[pypy-dev] Contributing Polyhedral Optimisations in PyPy

Armin Rigo armin.rigo at gmail.com
Fri Dec 18 13:03:49 EST 2020


Hi,

On Thu, 17 Dec 2020 at 23:48, William ML Leslie
<william.leslie.ttg at gmail.com> wrote:
> The challenge with implementing this in the pypy JIT at this point is
> that the JIT only sees one control flow path.  That is, one loop, and
> the branches taken within that loop.  It does not find out about the
> outer loop usually until later, and may not ever find out about the
> content of other control flow paths if they aren't taken.

Note that strictly speaking, the problem is not that you haven't seen
yet other code paths.  It's Python, so you never know what may happen
in the future---maybe another code path will be taken, or maybe
someone will do crazy things with `sys._getframe()` or with the
debugger `pdb`.  So merely seeing all paths in a function doesn't
really buy you a lot.  No, the problem is that emitting machine code
is incremental at the granularity of code paths.  At the point where
we see a new code path, all previously-seen code paths have already
been completely optimized and turned into machine code, and we don't
keep much information about them.

To go beyond this simple model, what we have so far is that we can
"invalidate" previous code paths at any point, when we figure out that
they were compiled using assumptions that no longer hold.  So using
it, it would be possible in theory to do any amount of global
optimizations: save enough additional information as you see each code
path; use it later in the optimization of additional code paths;
invalidate some of the old code paths if you figure out that its
optimizations are no longer valid (but invalidate only, not write a
new version yet); and when you later see the old code path being
generated again, optimize it differently.  It's all doable, but
theoretical so far: I don't know of any JIT compiler that seriously
does things like that.  It's certainly worth a research paper IMHO.
It also looks like quite some work.  It's certainly not just "take
some ideas from [ahead-of-time or full-method] compiler X and apply
them to PyPy".


A bientôt,

Armin.


More information about the pypy-dev mailing list