-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On 09/27/2011 10:43 PM, David Naylor wrote: > Hi All > > 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 > script) program? > > I, unfortunitely, have no experience with genetic algorithms nor know how to > optimise the jit parameters. pretty simple genomes could already do i suppose (pyevolve should have everything you need
the main tricky parts will be choosing what sizes of population and how to test i am very sure that this will be very computation-intensive - -- ronny -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.11 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org/ iQIcBAEBAgAGBQJOgj4fAAoJEE8uAqxPKbjk1l8QAIc3VWFEYbVhGIWfcx4SggGt tT1G8A2zZBJDZ1JOOAkrkomx4i1PGOY05/cXQweHLoBK95aP2l+uVooRWGwpiavV aC6KkJBQ6WFBRoIDvPGx/HUNcxPN4YQzqGFI9qZ6+IbbDpm+j9BrPAz10sNL/lem EpxP8yHggwhY3mTVm4rLaKZzCY7i/78V7nQPfDRd1lADR2EM2sMmgq+MJAeKEn29 pscGgm4Pm3XTAgS3pwcO2zR7CKjHlhRSNcKqSJ4yFVt1xzSSpACq6RRQVxfQLDz8 ifIF+9gLFerKWhQnsspNCLlq6zxn+4baA6/IH1RFo8QBB9fhWZa8LpXuTxaeA6yW oEDsd6Hc9i8IeKuOxV5EDSKSgFqhxUJsG097FVytS0N7qjYLdTb13J88MOjH367T KFdKM4ekqedHytHS2Y/dTZHGx8axGaNB53RV6yb6EiDrjLNBCtDMOaCcDsa/fN/d 8uf8deCyhULmkxW3MvzyYIcoUDwPEnb0T9pqiXEAgq35IMZ+830O+BR6Lhpm0aya 1la6mfGC1BB1vHAr8b0UCPkqAqFxPEd/dJoQxvQdzsMjmxgtO881N2ERfFyOACwD 4J2i3rP+7ZvQ8VMmJ0F5pqBiLZR8Yz02t8aaoQGvO8OVbV1fQHvmOwm5ESvBuM4m f84oSEQxc1U0GOE+ISk7 =BWpS -----END PGP SIGNATURE----- _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
