Repository: JuliaGPU/CUDA.jl

Issue #1363: mul! does not dispatch on Adjoint
Created: 2022-02-09T23:48:56Z
Describe the bug
mul! does not dispatch on Adjoint{Float32, CUDA.CUSPARSE.CuSparseMatrixCSC{Float32, Int32}}. Easily fixable by using e.g. cu(A') but I thought I'd report it.
To reproduce
The Minimal Working Example (MWE) for this bug:
using SparseArrays, CUDA, LinearAlgebra

CUDA.allowscalar(false)

N = 400
uA2 = cu(zeros(N,N))
A2u = cu(zeros(N,N))
A2 = cu(sprand(N, N, 0.01))
u = cu(rand(N, N))

mul!(A2u, A2, u)
mul!(uA2, u, A2')
First mul! works, second doesn't.
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Expected behavior
Both multiplications work.
Version info
Details on Julia:
Julia Version 1.7.1
Commit ac5cc99908 (2021-12-22 19:35 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: 12th Gen Intel(R) Core(TM) i7-12700K
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, tigerlake)
Environment:
  JULIA_EDITOR = "/home/ash/.vscode-server/bin/899d46d82c4c95423fb7e10e68eba52050e30ba3/node"
  JULIA_NUM_THREADS = 16

Details on CUDA:
CUDA toolkit 11.6, artifact installation
NVIDIA driver 470.86.0, for CUDA 11.4
CUDA driver 11.4

Libraries: 
- CUBLAS: 11.8.1
- CURAND: 10.2.9
- CUFFT: 10.7.0
- CUSOLVER: 11.3.2
- CUSPARSE: 11.7.1
- CUPTI: 16.0.0
- NVML: 11.0.0+470.86
- CUDNN: 8.30.2 (for CUDA 11.5.0)
- CUTENSOR: 1.4.0 (for CUDA 11.5.0)

Toolchain:
- Julia: 1.7.1
- LLVM: 12.0.1
- 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
- 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

1 device:
  0: NVIDIA GeForce RTX 3080 Ti (sm_86, 11.341 GiB / 11.768 GiB available)

Duplicate issue #1568: LinearAlgebra./ and LinearAlgebra.\ breaks CuArray 
Created: 2022-07-22T03:29:35Z
After using the operator / or \ on two CuArrays, some internal states oc CUDA seems to be broken.
The lines followng it causes strange error messages.
Removing the line using the operator / or \ will eliminate the error.
To reproduce
The Minimal Working Example (MWE) for this bug:
using LinearAlgebra
using CUDA

b = CUDA.rand(Float64,5,5)
A = CUDA.rand(Float64,5,5)
V = (A \ b)  # no command-line errors if this line is absent 

B = CUDA.rand(Float64,5,5)
w = CUDA.rand(Float64,5)
B * w
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git-tree-sha1 = "771bfe376249626d3ca12bcd58ba243d3f961576"
uuid = "dad2f222-ce93-54a1-a47d-0025e8a3acab"
version = "0.0.16+0"

[[LazyArtifacts]]
deps = ["Artifacts", "Pkg"]
uuid = "4af54fe1-eca0-43a8-85a7-787d91b784e3"

[[LibCURL]]
deps = ["LibCURL_jll", "MozillaCACerts_jll"]
uuid = "b27032c2-a3e7-50c8-80cd-2d36dbcbfd21"

[[LibCURL_jll]]
deps = ["Artifacts", "LibSSH2_jll", "Libdl", "MbedTLS_jll", "Zlib_jll", "nghttp2_jll"]
uuid = "deac9b47-8bc7-5906-a0fe-35ac56dc84c0"

[[LibGit2]]
deps = ["Base64", "NetworkOptions", "Printf", "SHA"]
uuid = "76f85450-5226-5b5a-8eaa-529ad045b433"

[[LibSSH2_jll]]
deps = ["Artifacts", "Libdl", "MbedTLS_jll"]
uuid = "29816b5a-b9ab-546f-933c-edad1886dfa8"

[[Libdl]]
uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"

[[LinearAlgebra]]
deps = ["Libdl"]
uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

[[LogExpFunctions]]
deps = ["ChainRulesCore", "ChangesOfVariables", "DocStringExtensions", "InverseFunctions", "IrrationalConstants", "LinearAlgebra"]
git-tree-sha1 = "09e4b894ce6a976c354a69041a04748180d43637"
uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
version = "0.3.15"

[[Logging]]
uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"

[[Markdown]]
deps = ["Base64"]
uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"

[[MbedTLS_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"

[[MozillaCACerts_jll]]
uuid = "14a3606d-f60d-562e-9121-12d972cd8159"

[[NetworkOptions]]
uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"

[[OpenLibm_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "05823500-19ac-5b8b-9628-191a04bc5112"

[[OpenSpecFun_jll]]
deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1"
uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
version = "0.5.5+0"

[[Pkg]]
deps = ["Artifacts", "Dates", "Downloads", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "Serialization", "TOML", "Tar", "UUIDs", "p7zip_jll"]
uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"

[[Preferences]]
deps = ["TOML"]
git-tree-sha1 = "47e5f437cc0e7ef2ce8406ce1e7e24d44915f88d"
uuid = "21216c6a-2e73-6563-6e65-726566657250"
version = "1.3.0"

[[Printf]]
deps = ["Unicode"]
uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"

[[REPL]]
deps = ["InteractiveUtils", "Markdown", "Sockets", "Unicode"]
uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"

[[Random]]
deps = ["Serialization"]
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

[[Random123]]
deps = ["Random", "RandomNumbers"]
git-tree-sha1 = "afeacaecf4ed1649555a19cb2cad3c141bbc9474"
uuid = "74087812-796a-5b5d-8853-05524746bad3"
version = "1.5.0"

[[RandomNumbers]]
deps = ["Random", "Requires"]
git-tree-sha1 = "043da614cc7e95c703498a491e2c21f58a2b8111"
uuid = "e6cf234a-135c-5ec9-84dd-332b85af5143"
version = "1.5.3"

[[Reexport]]
git-tree-sha1 = "45e428421666073eab6f2da5c9d310d99bb12f9b"
uuid = "189a3867-3050-52da-a836-e630ba90ab69"
version = "1.2.2"

[[Requires]]
deps = ["UUIDs"]
git-tree-sha1 = "838a3a4188e2ded87a4f9f184b4b0d78a1e91cb7"
uuid = "ae029012-a4dd-5104-9daa-d747884805df"
version = "1.3.0"

[[SHA]]
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"

[[Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"

[[Sockets]]
uuid = "6462fe0b-24de-5631-8697-dd941f90decc"

[[SparseArrays]]
deps = ["LinearAlgebra", "Random"]
uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

[[SpecialFunctions]]
deps = ["ChainRulesCore", "IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
git-tree-sha1 = "d75bda01f8c31ebb72df80a46c88b25d1c79c56d"
uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
version = "2.1.7"

[[Statistics]]
deps = ["LinearAlgebra", "SparseArrays"]
uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"

[[TOML]]
deps = ["Dates"]
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"

[[Tar]]
deps = ["ArgTools", "SHA"]
uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"

[[Test]]
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[[TimerOutputs]]
deps = ["ExprTools", "Printf"]
git-tree-sha1 = "464d64b2510a25e6efe410e7edab14fffdc333df"
uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
version = "0.5.20"

[[UUIDs]]
deps = ["Random", "SHA"]
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"

[[Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"

[[Zlib_jll]]
deps = ["Libdl"]
uuid = "83775a58-1f1d-513f-b197-d71354ab007a"

[[nghttp2_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"

[[p7zip_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"




Expected behavior
Run the code in MWE from command line or Julia REPL will generate the following error message:
(base) dabajabaza@XXXX:~$ julia jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl 
ERROR: LoadError: CUBLASError: the requested feature is not supported (code 15, CUBLAS_STATUS_NOT_SUPPORTED)
Stacktrace:
 [1] throw_api_error(res::CUDA.CUBLAS.cublasStatus_t)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/cublas/error.jl:50
 [2] macro expansion
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/error.jl:63 [inlined]
 [3] cublasDgemv_v2(handle::Ptr{Nothing}, trans::Char, m::Int64, n::Int64, alpha::Bool, A::CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, lda::Int64, x::CuArray{Float64, 1, CUDA.Mem.DeviceBuffer}, incx::Int64, beta::Bool, y::CuArray{Float64, 1, CUDA.Mem.DeviceBuffer}, incy::Int64)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/utils/call.jl:26
 [4] gemv!
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/wrappers.jl:331 [inlined]
 [5] gemv_dispatch!(Y::CuArray{Float64, 1, CUDA.Mem.DeviceBuffer}, A::CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, B::CuArray{Float64, 1, CUDA.Mem.DeviceBuffer}, alpha::Bool, beta::Bool)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/cublas/linalg.jl:179
 [6] mul!
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/linalg.jl:188 [inlined]
 [7] mul!
   @ ~/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:275 [inlined]
 [8] *(A::CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, x::CuArray{Float64, 1, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:47
 [9] top-level scope
   @ ~/jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl:9
in expression starting at /home/dabajabaza/jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl:9


Version info
Details on Julia:
Julia Version 1.7.2
Commit bf53498635 (2022-02-06 15:21 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
Environment:
  JULIA_PKG_SERVER = https://mirrors.tuna.tsinghua.edu.cn/julia


Details on CUDA:
CUDA toolkit 11.7, artifact installation
NVIDIA driver 495.29.5, for CUDA 11.5
CUDA driver 11.5

Libraries: 
- CUBLAS: 11.10.1
- CURAND: 10.2.10
- CUFFT: 10.7.2
- CUSOLVER: 11.3.5
- CUSPARSE: 11.7.3
- CUPTI: 17.0.0
- NVML: 11.0.0+495.29.5
- CUDNN: 8.30.2 (for CUDA 11.5.0)
- CUTENSOR: 1.4.0 (for CUDA 11.5.0)

Toolchain:
- Julia: 1.7.2
- LLVM: 12.0.1
- 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
- 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

1 device:
  0: NVIDIA GeForce GTX 1060 (sm_61, 5.387 GiB / 5.936 GiB available)

Closing comment (2022-07-22T09:37:05Z): maybe related to #1363

How would that be related?
I can't reproduce this. Please run with JULIA_DEBUG=CUBLAS.