There actually is a trick how to execute a parallel operation in a specific fork-join pool. If you execute it as a task in a fork-join pool, it stays there and does not use the common one. final int parallelism = 4; ForkJoinPool forkJoinPool = null; try { forkJoinPool = new ForkJoinPool(parallelism); final List<Integer> primes … Read more
What is the difference between concurrency and parallelism?
First example: No multiple threads. Both execute in single (existing) thread. No thread creation. R1 r1 = new R1(); R2 r2 = new R2(); r1 and r2 are just two different objects of classes that implement the Runnable interface and thus implement the run() method. When you call r1.run() you are executing it in the … Read more
You can definitely do this in the latest versions of async for .NET, using .NET 4.5 Beta. The previous post from ‘usr’ points to a good article written by Stephen Toub, but the less announced news is that the async semaphore actually made it into the Beta release of .NET 4.5 If you look at … Read more
That’s a good question. I’d love to say “yes”. I can’t. JavaScript is usually considered to have a single thread of execution visible to scripts(*), so that when your inline script, event listener or timeout is entered, you remain completely in control until you return from the end of your block or function. (*: ignoring … Read more
What’s likely happening is that SignalData is indirectly changing the subscribers dictionary under the hood during the loop and leading to that message. You can verify this by changing foreach(Subscriber s in subscribers.Values) To foreach(Subscriber s in subscribers.Values.ToList()) If I’m right, the problem will disappear. Calling subscribers.Values.ToList() copies the values of subscribers.Values to a separate … Read more
Short & quick answer: volatile is (nearly) useless for platform-agnostic, multithreaded application programming. It does not provide any synchronization, it does not create memory fences, nor does it ensure the order of execution of operations. It does not make operations atomic. It does not make your code magically thread safe. volatile may be the single-most … Read more
A race condition occurs when two or more threads can access shared data and they try to change it at the same time. Because the thread scheduling algorithm can swap between threads at any time, you don’t know the order in which the threads will attempt to access the shared data. Therefore, the result of … Read more
Since this question was asked in 2010, there has been real simplification in how to do simple multithreading with Python with map and pool. The code below comes from an article/blog post that you should definitely check out (no affiliation) – Parallelism in one line: A Better Model for Day to Day Threading Tasks. I’ll … Read more