Hi 黄若尘 This is generally a hard problem that projects like GCC or LLVM didn't get very far. The problem is slightly more advanced with PyPys JIT, but not much more.
However, the problem is you can do it for simple loops, but the applications are limited outside of pure numerics (e.g. numpy) and also doing SSE stuff in such cases first seems like both a good starting point and a small enough project for master thesis. Cheers, fijal On Tue, Nov 18, 2014 at 3:46 AM, 黄若尘 <hrc...@gmail.com> wrote: > Hi everyone, > > I’m a master student in Japan and I want to do some research in > PyPy/RPython. > I have read some papers about PyPy and I also had some ideas about it. I > have communicated with Mr. Bloz and been advised to send my question here. > > Actually, I wonder if it is possible to make an automatic parallelization > for the trace generated by JIT, that is, check if the hot loop is a parallel > loop, if so, then try to run the trace parallel in multi-core CPU or GPU, > make it faster. > I think it maybe suitable because: > 1. The traced-base JIT is targeting on loops, which is straight to > parallel computation. > 2. There is no control-flow in trace, which is suitable to the fragment > program in GPU. > 3. We may use the hint of @elidable in interpreter codes, since the > elidable functions are nonsensitive in the execution ordering so can be > executed parallel. > > What do you think about it? > > Best Regards, > Huang Ruochen > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > https://mail.python.org/mailman/listinfo/pypy-dev _______________________________________________ pypy-dev mailing list pypy-dev@python.org https://mail.python.org/mailman/listinfo/pypy-dev
