threadpool

I have one thread in the thread-pool servicing blocking request. def sync = Action { import Contexts.blockingPool Future { Thread.sleep(100) } Ok("Done") } In Contexts.blockingPool is configured as: custom-pool { fork-join-executor { parallelism-min = 1 parallelism-max = 1 } } In theory, if above request receives 100 simultaneous requests, the expected behaviour should be: 1 request should sleep(100) and rest of 99 requests should be rejected (or queued until timeout?). However I observed that extra worker threads are created to service rest of requests. I also observed that latency increases

[EDIT: thanks to MSalters answer and Raymond Chen's answer to InterlockedIncrement vs EnterCriticalSection/counter++/LeaveCriticalSection , the problem is solved and the code below is working properly. This should provide an interesting simple example of Thread Pool use in Windows] I don't manage to find a simple example of the following task. My program, for example, needs to increment the values in a huge std::vector by one, so I want to do that in parallel. It needs to do that a bunch of times across the lifetime of the program. I know how to do that using CreateThread at each call of the

I have this application that will recurse all folders in a given directory and look for PDF. If a PDF file is found, the application will count its pages using ITextSharp. I did this by using a thread to recursively scan all the folders for pdf, then if then PDF is found, this will be queued to the thread pool. The code looks like this: //spawn a thread to handle the processing of pdf on each folder. var th = new Thread(() => { pdfDirectories = Directory.GetDirectories(pdfPath); processDir(pdfDirectories); }); th.Start(); private void processDir(string[] dirs) { foreach (var dir in dirs) {

I've been tasked with taking an existing single threaded monte carlo simulation and optimising it. This is a c# console app, no db access it loads data once from a csv file and writes it out at the end, so it's pretty much just CPU bound , also only uses about 50mb of memory. I've run it through Jetbrains dotTrace profiler. Of total execution time about 30% is generating uniform random numbers, 24% translating uniform random numbers to normally distributed random numbers. The basic algorithm is a whole lot of nested for loops , with random number calls and matrix multiplication at the centre,

I am using cached thread pool ExecutorService to run some asynchronous background tasks. I've provided my ThreadFactory that hands out threads to the ExecutorService (whenever it needs them). My understanding of the cached thread pool is that after the thread is sitting idle for 60 seconds it is termniated by the ExecutorService. I want to perform some state cleanup when my thread is about to be terminated. What is the best way to achieve this? The ExecutorService does not readily provide hooks into the thread's lifecycle. I don't want to shutdown my ExecutorService - useful for running tasks

I'm trying to debug a custom thread pool implementation that has rarely deadlocks. So I cannot use a debugger like gdb because I have click like 100 times "launch" debugger before having a deadlock. Currently, I'm running the threadpool test in an infinite loop in a shell script, but that means I cannot see variables and so on. I'm trying to std::cout data, but that slow down the thread and reduce the risk of deadlocks meaning that I can wait like 1hour with my infinite before getting messages. Then I don't get the error, and I need more messages, which means waiting one more hour... How to