The multiprocessing module allows the programmer to fully leverage *multiple * processors on a given machine (python docs). This allows the operating system to take advantage of any parallelism inherent in the hardware design.
If you are using the module on non-multiprocessor machines, I think you are not using it to its full capability, and the module's overhead will just slow down your code. Aldrich On Thu, Jun 21, 2012 at 12:05 AM, Yesterday Paid <howmuchisto...@gmail.com>wrote: > from multiprocessing import Pool > from itertools import product > > def sym(lst): > x,y=lst > tmp=x*y > if rec(tmp): > return tmp > else: > return None > > def rec(num): > num=str(num) > if num == "".join(reversed(num)): return True > else: return False > > if __name__ == "__main__": > pool=Pool(processes=8) > lst=product(xrange(100,1000),repeat=2) > rst=pool.map(sym,lst) > #rst=sym(lst) > print max(rst) > > > in my old computer(2006), > when run it on single process, it takes 2 seconds > but using multiprocessing.pool, it takes almost 8 or 9 seconds > is it possible? > -- > http://mail.python.org/mailman/listinfo/python-list >
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