exanauts / cusolverrf.jl Goto Github PK
View Code? Open in Web Editor NEWA Julia wrapper for cusolverRF
License: MIT License
A Julia wrapper for cusolverRF
License: MIT License
I added a structure TriangularOperator
in KrylovPreconditioners.jl
(v0.2.1) to easily update the triangular matrix and also have the most efficient function to perform backward and forward sweeps.
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On the branch master
, the following testset fails with the following error:
CUDA runtime 12.3, artifact installation
CUDA driver 12.3
NVIDIA driver 535.104.12, originally for CUDA 12.2
CUDA libraries:
- CUBLAS: 12.3.2
- CURAND: 10.3.4
- CUFFT: 11.0.11
- CUSOLVER: 11.5.3
- CUSPARSE: 12.1.3
- CUPTI: 21.0.0
- NVML: 12.0.0+535.104.12
Julia packages:
- CUDA: 5.1.0
- CUDA_Driver_jll: 0.7.0+0
- CUDA_Runtime_jll: 0.10.0+1
Toolchain:
- Julia: 1.9.3
- LLVM: 14.0.6
1 device:
0: NVIDIA A100 80GB PCIe (sm_80, 79.143 GiB / 80.000 GiB available)
RFBacthedLowLevel factorization: Error During Test at /home/montalex/git/CUSOLVERRF.jl/test/cusolverRF.jl:29
Got exception outside of a @test
ReadOnlyMemoryError()
Stacktrace:
[1] macro expansion
@ ~/.julia/packages/CUDA/nIZkq/lib/cusolver/libcusolverRF.jl:236 [inlined]
[2] #1195
@ ~/.julia/packages/CUDA/nIZkq/lib/utils/call.jl:27 [inlined]
[3] #1
@ ~/.julia/packages/CUDA/nIZkq/lib/cusolver/libcusolver.jl:17 [inlined]
[4] retry_reclaim(f::CUDA.CUSOLVER.var"#1#2"{CUDA.CUSOLVER.var"#1195#1196"{CUSOLVERRF.RfHandle}}, isfailed::Base.Fix2{typeof(in), Tuple{CUDA.CUSOLVER.cusolverStatus_t}})
@ CUDA ~/.julia/packages/CUDA/nIZkq/src/pool.jl:359
[5] check
@ ~/.julia/packages/CUDA/nIZkq/lib/cusolver/libcusolver.jl:16 [inlined]
[6] cusolverRfBatchAnalyze
@ ~/.julia/packages/CUDA/nIZkq/lib/utils/call.jl:26 [inlined]
[7] CUSOLVERRF.RFBatchedLowLevel(lu_host::CUSOLVERRF.RFSymbolicAnalysis{Float64, Int32}, batchsize::Int64; options::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ CUSOLVERRF ~/git/CUSOLVERRF.jl/src/rf_wrapper.jl:222
[8] RFBatchedLowLevel
@ ~/git/CUSOLVERRF.jl/src/rf_wrapper.jl:200 [inlined]
[9] #RFBatchedLowLevel#5
@ ~/git/CUSOLVERRF.jl/src/rf_wrapper.jl:197 [inlined]
[10] CUSOLVERRF.RFBatchedLowLevel(A::CuSparseMatrixCSR{Float64, Int32}, batchsize::Int64)
@ CUSOLVERRF ~/git/CUSOLVERRF.jl/src/rf_wrapper.jl:192
[11] macro expansion
@ ~/git/CUSOLVERRF.jl/test/cusolverRF.jl:39 [inlined]
[12] macro expansion
@ ~/Applications/julia/julia-1.9.3/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
[13] macro expansion
@ ~/git/CUSOLVERRF.jl/test/cusolverRF.jl:30 [inlined]
[14] macro expansion
@ ~/Applications/julia/julia-1.9.3/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
[15] top-level scope
@ ~/git/CUSOLVERRF.jl/test/cusolverRF.jl:4
[16] include(fname::String)
@ Base.MainInclude ./client.jl:478
[17] top-level scope
@ ~/git/CUSOLVERRF.jl/test/runtests.jl:15
[18] include(fname::String)
@ Base.MainInclude ./client.jl:478
[19] top-level scope
@ none:6
[20] eval
@ ./boot.jl:370 [inlined]
[21] exec_options(opts::Base.JLOptions)
@ Base ./client.jl:280
[22] _start()
@ Base ./client.jl:522
Test Summary: | Pass Error Total Time
cusolverRF | 2 1 3 19.5s
RFLowLevel factorization | 2 2 15.4s
RFBacthedLowLevel factorization | 1 1 1.9s
ERROR: LoadError: Some tests did not pass: 2 passed, 0 failed, 1 errored, 0 broken.
in expression starting at /home/montalex/git/CUSOLVERRF.jl/test/cusolverRF.jl:2
in expression starting at /home/montalex/git/CUSOLVERRF.jl/test/runtests.jl:15
ERROR: Package CUSOLVERRF errored during testing
CUDA 12.0 has made some change in cusparse
, apparently impacting CUSOLVERRF.
Also, the functions used in the backsolve have been deprecated and removed in CUDA 12.0.
We observed a performance regression due to the new API of CUSPARSE in CUDA 12. This is due to the analysis step being required before each backsolve. This was not the case with CUDA version < 12.
CUDA 12:
CUSOLVERRF.jl/src/backsolve.jl
Lines 76 to 79 in d683147
CUDA 11:
CUSOLVERRF.jl/src/backsolve_deprecated.jl
Line 74 in d683147
For now we detect the loaded CUDA version and use the faster approach of CUDA version < 12, where the analysis stage is only called once.
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