Hi David, On Fri, Aug 19, 2011 at 1:56 PM, David Fraser <dav...@sjsoft.com> wrote: > The pypy JIT takes a while to work out which parts of python code need > optimization etc, and only after that phase do the speedups become relevant. > Have there been any efforts (indeed, is it a feasible idea at all) that look > at saving these optimizations for future runs of the same codebase?
No, this is not really doable. The JIT writes explicitly in the assembler the address of a ton of constants. We have no clue what these constants become when we are in a different process. Think even just about Python classes: there is no way at all to know that a class at address 0x1234567 is "the same" as a previous class in a previous process at address 0x7654321, let alone defining what exactly "the same" means. Instead, we can work on lowering the warm-up time of the JIT, notably by lowering the (so far very large) overhead it takes for the JIT to trace a loop. A bientôt, Armin. _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
