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POIs there any "threshold" justifying multithreaded computation?
 

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  1. POIs there any "threshold" justifying multithreaded computation?
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    <p>So basically I needed to optimize this piece of code today. It tries to find the longest sequence produced by some function for the first million starting numbers:</p> <pre><code>public static void main(String[] args) { int mostLen = 0; int mostInt = 0; long currTime = System.currentTimeMillis(); for(int j=2; j&lt;=1000000; j++) { long i = j; int len = 0; while((i=next(i)) != 1) { len++; } if(len &gt; mostLen) { mostLen = len; mostInt = j; } } System.out.println(System.currentTimeMillis() - currTime); System.out.println("Most len is " + mostLen + " for " + mostInt); } static long next(long i) { if(i%2==0) { return i/2; } else { return i*3+1; } } </code></pre> <p>My mistake was to try to introduce multithreading:</p> <pre><code>void doSearch() throws ExecutionException, InterruptedException { final int numProc = Runtime.getRuntime().availableProcessors(); System.out.println("numProc = " + numProc); ExecutorService executor = Executors.newFixedThreadPool(numProc); long currTime = System.currentTimeMillis(); List&lt;Future&lt;ValueBean&gt;&gt; list = new ArrayList&lt;Future&lt;ValueBean&gt;&gt;(); for (int j = 2; j &lt;= 1000000; j++) { MyCallable&lt;ValueBean&gt; worker = new MyCallable&lt;ValueBean&gt;(); worker.setBean(new ValueBean(j, 0)); Future&lt;ValueBean&gt; f = executor.submit(worker); list.add(f); } System.out.println(System.currentTimeMillis() - currTime); int mostLen = 0; int mostInt = 0; for (Future&lt;ValueBean&gt; f : list) { final int len = f.get().getLen(); if (len &gt; mostLen) { mostLen = len; mostInt = f.get().getNum(); } } executor.shutdown(); System.out.println(System.currentTimeMillis() - currTime); System.out.println("Most len is " + mostLen + " for " + mostInt); } public class MyCallable&lt;T&gt; implements Callable&lt;ValueBean&gt; { public ValueBean bean; public void setBean(ValueBean bean) { this.bean = bean; } public ValueBean call() throws Exception { long i = bean.getNum(); int len = 0; while ((i = next(i)) != 1) { len++; } return new ValueBean(bean.getNum(), len); } } public class ValueBean { int num; int len; public ValueBean(int num, int len) { this.num = num; this.len = len; } public int getNum() { return num; } public int getLen() { return len; } } long next(long i) { if (i % 2 == 0) { return i / 2; } else { return i * 3 + 1; } } </code></pre> <p>Unfortunately, the multithreaded version worked 5 times slower than the single-threaded on 4 processors (cores).</p> <p>Then I tried a bit more crude approach:</p> <pre><code>static int mostLen = 0; static int mostInt = 0; synchronized static void updateIfMore(int len, int intgr) { if (len &gt; mostLen) { mostLen = len; mostInt = intgr; } } public static void main(String[] args) throws InterruptedException { long currTime = System.currentTimeMillis(); final int numProc = Runtime.getRuntime().availableProcessors(); System.out.println("numProc = " + numProc); ExecutorService executor = Executors.newFixedThreadPool(numProc); for (int i = 2; i &lt;= 1000000; i++) { final int j = i; executor.execute(new Runnable() { public void run() { long l = j; int len = 0; while ((l = next(l)) != 1) { len++; } updateIfMore(len, j); } }); } executor.shutdown(); executor.awaitTermination(30, TimeUnit.SECONDS); System.out.println(System.currentTimeMillis() - currTime); System.out.println("Most len is " + mostLen + " for " + mostInt); } static long next(long i) { if (i % 2 == 0) { return i / 2; } else { return i * 3 + 1; } } </code></pre> <p>and it worked much faster, but still it was slower than the single thread approach.</p> <p>I hope it's not because I screwed up the way I'm doing multithreading, but rather this particular calculation/algorithm is not a good fit for parallel computation. If I change calculation to make it more processor intensive by replacing method <code>next</code> with:</p> <pre><code>long next(long i) { Random r = new Random(); for(int j=0; j&lt;10; j++) { r.nextLong(); } if (i % 2 == 0) { return i / 2; } else { return i * 3 + 1; } } </code></pre> <p>both multithreaded versions start to execute more than twice as fast than the singlethreaded version on a 4 core machine.</p> <p>So clearly there must be some threshold that you can use to determine if it is worth to introduce multithreading and my question is: </p> <p><em>What is the basic rule that would help decide if a given calculation is intensive enough to be optimized by running it in parallel (without spending effort to actually implement it?)</em></p>
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    1. USOleg Mikheev
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    1. COThis is only tangentially related to the question, but the algorithm in question is related to the [Collatz conjecture](http://en.wikipedia.org/wiki/Collatz_conjecture). It's more famous in geekdom thanks to [this](http://xkcd.com/710/) and [this](http://store.xkcd.com/xkcd/#CollatzConjecture).
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      1. USMichael McGowan
    2. COI *highly* recommend the book [Java Concurrency in Practice](http://www.amazon.com/Java-Concurrency-Practice-Brian-Goetz/dp/0321349601) by Brian Goetz.
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