[pypy-dev] Pypy jit and (meta) genetic algorithms
naylor.b.david at gmail.com
Tue Sep 27 22:43:20 CEST 2011
It occurred to me that with the many options available for jit (such as
inlining, function_threshold) there may be some merit to optimising those
values. I would expect that the optimised values would be workload specific
however if a workload takes days to run then it would be worth optimising.
I recall an article that used genetic algorithms to select the best parameters
(for gcc) that produces the fastest execution. Is there an equivalent program
for pypy? Or if it is easy enough could someone put together such a (shell
I, unfortunitely, have no experience with genetic algorithms nor know how to
optimise the jit parameters.
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