Open
Description
openedon Mar 3, 2024
Describe the bug
When taking the 2-norm (or any p-norm apart from 1- and Inf-norm) of a CuArray view, the implementation errors due to scalar iteration. Interestingly, 1-norm and Inf-norm don't result in an error.
To reproduce
The Minimal Working Example (MWE) for this bug:
julia> using CUDA
julia> CUDA.allowscalar(false)
julia> F = CUDA.rand(Float64, 10, 10);
julia> using LinearAlgebra
julia> norm(F, 1)
52.56442439112135
julia> norm(F, Inf)
0.9987327733895317
julia> norm(F, 2)
5.909233996256053
julia> F_v = @view F[2:end-1,2:end-1];
julia> norm(F_v, 1)
33.28196660190136
julia> norm(F_v, Inf)
0.986534225435441
julia> norm(F_v, 2)
ERROR: Scalar indexing is disallowed.
Invocation of getindex resulted in scalar indexing of a GPU array.
This is typically caused by calling an iterating implementation of a method.
Such implementations *do not* execute on the GPU, but very slowly on the CPU,
and therefore should be avoided.
If you want to allow scalar iteration, use `allowscalar` or `@allowscalar`
to enable scalar iteration globally or for the operations in question.
Stacktrace:
[1] error(s::String)
@ Base ./error.jl:35
[2] errorscalar(op::String)
@ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:155
[3] _assertscalar(op::String, behavior::GPUArraysCore.ScalarIndexing)
@ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:128
[4] assertscalar(op::String)
@ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:116
[5] getindex(A::CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, I::Int64)
@ GPUArrays ~/.julia/packages/GPUArrays/Hd5Sk/src/host/indexing.jl:48
[6] scalar_getindex
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/indexing.jl:34 [inlined]
[7] _getindex
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/indexing.jl:17 [inlined]
[8] getindex
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/indexing.jl:15 [inlined]
[9] getindex
@ ./subarray.jl:288 [inlined]
[10] _getindex
@ ./abstractarray.jl:1341 [inlined]
[11] getindex
@ ./abstractarray.jl:1291 [inlined]
[12] iterate
@ ./abstractarray.jl:1217 [inlined]
[13] iterate
@ ./abstractarray.jl:1215 [inlined]
[14] generic_norm2(x::SubArray{Float64, 2, CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, Tuple{UnitRange{Int64}, UnitRange{Int64}}, false})
@ LinearAlgebra /scratch-1/soft/julia/julia-1.10.1/share/julia/stdlib/v1.10/LinearAlgebra/src/generic.jl:465
[15] norm2
@ /scratch-1/soft/julia/julia-1.10.1/share/julia/stdlib/v1.10/LinearAlgebra/src/generic.jl:529 [inlined]
[16] norm(itr::SubArray{Float64, 2, CuArray{Float64, 2, CUDA.Mem.DeviceBuffer}, Tuple{UnitRange{Int64}, UnitRange{Int64}}, false}, p::Int64)
@ LinearAlgebra /scratch-1/soft/julia/julia-1.10.1/share/julia/stdlib/v1.10/LinearAlgebra/src/generic.jl:598
[17] top-level scope
@ REPL[61]:1
[18] top-level scope
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version = "1.2.2"
[[deps.Requires]]
deps = ["UUIDs"]
git-tree-sha1 = "838a3a4188e2ded87a4f9f184b4b0d78a1e91cb7"
uuid = "ae029012-a4dd-5104-9daa-d747884805df"
version = "1.3.0"
[[deps.SHA]]
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
version = "0.7.0"
[[deps.Scratch]]
deps = ["Dates"]
git-tree-sha1 = "3bac05bc7e74a75fd9cba4295cde4045d9fe2386"
uuid = "6c6a2e73-6563-6170-7368-637461726353"
version = "1.2.1"
[[deps.SentinelArrays]]
deps = ["Dates", "Random"]
git-tree-sha1 = "0e7508ff27ba32f26cd459474ca2ede1bc10991f"
uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
version = "1.4.1"
[[deps.Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
[[deps.Sockets]]
uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
[[deps.SortingAlgorithms]]
deps = ["DataStructures"]
git-tree-sha1 = "66e0a8e672a0bdfca2c3f5937efb8538b9ddc085"
uuid = "a2af1166-a08f-5f64-846c-94a0d3cef48c"
version = "1.2.1"
[[deps.SparseArrays]]
deps = ["Libdl", "LinearAlgebra", "Random", "Serialization", "SuiteSparse_jll"]
uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
version = "1.10.0"
[[deps.StaticArrays]]
deps = ["LinearAlgebra", "PrecompileTools", "Random", "StaticArraysCore"]
git-tree-sha1 = "bf074c045d3d5ffd956fa0a461da38a44685d6b2"
uuid = "90137ffa-7385-5640-81b9-e52037218182"
version = "1.9.3"
[deps.StaticArrays.extensions]
StaticArraysChainRulesCoreExt = "ChainRulesCore"
StaticArraysStatisticsExt = "Statistics"
[deps.StaticArrays.weakdeps]
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
[[deps.StaticArraysCore]]
git-tree-sha1 = "36b3d696ce6366023a0ea192b4cd442268995a0d"
uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
version = "1.4.2"
[[deps.Statistics]]
deps = ["LinearAlgebra", "SparseArrays"]
uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
version = "1.10.0"
[[deps.StringManipulation]]
deps = ["PrecompileTools"]
git-tree-sha1 = "a04cabe79c5f01f4d723cc6704070ada0b9d46d5"
uuid = "892a3eda-7b42-436c-8928-eab12a02cf0e"
version = "0.3.4"
[[deps.SuiteSparse_jll]]
deps = ["Artifacts", "Libdl", "libblastrampoline_jll"]
uuid = "bea87d4a-7f5b-5778-9afe-8cc45184846c"
version = "7.2.1+1"
[[deps.TOML]]
deps = ["Dates"]
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
version = "1.0.3"
[[deps.TableTraits]]
deps = ["IteratorInterfaceExtensions"]
git-tree-sha1 = "c06b2f539df1c6efa794486abfb6ed2022561a39"
uuid = "3783bdb8-4a98-5b6b-af9a-565f29a5fe9c"
version = "1.0.1"
[[deps.Tables]]
deps = ["DataAPI", "DataValueInterfaces", "IteratorInterfaceExtensions", "LinearAlgebra", "OrderedCollections", "TableTraits"]
git-tree-sha1 = "cb76cf677714c095e535e3501ac7954732aeea2d"
uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
version = "1.11.1"
[[deps.Tar]]
deps = ["ArgTools", "SHA"]
uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"
version = "1.10.0"
[[deps.Test]]
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[[deps.TimerOutputs]]
deps = ["ExprTools", "Printf"]
git-tree-sha1 = "f548a9e9c490030e545f72074a41edfd0e5bcdd7"
uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
version = "0.5.23"
[[deps.UUIDs]]
deps = ["Random", "SHA"]
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
[[deps.Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
[[deps.UnsafeAtomics]]
git-tree-sha1 = "6331ac3440856ea1988316b46045303bef658278"
uuid = "013be700-e6cd-48c3-b4a1-df204f14c38f"
version = "0.2.1"
[[deps.UnsafeAtomicsLLVM]]
deps = ["LLVM", "UnsafeAtomics"]
git-tree-sha1 = "323e3d0acf5e78a56dfae7bd8928c989b4f3083e"
uuid = "d80eeb9a-aca5-4d75-85e5-170c8b632249"
version = "0.1.3"
[[deps.Zlib_jll]]
deps = ["Libdl"]
uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
version = "1.2.13+1"
[[deps.libblastrampoline_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
version = "5.8.0+1"
[[deps.nghttp2_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
version = "1.52.0+1"
[[deps.p7zip_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"
version = "17.4.0+2"
Expected behavior
The 2-norm of a CuArray view should behave similarly to other norms, calling CUDA implementation.
Version info
Details on Julia:
julia> versioninfo()
Julia Version 1.10.1
Commit 7790d6f0641 (2024-02-13 20:41 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 32 × AMD EPYC 7282 16-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-15.0.7 (ORCJIT, znver2)
Threads: 4 default, 0 interactive, 2 GC (on 32 virtual cores)
Environment:
JULIA_HDF5_PATH = /scratch-1/soft/spack/opt/spack/linux-ubuntu20.04-zen2/gcc-9.4.0/hdf5-1.14.3-ldtujwyb3rbhtch7y7yjh3njta67pkj3
JULIA_LOAD_PATH = :/scratch-1/julia_prefs/
JULIA_NUM_THREADS = 4
Details on CUDA:
# please post the output of:
julia> CUDA.versioninfo()
CUDA runtime 12.3, local installation
CUDA driver 12.3
NVIDIA driver 545.23.8
CUDA libraries:
- CUBLAS: 12.3.4
- CURAND: 10.3.4
- CUFFT: 11.0.12
- CUSOLVER: 11.5.4
- CUSPARSE: 12.2.0
- CUPTI: 21.0.0
- NVML: 12.0.0+545.23.8
Julia packages:
- CUDA: 5.2.0
- CUDA_Driver_jll: 0.7.0+1
- CUDA_Runtime_jll: 0.11.1+0
- CUDA_Runtime_Discovery: 0.2.3
Toolchain:
- Julia: 1.10.1
- LLVM: 15.0.7
Preferences:
- CUDA_Runtime_jll.version: local
8 devices:
0: NVIDIA A100-SXM4-40GB (sm_80, 38.893 GiB / 40.000 GiB available)
1: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available)
2: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available)
3: NVIDIA A100-SXM4-40GB (sm_80, 34.860 GiB / 40.000 GiB available)
4: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available)
5: NVIDIA A100-SXM4-40GB (sm_80, 34.860 GiB / 40.000 GiB available)
6: NVIDIA A100-SXM4-40GB (sm_80, 34.860 GiB / 40.000 GiB available)
7: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available)
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