Hi,<br><br>I just wanted to let you know the numbers I got on a 32 core server.<br><br>1 thread: 3280 ms<br>4 threads: 2665 ms<br>8 threads: 2976 ms<br>16 threads: 2878 ms<br>32 threads: 2714 ms<br><br>Chris<br><br><div class="gmail_quote">
On Thu, Feb 16, 2012 at 3:58 PM, Armin Rigo <span dir="ltr"><<a href="mailto:arigo@tunes.org">arigo@tunes.org</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Hi all,<br>
<br>
An update for STM: today I managed to build a pypy using the new "stm<br>
gc". It runs richards.py on tannit:<br>
<br>
in 1 thread: 2320 ms per iteration<br>
in 2 threads: 1410 ms per iteration<br>
in 4 threads: 785 ms per iteration<br>
in 8 threads: 685 ms per iteration<br>
<br>
The small gap between 4 and 8 threads is due to tannit having only 4<br>
"real" cpus, each one hyperthreaded. The additional gain is thus<br>
smaller than expected.<br>
<br>
For comparison, a "pypy --jit off" runs at 650ms per iteration. So<br>
the single-threaded performance is already at only 3.6x worse, and<br>
moreover there are still a few easy big-win optimizations. I will<br>
confirm it in a few days, but I would say that this shows it's working<br>
quite well. :-)<br>
<br>
At least, it's fun to see in "top" a single pypy process using 397% cpu :-)<br>
<br>
For people interested, it is in the "stm-gc" branch; at least<br>
bba9b03f5e70 works. Linux-only for now: " translate.py -O1 --stm<br>
targetpypystandalone --no-allworkingmodules --withmod-transaction<br>
--withmod-select --withmod-_socket ". The modified version of<br>
richards.py I use is in pypy/translator/stm/test/.<br>
<br>
<br>
A bientôt,<br>
<br>
Armin.<br>
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