Only install CUDA packages on CUDA 11. #77
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cc: @jakirkham @ajschmidt8 @raydouglass for your thoughts on this. |
jakirkham
reviewed
Oct 4, 2023
jakirkham
reviewed
Oct 4, 2023
Co-authored-by: jakirkham <[email protected]>
ajschmidt8
approved these changes
Oct 10, 2023
jakirkham
approved these changes
Oct 10, 2023
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Looks like a couple builds might need restarts |
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We should wait to merge this until after the |
raydouglass
approved these changes
Oct 16, 2023
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Thanks all! 🙏 |
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Oct 19, 2023
…or new CI containers (#14296) The aws-sdk-cpp pinning introduced in #14173 causes problems because newer builds of libarrow require a newer version of aws-sdk-cpp. Even though we restrict to libarrow 12.0.1, this restriction is insufficient to create solvable environments because the conda (mamba) solver doesn't seem to consistently reach far back enough into the history of builds to pull the last build that was compatible with the aws-sdk-cpp version that we need. For now, the safest way for us to avoid this problem is to downgrade to arrow 12.0.0, for which all conda package builds are pinned to the older version of aws-sdk-cpp that does not have the bug in question. Separately, while the above issue was encountered we also got new builds of our CI images [that removed system installs of CTK packages from CUDA 12 images](rapidsai/ci-imgs#77). This changes was made because for CUDA 12 we can get all the necessary pieces of the CTK from conda-forge. However, it turns out that the cudf_kafka builds were implicitly relying on system CTK packages, and the cudf_kafka build is in fact not fully compatible with conda-forge CTK packages because it is not using CMake via scikit-build (nor any other more sophisticated library discovery mechanism like pkg-config) and therefore does not know how to find conda-forge CTK headers/libraries. This PR introduces a set of temporary patches to get around this limitation. These patches are not a long-term fix, and are only put in place assuming that #14292 is merged in the near future before we cut a 23.12 release. Authors: - Vyas Ramasubramani (https://github.com/vyasr) Approvers: - Bradley Dice (https://github.com/bdice) - Ray Douglass (https://github.com/raydouglass) URL: #14296
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This PR changes CUDA 12
ci-condaimages so that they don't install CUDA Toolkit packages. For CUDA 12 conda images, we should fetch the relevant CUDA Toolkit packages from conda-forge and don't need a full system CUDA Toolkit.Resolves https://github.com/rapidsai/ops/issues/2565.