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Include ptxas in cudatoolkit package #15
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@katietz FYI |
Note I didn't test this on Windows since I don't have a Windows machine. |
@jayfurmanek would suggest submitting this to the conda-forge feedstock ( https://github.com/conda-forge/cudatoolkit-feedstock ) Also Jonathan left Anaconda FYI |
@jayfurmanek Could you also fire up a PR to https://github.com/conda-forge/cudatoolkit-feedstock if you have time? 🙂 It is maintained by some NVIDIA folks so it's in a better shape. I am less certain about whether or not btw I think Jonathon is no longer a maintainer here. You might have to ping someone else from Anaconda (try https://gitter.im/conda/conda). cc: @jakirkham @kkraus14 |
@jakirkham What do you think about I can look at putting this up in forge as well. |
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Will ping some folks internally to see what can be done here |
Aha John and I replied at the same time! |
The part about libdevice.10.bc is for sure something I would merge into Anconda's recipe. The ptxas part needs to be delayed. If there might be a solution found for it, ok. So I would suggest to make at least for the libdevice.10.bc part a new PR. |
It was discovered that XLA does not work with the latest TensorFlow GPU builds:
AnacondaRecipes/tensorflow_recipes#24 (comment)
This is because XLA requires the ptxas compiler and libdevice.10.bc.
This PR has two changes to the cudatoolkit package to fix XLA:
the libdevice.10.bc package is in the wrong location for XLA. It's shipped in $CONDA_HOME/lib when it should be in
$CONDA_HOME/nvvm/libdevice/
so this PR copies it to this location (and keeps it in /lib too in case some things need it there)the
ptxas
binary, which is used by the XLA compiler, is not included in the package at all currently so this PR adds it into$CONDA_HOME/bin
Unfortunately, this feedstock doesn't have any branches for older cuda versions, so this PR is only against the latest (11.0).