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[gpuCI] Forward-merge branch-22.06 to branch-22.08 [skip gpuci] #707

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[gpuCI] Forward-merge branch-22.06 to branch-22.08 [skip gpuci] #707

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GPUtester
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Forward-merge triggered by push to branch-22.06 that creates a PR to keep branch-22.08 up-to-date. If this PR is unable to be immediately merged due to conflicts, it will remain open for the team to manually merge.

@ajschmidt8
Add conda compilers (#702)
0b55c32 
Our `devel` Docker containers need to be switched to using `conda` compilers to resolve a linking error. `raft` is in those containers, but hasn't yet been built with `conda` compilers. This PR addresses that.

These changes won't cleanly merge into `branch-22.08` unfortunately due to the changes in #641, but we can address that another time.

Authors:
   - AJ Schmidt (https://github.com/ajschmidt8)
   - Corey J. Nolet (https://github.com/cjnolet)
   - Vyas Ramasubramani (https://github.com/vyasr)

Approvers:
   - Corey J. Nolet (https://github.com/cjnolet)
@GPUtester GPUtester requested review from a team as code owners June 7, 2022 14:47
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FAILURE - Unable to forward-merge due to conflicts, manual merge is necessary. Do not use the Resolve conflicts option in this PR, follow these instructions https://docs.rapids.ai/maintainers/gpuci/#forward-mergers
IMPORTANT: Before merging and approving this PR, be sure to change the merging strategy to Create a Merge Commit. Otherwise, history will be lost and the branches become incompatible.

@github-actions github-actions bot added the gpuCI label Jun 7, 2022
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cjnolet commented Jun 13, 2022 •
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#705 should fix this conflict. The problem is that the changes introduced into 22.08 which build a separate test conda package assume that the actual API functions for the CTK libs are available across all supported toolkit versions- which isn't the case in a few of them. As an example, there are cusparse functions which were introduced into CTK 11.2 which we use and these aren't available in CTK 11.0. Our current CI is attempting to build a package in CUDA 11.2+ and then execute it in resources containing only CUDA toolkit 11.0. This just simply won't work because the symbols for 11.2 libraries won't be available in 11.0.

Tagging @robertmaynard for any thoughts. Maybe we can consider statically building the cuda toolkit libraries just to pass CI? Otherwise, we might need to consider building the tests conda package fresh in the GPU builds, rather than trying to reuse the one built in the CPU builds.

cc @ajschmidt8 @raydouglass for awareness.

@cjnolet cjnolet closed this Jun 15, 2022
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@GPUtester @cjnolet @ajschmidt8 @raydouglass