[pypy-dev] Saving and reloading JIT optimizations

[Armin Rigo]

Hi David,

On Fri, Aug 19, 2011 at 1:56 PM, David Fraser <davidf at 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.