multiprocessing

问题 I've written a multitprocess application in VC++ and tried to execute it with command line arguments with the system command from MATLAB. It runs, but only on one core --- any suggestions? Update :In fact, it doesn't even see the second core. I used OpenMP and used omp_get_max_threads() and omp_get_thread_num() to check and omp_get_max_threads() seems to be 1 when I execute the application from MATLAB but it's 2 (as is expected) if I run it from the command window. Question :My task manager

问题 How do I pass a dictionary to a function with Python's Multiprocessing? The Documentation: https://docs.python.org/3.4/library/multiprocessing.html#reference says to pass a dictionary, but I keep getting TypeError: fp() got multiple values for argument 'what' Here's the code: from multiprocessing import Pool, Process, Manager def fp(name, numList=None, what='no'): print ('hello %s %s'% (name, what)) numList.append(name+'44') if __name__ == '__main__': manager = Manager() numList = manager

问题 In python2.7, multiprocessing.Queue throws a broken error when initialized from inside a function. I am providing a minimal example that reproduces the problem. #!/usr/bin/python # -*- coding: utf-8 -*- import multiprocessing def main(): q = multiprocessing.Queue() for i in range(10): q.put(i) if __name__ == "__main__": main() throws the below broken pipe error Traceback (most recent call last): File "/usr/lib64/python2.7/multiprocessing/queues.py", line 268, in _feed send(obj) IOError:

问题 In python2.7, multiprocessing.Queue throws a broken error when initialized from inside a function. I am providing a minimal example that reproduces the problem. #!/usr/bin/python # -*- coding: utf-8 -*- import multiprocessing def main(): q = multiprocessing.Queue() for i in range(10): q.put(i) if __name__ == "__main__": main() throws the below broken pipe error Traceback (most recent call last): File "/usr/lib64/python2.7/multiprocessing/queues.py", line 268, in _feed send(obj) IOError:

问题 I am trying to implement the multiprocessing module for a working with a large csv file. I am using Python 2.7 and following the example from here. I ran the unmodified code (copied below for convenience) and noticed that print statements within the worker function do not work. The inability to print makes it difficult to understand the flow and debug. Can anyone please explain why print is not working here? Does pool.map not execute print commands? I searched online but did not find any

问题 I am trying to follow a very simple multiprocessing example: import multiprocessing as mp def cube(x): return x**3 pool = mp.Pool(processes=2) results = [pool.apply_async(cube, args=x) for x in range(1,7)] However, on my windows machine, I am not able to get the result (on ubuntu 12.04LTS it runs perfectly). If I inspect results , I see the following: [<multiprocessing.pool.ApplyResult object at 0x01FF0910>, <multiprocessing.pool.ApplyResult object at 0x01FF0950>, <multiprocessing.pool

问题 I am trying to add multiprocessing to some code which features functions that I can not modify. I want to submit these functions as jobs to a multiprocessing pool asynchronously. I am doing something much like the code shown here. However, I am not sure how to keep track of results. How can I know to which applied function a returned result corresponds? The important points to emphasise are that I can not modify the existing functions (other things rely on them remaining as they are) and that

问题 I am trying to add multiprocessing to some code which features functions that I can not modify. I want to submit these functions as jobs to a multiprocessing pool asynchronously. I am doing something much like the code shown here. However, I am not sure how to keep track of results. How can I know to which applied function a returned result corresponds? The important points to emphasise are that I can not modify the existing functions (other things rely on them remaining as they are) and that

问题 Experimental Code Here is the experimental code that can launch a specified number of worker processes and then launch a specified number of worker threads within each process and perform the task of fetching URLs: import multiprocessing import sys import time import threading import urllib.request def main(): processes = int(sys.argv[1]) threads = int(sys.argv[2]) urls = int(sys.argv[3]) # Start process workers. in_q = multiprocessing.Queue() process_workers = [] for _ in range(processes): w

问题 It cost me a whole night to debug my code, and I finally found this tricky problem. Please take a look at the code below. from multiprocessing import Pool def myfunc(x): return [i for i in range(x)] pool=Pool() A=[] r = pool.map_async(myfunc, (1,2), callback=A.extend) r.wait() I thought I would get A=[0,0,1] , but the output is A=[[0],[0,1]] . This does not make sense to me because if I have A=[] , A.extend([0]) and A.extend([0,1]) will give me A=[0,0,1] . Probably the callback works in a