Hi all, I have a program that uses the multiprocessing package to run a set of jobs. When I run it using the standard python interpreter on my computer, top shows 8 threads each using about 40M of memory, which remains fairly steady. When I use pypy, both 1.6 and 1.7, the 8 threads almost immediately show using 90-100M of memory, and then that continues to climb as the program runs. Each job runs a lot faster in pypy, but usually before all the jobs are done, the memory on the system is exhausted and swapping starts, which brings the execution speed to a crawl. Is this something anyone else has experienced? Thanks, Colin
On Thu, Dec 22, 2011 at 10:24 PM, Colin Kern <colin.kern@gmail.com> wrote:
Hi Colin. Thanks for the bug report, but we can't really help you without seeing the code. There has been some issues like this in the past, however most of them has been fixed, as far as we know. If you can isolate a preferably small example, we would be happy to help you. Cheers, fijal
On Thu, Dec 22, 2011 at 10:24 PM, Colin Kern <colin.kern@gmail.com> wrote:
Hi Colin. Thanks for the bug report, but we can't really help you without seeing the code. There has been some issues like this in the past, however most of them has been fixed, as far as we know. If you can isolate a preferably small example, we would be happy to help you. Cheers, fijal
participants (2)
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Colin Kern -
Maciej Fijalkowski