I think you are looking for the JIT "threshold" option [1], which can be
specified as
pypy --jit threshold=200
to get the JIT to consider a loop "hot" after it has been hit 200 times.
The default is 1000
Matti
[0]
https://doc.pypy.org/en/latest/jit_help.html?highlight=trace_eagerness#advanced-jit-options
On 24/9/22 14:04, Pavel Durov wrote:
Hi,
I'm not sure that's the best place to ask questions, but I couldn't
find other mediums or documentation.
I have a question regarding pypy jit logs:
Sometimes when I run an RPython program that runs very quickly, I
don't get any jit logs produced, but when I intentionally increase the
execution time (by adding more loops, for example), I do get the logs.
What is the mechanics behind jit logs? Is there some kind of a hot
threshold that needs to be reached? Where can I read more about it?
My stack overflow question from a couple of weeks ago:
https://stackoverflow.com/questions/73665618/rpython-jit-logs
noredirect=1#comment130093714_73665618
I moved on from this problem since I was able to produce logs
eventually, but I would like to understand what's happening behind the
scenes.
Thank you,
Pavel
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