Add support for CUDA 12.0. #1742
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I can have a look @maleadt, CUDA v12.0 should fix some bugs but it also removed a lot of depreciated routines that we are using. The current error with ERROR: LoadError: UndefVarError: libcudart not definedand I have a similar error julia> using CUDA
julia> CUDA.versioninfo()
CUDA runtime 11.8, artifact installation
CUDA driver 11.8
NVIDIA driver 520.61.5
Libraries:
- CUBLAS: 11.11.3
- CURAND: 10.3.0
- CUFFT: 10.9.0
- CUSOLVER: 11.4.1
- CUSPARSE: 11.7.5
- CUPTI: 18.0.0
- NVML: 11.0.0+520.61.5
Toolchain:
- Julia: 1.8.1
- LLVM: 13.0.1
- PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3, 6.4, 6.5, 7.0, 7.1, 7.2
- Device capability support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75, sm_80, sm_86
8 devices:
0: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
1: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
2: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
3: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
4: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
5: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
6: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
7: Tesla P100-PCIE-12GB (sm_60, 11.910 GiB / 12.000 GiB available)
julia> CUDA.set_runtime_version!(v"12.0")
[ Info: Set CUDA Runtime version preference to 12.0, please re-start Julia for this to take effect.montalex@pandora.gerad.lan:~/git/CUDA.jl (1016)>julia
_
_ _ _(_)_ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 1.8.1 (2022-09-06)
_/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |
julia> using CUDA
[ Info: Precompiling CUDA [052768ef-5323-5732-b1bb-66c8b64840ba]
┌ Error: No CUDA Runtime library found. This can have several reasons:
│ * you are using an unsupported platform: CUDA.jl only supports Linux (x86_64, aarch64, ppc64le), and Windows (x86_64).
│ refer to the documentation for instructions on how to use a custom CUDA runtime.
│ * you precompiled CUDA.jl in an environment where the CUDA driver was not available.
│ in that case, you need to specify (during pre compilation) which version of CUDA to use.
│ refer to the documentation for instructions on how to use `CUDA.set_runtime_version!`.
│ * you requested use of a local CUDA toolkit, but not all components were discovered.
│ try running with JULIA_DEBUG=CUDA_Runtime_Discovery for more information.
└ @ CUDA ~/git/CUDA.jl/src/initialization.jl:77 |
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I'll update the headers.
That's because your driver is too old, only supporting up to CUDA 11.8, not CUDA 12.0. EDIT: Oh, I forgot to bump the Project.toml change, maybe that's the reason. |
maleadt
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@maleadt |
Now may be a good time to remove that, so yeah feel free to get rid of those. |
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FWIW, now that we've bumped the minimum requirement to CUDA 11.0, these are the driver-level functions that are supported (since it isn't always documented exactly which functions are supported; often deprecated or undocumented ones are silently still available): Posting this list because we can't do CI for this |
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@maleadt ps: I also added some others fixes for the release v"12.0" on my branch |
Thanks, I've merged them here. |
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As expected, the upgrade to 12.0 Update 1 didn't help with the CUSPARSE issues. |
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@amontoison Any update from NVIDIA? Worst case, we make the cusparse/broadcast use larger inputs and introduce a test marked as broken on CUDA 12 for the problematic conversions. |
amontoison
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Feb 8, 2023
They still try to understand where is the issue. |
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Yep, that's OK for me :-) |
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I will open a PR tonight to fix |
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The remaining problem with the cudadrv tests is do |
* Update CUSPARSE for CUDA v12.0 * Fix a test with CuMatrix * CuSparseMatrixCOO * Keep the previous signature of scatter! and gather!
Also add a conversion CuSparseVector -> CuVector
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Ahh, so close. @amontoison Looks like some of the conversions regressed on CUDA 11.0. |
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Fixed with #1791 🤞 |
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Great! Let's do a final check after merging your other changes, and get this over the finish line. Just in time for CUDA 12.1... 😅 |
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## master #1742 +/- ##
==========================================
- Coverage 60.46% 59.85% -0.61%
==========================================
Files 148 147 -1
Lines 11885 12086 +201
==========================================
+ Hits 7186 7234 +48
- Misses 4699 4852 +153
... and 28 files with indirect coverage changes Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report in Codecov by Sentry. |
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Finally, CI is all green. Thanks for the help @amontoison! |
simonbyrne
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Co-authored-by: Alexis Montoison <alexis.montoison@polymtl.ca>
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Release notes: https://developer.nvidia.com/blog/cuda-toolkit-12-0-released-for-general-availability/
TODO: