Another current problem is that PoCL also does not appear to work on Windows, which is a platform I would like to see supported, but I suspect this is just a few tweaks here and there to get it running since LLVM & CMake work on Windows.

Ideally, a single PyOpenCL package would always have a PoCL platform to work with, but it could take advantage of Intel, AMD, etc if present. I guess this would require some work on the loader itself.

I'm looking at rewriting a current numerical project to PyOpenCL so I'm willing to invest some effort here. Can you point out those conda recipes you mentioned?


On Thu, May 19, 2016 at 4:31 AM, Andreas Klöckner <lists@informa.tiker.net> wrote:

I would also be interested in making PyOpenCL self contained enough that it can be installed without any further dependencies, in particular no OpenCL implementation. Ideally, 'pip install PyOpenCL' would just succeed no matter what. Pocl seems like a reasonable vehicle for that. The problem is that it has a nontrivial build system... And then there's LLVM... It feels like a substantial amount of engineering effort.

Another avenue I explored for a bit was a conda package. I even got to the point of making that work. I can dig those package recipes up if you're interested. I believe I also put them up on github. For those I did the thing that you asked about, which is link PyOpenCL directly to pocl.

Hope that helps, and let me know if you'd like to try and work together to engineer something.


Am 18. Mai 2016 03:16:04 GMT-05:00, schrieb Marmaduke Woodman <mmwoodman@gmail.com>:

I'm curious if anyone has succeeded in building and using PyOpenCL, linked directly to the Beignet or PortableCL runtimes?

In my case, I'm writing a library using PyOpenCL, and it would be useful to fall-back on such an alternative, if the user of my library does not have an OpenCL installation such as Intel's or Nvidia's.


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