On Fri, Feb 1, 2013 at 12:01 AM, John Camara <john.m.cam...@gmail.com> wrote: > A couple of days ago I heard about the Parallella [1] project which is an > open hardware platform similar to the Raspberry Pi but with much higher > capabilities. It has a Zynq Z-7010 which has both a dual core ARM A9 (800 > MHz) processor and a Artix-7 FPGA, a 16 core Epiphany multicore accelerator, > 1GB ram (see [2] for more info) and currently boots up in Ubuntu. > > The goal of the Parallella project is to develop an open parallel hardware > platform and development tools. Recently they announced support for Python > with Mark Dewing [3] leading the effort. I had asked Mark if he considered > PyPy but at this time he doesn't have time for this investigation and he > reposted my comment on the forum [4] with a couple of question. Maybe one of > you could answer them. > > Working with the Parallella project maybe a good opportunity for the PyPy > project from both a PR perspective and as well as the technical challenges > it would present. On the technical side it would give the opportunity to > test STM on a reasonable number of cores while also dealing with cores from > different architectures (ARM and Epiphany). I could see all the JITting > occurring on the ARM cores with it producing output for both architectures > based on which type of core STM decides to use for a chunk of work to > execute on. Of course there is also the challenge of bridging between the 2 > architectures. Maybe even some of the more expensive STM operations could > be offloaded to the FPGA or even a limited amount of very hot sections of > code could be JITted to the FPGA (although this might be more work than its > worth). > > From a PR perspective PyPy needs to excel at some niche market so that the > PyPy platform can take off. When PyPy started concentrating on the > scientific market with increasing support for Numpy I thought this would be > the niche market that would get PyPy to take off. But there have been a > couple of issue with this approach. There is a tremendous amount of work > that needs to be done so that PyPy can look attractive to this niche market. > It requires supporting both NumPy and SciPy and their was an expectation > that if PyPy supports NumPy others would come to help out with the SciPy > support. The problem is that there doesn't seam to be many who are eager to > pitch in for the SciPy effort and there also has not been a whole lot > willing to help will the ongoing NumPy work. I think in general the ratio > of people who use NumPy and SciPy to those willing to contribute is quite > small. So the idea of going after this market was a good idea and can > definitely have the opportunity to showing the strength of PyPy project it > hasn't done much to improve the image of the PyPy project. It also doesn't > help that there is some commercial interests that have popped up recently > that have decided to play hard ball against PyPy by spreading FUD. > > Unlike the Raspberry Pi hardware which can only support hobbyist the > Parallella hardware can support both hobbyists and commercial interests. > They cost $100 which is more than the $35 for Raspberry Pi but still within > reach of most hobbyists and they didn't cut out the many features that are > needed for commercial interests. The Parallella project raised nearly $0.9 > million on kickstarter [5] for the project with nearly 5000 backers. Since > many who will use the Parallella hardware also have experience on embedded > systems they and are more likely used to writing low level code in assembly, > FPGAs, and even lots of C code and I'm sure have hit many issues with > programming in parallel/multithreaded and would welcome a better developer > experience. I bet many of them would be willing to contribute both > financially and time to supporting such an effort. I believe the > Architecture of PyPy could lend it self to becoming the core of such a > development system and would allow Python to be used in this space. This > could provide a lot of good PR for the PyPy project. > > Now I'm not saying PyPy shouldn't devote any more time to supporting NumPy > as I'm sure when PyPy has very good support for both NumPy and SciPy it's > going to be a very good day for all Python supporters. I just think that > the PyPy team needs to think about a strategy that in the end will help its > PR and gain support from a much larger community. This project is doing a > lot of good things technically and now it just needs to get the attention of > the development community at large. Now I can't predict if working with the > Parallella project would be the break though in PR that PyPy needs but it's > at least an option that's out there. > > BTW I don't have any commercial interests in the Parallella project. If > some time in the future I use their hardware it would likely be as a > hobbyist and it would be nice to program it in Python. My real objective of > this post to see the PyPy project gain wider interest as it would be a good > thing for Python. > > [1] - http://www.parallella.org/ > [2] - http://www.parallella.org/board/ > [3] - http://forums.parallella.org/memberlist.php?mode=viewprofile&u=3344 > [4] - http://forums.parallella.org/viewtopic.php?f=26&t=139 > [5] - > http://www.kickstarter.com/projects/adapteva/parallella-a-supercomputer-for-everyone > > John > > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > http://mail.python.org/mailman/listinfo/pypy-dev >
Hi John To answer the question from the forum - the JIT emits assembler (x86, arm) it does not emit C code. As far as PR is concerned, there is no such things as PyPy team meets and decided where to go. Everyone works what they feel like doing where volunteer time is concerned. Obviously things are a little different when there is a commercial interest in something. >From my own perspective PyPy should excel at one thing - providing kick ass Python VM that's universally fast. We're missing quite a few things (like library support), but the things has improved quite drastically, due to things like cffi. The startup time is another one on the list to consider and it affects ARM even more (since it's slower in general). Cheers, fijal _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
