Question #244277 on Yade changed:
https://answers.launchpad.net/yade/+question/244277
Status: Open => Answered
Bruno Chareyre proposed the following answer:
I observed that if I run -jN when the number of available cores is >N, the
cores that are effectively used are always changing during the simulation. For
-j2 for instance, it will use (1,4), (2,3), (4,7), etc. randomly.
Could it be that it adds big overhead when 32 simulations are sharing 64
threads and exchanging them all the time (wich needs, I guess, a lot of cache
update)?
Is it the reason for the "affinity" option, that I don't clearly understood yet?
What happens with variants like below?
yade-batch -j1 --job-threads=2 file.table file.py
yade-batch -j2 --job-threads=2 file.table file.py
yade-batch -j4 --job-threads=2 file.table file.py
etc.
Also interesting:
yade-batch -j16 --job-threads=1 file.table file.py
How did you know the "--job-threads" option? I didn't know it and I don't see
it in the documentation.
I can grep it in the source code though, if it really works we should mention
it in user manual and list it in yade -h.
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