Due to GIL there is no point to use threads for CPU intensive tasks in CPython. You need either multiprocessing (example) or use C extensions that release GIL during computations e.g., some of numpy functions, example. You could easily write C extensions that use multiple threads in Cython, example.
From the xargs man page: This manual page documents the GNU version of xargs. xargs reads items from the standard input, delimited by blanks (which can be protected with double or single quotes or a backslash) or newlines, and executes the command (default is /bin/echo) one or more times with any initial- arguments followed by items read … Read more
Error 1: AttributeError: Can’t pickle local object ‘SomeClass.some_method..single’ You solved this error yourself by moving the nested target-function single() out to the top-level. Background: Pool needs to pickle (serialize) everything it sends to its worker-processes (IPC). Pickling actually only saves the name of a function and unpickling requires re-importing the function by name. For that … Read more
Using multiple threads on CPython won’t give you better performance for pure-Python code due to the global interpreter lock (GIL). I suggest using the multiprocessing module instead: Note that this won’t work in the interactive interpreter. To avoid the usual FUD around the GIL: There wouldn’t be any advantage to using threads for this example anyway. You want to … Read more
Using multiple threads on CPython won’t give you better performance for pure-Python code due to the global interpreter lock (GIL). I suggest using the multiprocessing module instead: Note that this won’t work in the interactive interpreter. To avoid the usual FUD around the GIL: There wouldn’t be any advantage to using threads for this example anyway. You want to … Read more
Concurrency is when two or more tasks can start, run, and complete in overlapping time periods. It doesn’t necessarily mean they’ll ever both be running at the same instant. For example, multitasking on a single-core machine. Parallelism is when tasks literally run at the same time, e.g., on a multicore processor. Quoting Sun’s Multithreaded Programming Guide: Concurrency: A condition that exists when at least two … Read more
First and foremost, there are ways to debug an MPI application, which should really be your top priority. A general approach for multi-process applications is to pause at the beginning of your application e.g. with a getchar() then attach to each process with a debugger as described here: compile, link and start running your MPI … Read more
In the context of MPI, application buffer (often called user buffer) is the buffer that holds information to be sent or the place where information is to be received. Applications buffers are what one passes to MPI communication calls, e.g. Once MPI_Send is called, a message is constructed and depending on various criteria is either … Read more