Hi Fijaklowski, Thank you very much for your reply.
Yes, you are right, it’s too hard for me to implement automatic parallelization for the whole PyPy’s trace JIT. I think maybe I can firstly do some work with a very simple interpreter (for example the example-interpreter introduced by PyPy documentation), and try to change some behaviors of RPython JIT. By the way, could you tell me how can I get the traces and handle them before compiled to native code? I just want to try to convert some of the traces to OpenCL kernel codes and run them in other devices like GPU. Best Regards, Huang Ruochen > 在 2014年11月21日，上午12:05，Maciej Fijalkowski <fij...@gmail.com> 写道： > > 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
