCachedThreadPool();        // some other exectuors you could try to see the different behaviours        // ExecutorService exec = Executors.newFixedThreadPool(3);        // ExecutorService exec = Executors.newSingleThreadExecutor();        try {            long start = System.currentTimeMillis();            List<Future<Result>> results = exec.invokeAll(tasks);            int sum = 0;            for (Future<Result> fr : results) {                sum += fr.get().wait;                System.out.println(String.format("Task waited %d ms",                    fr.get().wait));            }            long elapsed = System.currentTimeMillis() - start;            System.out.println(String.format("Elapsed time: %d ms", elapsed));            System.out.println(String.format("... but compute tasks waited for total of %d ms; speed-up of %.2fx", sum, sum / (elapsed * 1d)));        } finally {            exec.shutdown();        }    }}

With Java8 and later you can use a parallelStream on the collection to achieve this:

List<T> objects = ...;List<Result> result = objects.parallelStream().map(object -> {            return compute(object);        }).collect(Collectors.toList());

Note: the order of the result list may not match the order in the objects list.

Details how to setup the right number of threads are available in this stackoverflow question how-many-threads-are-spawned-in-parallelstream-in-java-8

One can simple create a few thread and get the result.

Thread t = new Mythread(object);if (t.done()) {   // get result   // add result}

EDIT : I think other solutions are cooler.