1 #!/usr/bin/env python 2 3 """ 4 A simple example of parallel computation using a map and managed callables. 5 """ 6 7 import pprocess 8 import time 9 #import random 10 11 # Array size and a limit on the number of processes. 12 13 N = 10 14 limit = 10 15 delay = 1 16 17 # Work function and monitoring class. 18 19 def calculate(i, j): 20 21 """ 22 A supposedly time-consuming calculation on 'i' and 'j'. 23 """ 24 25 #time.sleep(delay * random.random()) 26 time.sleep(delay) 27 return i * N + j 28 29 # Main program. 30 31 if __name__ == "__main__": 32 33 t = time.time() 34 35 # Initialise the results using a map with a limit on the number of 36 # channels/processes. 37 38 results = pprocess.Map(limit=limit) 39 40 # Wrap the calculate function and manage it. 41 42 calc = results.manage(pprocess.MakeParallel(calculate)) 43 44 # Perform the work. 45 46 print "Calculating..." 47 for i in range(0, N): 48 for j in range(0, N): 49 calc(i, j) 50 51 # Show the results. 52 53 for i in range(0, N): 54 for result in results[i*N:i*N+N]: 55 print result, 56 print 57 58 print "Time taken:", time.time() - t 59 60 # vim: tabstop=4 expandtab shiftwidth=4
