[pypy-dev] Profiling pypy code

[Armin Rigo]

Hi Timothy,

On Wed, Mar 28, 2012 at 16:35, Timothy Baldridge <tbaldridge at gmail.com> wrote:
> What should I look into for benchmarking actual times spent
> in each loop?

As a first approximation, getting only the execution counts is enough.
 Basically the work flow is: pick one of the most often executed
loops, look into it, and be scared by the amount of cruft left ---
calls to RPython functions, notably.  Then try to remove them.

Getting the execution times is not very useful at first, because the
typical execution counts are not flat at all: often, the first few
loops are run 100's or 1000's of times more often than all the others.
 At least it is so when looking at the interpreter running small
examples.


A bientôt,

Armin.