Use ptxcompiler to patch Numba at runtime to support CUDA enhanced compatibility. #9687
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This looks good so far on inspection. |
shwina
changed the title
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It sounds like we're not going to require ptxcompiler for ARM (and not even build the package for it) and just require CUDA 11.5 for it - in that case, I think we'll also need to depend on ptxcompiler conditionally, and guard its use with try ... except ImportError.
Co-authored-by: Graham Markall <[email protected]>
python/cudf/cudf/__init__.py
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| # Patch Numba to support CUDA enhanced compatibility. | ||
| # See https://github.com/rapidsai/ptxcompiler for | ||
| # details. | ||
| patch_numba_codegen_if_needed() | ||
| del patch_numba_codegen_if_needed | ||
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Removed as added above
| # Patch Numba to support CUDA enhanced compatibility. | |
| # See https://github.com/rapidsai/ptxcompiler for | |
| # details. | |
| patch_numba_codegen_if_needed() | |
| del patch_numba_codegen_if_needed |
shwina
requested review from
rgsl888prabhu and
skirui-source
and removed request for
a team
raydouglass
added
feature request
| @@ -51,6 +51,7 @@ requirements: | |||
| - nvtx >=0.2.1 | |||
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Don't you need to increase the numba pin in this file as well?
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rerun tests |
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rerun tests |
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This will make cudf change the behavior of Numba on import now, correct? It's a bit of a shame that we're adding additional side effects to importing cudf that are arguably more impactful than the memory allocator side effects we currently have... |
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It patches Numba only in an Enhanced Compatibility scenario - when the toolkit version is newer than the driver version. When the driver version is sufficient, no patching occurs. In other words, the only scenario in which Numba is patched is when it wouldn't have worked at all. In the long term I expect Numba will use ptxcompiler by default, but it also needs a cubin linker than can be linked statically too, which is not available at present. This will give Numba general support for Enhanced Compatibility, so no patch would be needed in any case. |
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