Describe the bug
Some methods of GPUArrays related to sparse arrays are missing for CuSparseMatrixCOO and CuSparseMatrixBSR, whereas they exist for CuSparseMatrixCSC and CuSparseMatrixCSR.
To reproduce
The Minimal Working Example (MWE) for this bug:
using CUDA, CUDA.CUSPARSE
using GPUArrays
using SparseArrays
GPUArrays.sparse_array_type(CuSparseMatrixCSC(spzeros(1, 1))) == CuSparseMatrixCSC # true, correct behavior
GPUArrays.sparse_array_type(CuSparseMatrixCOO(spzeros(1, 1))) == CuSparseMatrixCOO # false, missing implem
Manifest.toml
Status `~/.julia/environments/v1.11/Manifest.toml`
[47edcb42] ADTypes v1.21.0
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[66dad0bd] AliasTables v1.1.3
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⌃ [4fba245c] ArrayInterface v7.22.0
[a9b6321e] Atomix v1.1.2
[67c07d97] Automa v1.1.0
[13072b0f] AxisAlgorithms v1.1.0
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[ab4f0b2a] BFloat16s v0.6.1
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[d1d4a3ce] BitFlags v0.1.9
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[fa961155] CEnum v0.5.0
[2a0fbf3d] CPUSummary v0.2.7
[96374032] CRlibm v1.0.2
⌃ [336ed68f] CSV v0.10.15
⌃ [052768ef] CUDA v5.9.6
[1af6417a] CUDA_Runtime_Discovery v1.0.0
[d360d2e6] ChainRulesCore v1.26.0
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⌃ [f0e56b4a] ConcurrentUtilities v2.5.0
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[187b0558] ConstructionBase v1.6.0
[d38c429a] Contour v0.6.3
[adafc99b] CpuId v0.3.1
[a8cc5b0e] Crayons v4.1.1
[9a962f9c] DataAPI v1.16.0
[a93c6f00] DataFrames v1.8.1
[864edb3b] DataStructures v0.19.3
[e2d170a0] DataValueInterfaces v1.0.0
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[8bb1440f] DelimitedFiles v1.9.1
[163ba53b] DiffResults v1.1.0
[b552c78f] DiffRules v1.15.1
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[31c24e10] Distributions v0.25.123
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⌃ [7da242da] Enzyme v0.13.129
[f151be2c] EnzymeCore v0.8.18
[429591f6] ExactPredicates v2.2.9
[460bff9d] ExceptionUnwrapping v0.1.11
[e2ba6199] ExprTools v0.1.10
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[411431e0] Extents v0.1.6
[c87230d0] FFMPEG v0.4.5
[b86e33f2] FFTA v0.3.1
[9aa1b823] FastClosures v0.3.2
[5789e2e9] FileIO v1.18.0
[8fc22ac5] FilePaths v0.9.0
[48062228] FilePathsBase v0.9.24
[1a297f60] FillArrays v1.16.0
[53c48c17] FixedPointNumbers v0.8.5
[1fa38f19] Format v1.3.7
[f6369f11] ForwardDiff v1.3.2
[b38be410] FreeType v4.1.1
[663a7486] FreeTypeAbstraction v0.10.8
[d9f16b24] Functors v0.5.2
[0c68f7d7] GPUArrays v11.4.1
[46192b85] GPUArraysCore v0.2.0
[61eb1bfa] GPUCompiler v1.8.2
[096a3bc2] GPUToolbox v1.0.0
⌃ [28b8d3ca] GR v0.73.22
[5c1252a2] GeometryBasics v0.5.10
[3955a311] GridLayoutBase v0.11.2
[42e2da0e] Grisu v1.0.2
⌃ [cd3eb016] HTTP v1.10.19
[076d061b] HashArrayMappedTries v0.2.0
[34004b35] HypergeometricFunctions v0.3.28
⌃ [7073ff75] IJulia v1.34.1
[615f187c] IfElse v0.1.1
[2803e5a7] ImageAxes v0.6.12
[c817782e] ImageBase v0.1.7
[a09fc81d] ImageCore v0.10.5
[82e4d734] ImageIO v0.6.9
[bc367c6b] ImageMetadata v0.9.10
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[8197267c] IntervalSets v0.7.13
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[82899510] IteratorInterfaceExtensions v1.0.0
[1019f520] JLFzf v0.1.11
[692b3bcd] JLLWrappers v1.7.1
[682c06a0] JSON v1.4.0
[0f8b85d8] JSON3 v1.14.3
[b835a17e] JpegTurbo v0.1.6
⌃ [63c18a36] KernelAbstractions v0.9.39
[5ab0869b] KernelDensity v0.6.11
[929cbde3] LLVM v9.4.6
[8b046642] LLVMLoopInfo v1.0.0
[b964fa9f] LaTeXStrings v1.4.0
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[8cdb02fc] LazyModules v0.3.1
[2ab3a3ac] LogExpFunctions v0.3.29
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[b2108857] Lux v1.31.3
[bb33d45b] LuxCore v1.5.3
[82251201] LuxLib v1.15.4
[7e8f7934] MLDataDevices v1.17.4
[1914dd2f] MacroTools v0.5.16
⌃ [ee78f7c6] Makie v0.24.8
[dbb5928d] MappedArrays v0.4.3
[0a4f8689] MathTeXEngine v0.6.7
⌃ [739be429] MbedTLS v1.1.9
[442fdcdd] Measures v0.3.3
[e1d29d7a] Missings v1.2.0
[e94cdb99] MosaicViews v0.3.4
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[5432bcbf] PaddedViews v0.5.12
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[eebad327] PkgVersion v0.3.3
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⌃ [91a5bcdd] Plots v1.41.5
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[2dfb63ee] PooledArrays v1.4.3
⌅ [aea7be01] PrecompileTools v1.2.1
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⌃ [08abe8d2] PrettyTables v3.1.2
[27ebfcd6] Primes v0.5.7
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⌃ [43287f4e] PtrArrays v1.3.0
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[c84ed2f1] Ratios v0.4.5
⌃ [3c362404] Reactant v0.2.213
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[01d81517] RecipesPipeline v0.6.12
[189a3867] Reexport v1.2.2
[05181044] RelocatableFolders v1.0.1
[ae029012] Requires v1.3.1
[79098fc4] Rmath v0.9.0
[5eaf0fd0] RoundingEmulator v0.2.1
[fdea26ae] SIMD v3.7.2
[431bcebd] SciMLPublic v1.0.1
⌃ [7e506255] ScopedValues v1.5.0
[6c6a2e73] Scratch v1.3.0
[91c51154] SentinelArrays v1.4.9
[efcf1570] Setfield v1.1.2
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⌃ [276daf66] SpecialFunctions v2.6.1
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[cae243ae] StackViews v0.1.2
[aedffcd0] Static v1.3.1
⌃ [90137ffa] StaticArrays v1.9.16
[1e83bf80] StaticArraysCore v1.4.4
[10745b16] Statistics v1.11.1
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⌃ [892a3eda] StringManipulation v0.4.2
[09ab397b] StructArrays v0.7.2
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⌃ [ec057cc2] StructUtils v2.6.2
[3783bdb8] TableTraits v1.0.1
[bd369af6] Tables v1.12.1
[62fd8b95] TensorCore v0.1.1
⌃ [731e570b] TiffImages v0.11.6
[e689c965] Tracy v0.1.6
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[41fe7b60] Unzip v0.2.0
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[ea10d353] WeakRefStrings v1.4.2
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⌃ [4ee394cb] CUDA_Driver_jll v13.1.0+2
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⌅ [d2c73de3] GR_jll v0.73.22+0
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⌃ [7746bdde] Glib_jll v2.86.2+0
[3b182d85] Graphite2_jll v1.3.15+0
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[e98f9f5b] NVTX_jll v3.2.2+0
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⌃ [e99dba38] Qt6Wayland_jll v6.8.2+2
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[f50d1b31] Rmath_jll v0.5.1+0
[a44049a8] Vulkan_Loader_jll v1.3.243+0
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[f67eecfb] Xorg_libICE_jll v1.1.2+0
[c834827a] Xorg_libSM_jll v1.2.6+0
⌃ [4f6342f7] Xorg_libX11_jll v1.8.12+0
[0c0b7dd1] Xorg_libXau_jll v1.0.13+0
[935fb764] Xorg_libXcursor_jll v1.2.4+0
[a3789734] Xorg_libXdmcp_jll v1.1.6+0
⌃ [1082639a] Xorg_libXext_jll v1.3.7+0
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⌃ [ec84b674] Xorg_libXrandr_jll v1.5.5+0
[ea2f1a96] Xorg_libXrender_jll v0.9.12+0
[a65dc6b1] Xorg_libpciaccess_jll v0.18.1+0
[c7cfdc94] Xorg_libxcb_jll v1.17.1+0
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[e920d4aa] Xorg_xcb_util_cursor_jll v0.1.6+0
[12413925] Xorg_xcb_util_image_jll v0.4.1+0
[2def613f] Xorg_xcb_util_jll v0.4.1+0
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⌃ [b53b4c65] libpng_jll v1.6.54+0
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[a9144af2] libsodium_jll v1.0.21+0
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[c5f90fcd] libwebp_jll v1.6.0+0
[009596ad] mtdev_jll v1.1.7+0
⌅ [1270edf5] x264_jll v10164.0.1+0
[dfaa095f] x265_jll v4.1.0+0
[d8fb68d0] xkbcommon_jll v1.13.0+0
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[ade2ca70] Dates v1.11.0
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[7b1f6079] FileWatching v1.11.0
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[4af54fe1] LazyArtifacts v1.11.0
[b27032c2] LibCURL v0.6.4
[76f85450] LibGit2 v1.11.0
[8f399da3] Libdl v1.11.0
[37e2e46d] LinearAlgebra v1.11.0
[56ddb016] Logging v1.11.0
[d6f4376e] Markdown v1.11.0
[a63ad114] Mmap v1.11.0
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[ea8e919c] SHA v0.7.0
[9e88b42a] Serialization v1.11.0
[1a1011a3] SharedArrays v1.11.0
[6462fe0b] Sockets v1.11.0
[2f01184e] SparseArrays v1.11.0
[f489334b] StyledStrings v1.11.0
[4607b0f0] SuiteSparse
[fa267f1f] TOML v1.0.3
[a4e569a6] Tar v1.10.0
[8dfed614] Test v1.11.0
[cf7118a7] UUIDs v1.11.0
[4ec0a83e] Unicode v1.11.0
[e66e0078] CompilerSupportLibraries_jll v1.1.1+0
[deac9b47] LibCURL_jll v8.6.0+0
[e37daf67] LibGit2_jll v1.7.2+0
[29816b5a] LibSSH2_jll v1.11.0+1
[c8ffd9c3] MbedTLS_jll v2.28.6+0
[14a3606d] MozillaCACerts_jll v2023.12.12
[4536629a] OpenBLAS_jll v0.3.27+1
[05823500] OpenLibm_jll v0.8.5+0
[efcefdf7] PCRE2_jll v10.42.0+1
[bea87d4a] SuiteSparse_jll v7.7.0+0
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.59.0+0
[3f19e933] p7zip_jll v17.4.0+2
Expected behavior
The following methods should be implemented:
# for COO
GPUArrays.sparse_array_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCOO
GPUArrays.sparse_array_type(::Type{<:CuSparseMatrixCSR}) = CuSparseMatrixCOO
GPUArrays.csc_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCSC
GPUArrays.csr_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCSR
GPUArrays.coo_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCOO
# for BSR
# ...The appropriate location for them is
|
GPUArrays.sparse_array_type(sa::CuSparseMatrixCSC) = CuSparseMatrixCSC |
|
GPUArrays.sparse_array_type(::Type{<:CuSparseMatrixCSC}) = CuSparseMatrixCSC |
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GPUArrays.sparse_array_type(sa::CuSparseMatrixCSR) = CuSparseMatrixCSR |
|
GPUArrays.sparse_array_type(::Type{<:CuSparseMatrixCSR}) = CuSparseMatrixCSR |
|
GPUArrays.sparse_array_type(sa::CuSparseVector) = CuSparseVector |
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GPUArrays.sparse_array_type(::Type{<:CuSparseVector}) = CuSparseVector |
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GPUArrays.dense_array_type(sa::CuSparseVector) = CuArray |
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GPUArrays.dense_array_type(::Type{<:CuSparseVector}) = CuArray |
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GPUArrays.dense_array_type(sa::CuSparseMatrixCSC) = CuArray |
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GPUArrays.dense_array_type(::Type{<:CuSparseMatrixCSC}) = CuArray |
|
GPUArrays.dense_array_type(sa::CuSparseMatrixCSR) = CuArray |
|
GPUArrays.dense_array_type(::Type{<:CuSparseMatrixCSR}) = CuArray |
|
|
|
GPUArrays.csc_type(sa::CuSparseMatrixCSR) = CuSparseMatrixCSC |
|
GPUArrays.csr_type(sa::CuSparseMatrixCSC) = CuSparseMatrixCSR |
|
GPUArrays.coo_type(sa::Union{CuSparseMatrixCSR, Transpose{<:Any,<:CuSparseMatrixCSR}, Adjoint{<:Any,<:CuSparseMatrixCSR}}) = CuSparseMatrixCOO |
|
GPUArrays.coo_type(sa::Union{CuSparseMatrixCSC, Transpose{<:Any,<:CuSparseMatrixCSC}, Adjoint{<:Any,<:CuSparseMatrixCSC}}) = CuSparseMatrixCOO |
|
GPUArrays.coo_type(::Type{T}) where {T<:Union{CuSparseMatrixCSR, Transpose{<:Any,<:CuSparseMatrixCSR}, Adjoint{<:Any,<:CuSparseMatrixCSR}}} = CuSparseMatrixCOO |
|
GPUArrays.coo_type(::Type{T}) where {T<:Union{CuSparseMatrixCSC, Transpose{<:Any,<:CuSparseMatrixCSC}, Adjoint{<:Any,<:CuSparseMatrixCSC}}} = CuSparseMatrixCOO |
Version info
Details on Julia:
# please post the output of: versioninfo()
Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 2 × Intel(R) Xeon(R) CPU @ 2.00GHz
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, skylake-avx512)
Threads: 2 default, 0 interactive, 1 GC (on 2 virtual cores)
Environment:
LD_LIBRARY_PATH = /usr/lib64-nvidia
JULIA_NUM_THREADS = auto
Details on CUDA:
# please post the output of: CUDA.versioninfo()
CUDA toolchain:
- runtime 12.8, local installation
- driver 580.82.7 for 13.1
- compiler 12.9
CUDA libraries:
- CUBLAS: 12.8.4
- CURAND: 10.3.9
- CUFFT: 11.3.3
- CUSOLVER: 11.7.3
- CUSPARSE: 12.5.8
- CUPTI: 2025.1.1 (API 12.8.0)
- NVML: 13.0.0+580.82.7
Julia packages:
- CUDA: 5.9.6
- GPUArrays: 11.4.1
- GPUCompiler: 1.8.2
- KernelAbstractions: 0.9.39
- CUDA_Driver_jll: 13.1.0+2
- CUDA_Compiler_jll: 0.4.1+1
- CUDA_Runtime_jll: 0.19.2+0
- CUDA_Runtime_Discovery: 1.0.0
Toolchain:
- Julia: 1.11.5
- LLVM: 16.0.6
Preferences:
- CUDA_Runtime_jll.version: 12.8.1
- CUDA_Runtime_jll.local: true
1 device:
0: Tesla T4 (sm_75, 14.560 GiB / 15.000 GiB available)
Additional context
Tested on a Colab notebook (hence the weird deps).
Describe the bug
Some methods of
GPUArraysrelated to sparse arrays are missing forCuSparseMatrixCOOandCuSparseMatrixBSR, whereas they exist forCuSparseMatrixCSCandCuSparseMatrixCSR.To reproduce
The Minimal Working Example (MWE) for this bug:
Manifest.toml
Expected behavior
The following methods should be implemented:
The appropriate location for them is
CUDA.jl/lib/cusparse/array.jl
Lines 108 to 126 in 153f819
Version info
Details on Julia:
Details on CUDA:
Additional context
Tested on a Colab notebook (hence the weird deps).