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CUDA.rand(Int64, m, n) can not be used when m or n is zero #2093

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ArrogantGao opened this issue Sep 25, 2023 · 0 comments · Fixed by #2098
Closed

CUDA.rand(Int64, m, n) can not be used when m or n is zero #2093

ArrogantGao opened this issue Sep 25, 2023 · 0 comments · Fixed by #2098
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bug Something isn't working

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@ArrogantGao
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Describe the bug

Hi, I found a bug of CUDA.rand(Int64, m, n) function, it can not accept m or n equals to zero.

To reproduce

The Minimal Working Example (MWE) for this bug:

julia> using CUDA

julia> A = CuArray(rand(Int64, 0, 1))
0×1 CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}

julia> A = CUDA.rand(Int64, 0, 1)
ERROR: ArgumentError: Grid dimensions should be non-null
Stacktrace:
  [1] #launch#862
    @ ~/.julia/packages/CUDA/35NC6/lib/cudadrv/execution.jl:57 [inlined]
  [2] #868
    @ ~/.julia/packages/CUDA/35NC6/lib/cudadrv/execution.jl:136 [inlined]
  [3] macro expansion
    @ ~/.julia/packages/CUDA/35NC6/lib/cudadrv/execution.jl:95 [inlined]
  [4] macro expansion
    @ ./none:0 [inlined]
  [5] convert_arguments
    @ ./none:0 [inlined]
  [6] #cudacall#867
    @ ~/.julia/packages/CUDA/35NC6/lib/cudadrv/execution.jl:135 [inlined]
  [7] cudacall
    @ ~/.julia/packages/CUDA/35NC6/lib/cudadrv/execution.jl:134 [inlined]
  [8] macro expansion
    @ ~/.julia/packages/CUDA/35NC6/src/compiler/execution.jl:219 [inlined]
  [9] macro expansion
    @ ./none:0 [inlined]
 [10] #call#1045
    @ ./none:0 [inlined]
 [11] call
    @ ./none:0 [inlined]
 [12] #_#1060
    @ ~/.julia/packages/CUDA/35NC6/src/compiler/execution.jl:340 [inlined]
 [13] HostKernel
    @ ~/.julia/packages/CUDA/35NC6/src/compiler/execution.jl:339 [inlined]
 [14] rand!(rng::CUDA.RNG, A::CuArray{Int64, 2, CUDA.Mem.DeviceBuffer})
    @ CUDA ~/.julia/packages/CUDA/35NC6/src/random.jl:71
 [15] rand!(A::CuArray{Int64, 2, CUDA.Mem.DeviceBuffer})
    @ CUDA ~/.julia/packages/CUDA/35NC6/src/random.jl:297
 [16] rand(T::Type, dim1::Int64, dims::Int64)
    @ CUDA ~/.julia/packages/CUDA/35NC6/src/random.jl:311
 [17] top-level scope
    @ REPL[4]:1
 [18] top-level scope
    @ ~/.julia/packages/CUDA/35NC6/src/initialization.jl:190
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git-tree-sha1 = "45e428421666073eab6f2da5c9d310d99bb12f9b"
uuid = "189a3867-3050-52da-a836-e630ba90ab69"
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 = "30449ee12237627992a99d5e30ae63e4d78cd24a"
uuid = "6c6a2e73-6563-6170-7368-637461726353"
version = "1.2.0"

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

[[deps.SimpleBufferStream]]
git-tree-sha1 = "874e8867b33a00e784c8a7e4b60afe9e037b74e1"
uuid = "777ac1f9-54b0-4bf8-805c-2214025038e7"
version = "1.1.0"

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

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

[[deps.SpecialFunctions]]
deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
git-tree-sha1 = "7beb031cf8145577fbccacd94b8a8f4ce78428d3"
uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
version = "2.3.0"
weakdeps = ["ChainRulesCore"]

    [deps.SpecialFunctions.extensions]
    SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"

[[deps.StaticArrays]]
deps = ["LinearAlgebra", "Random", "StaticArraysCore"]
git-tree-sha1 = "9cabadf6e7cd2349b6cf49f1915ad2028d65e881"
uuid = "90137ffa-7385-5640-81b9-e52037218182"
version = "1.6.2"
weakdeps = ["Statistics"]

    [deps.StaticArrays.extensions]
    StaticArraysStatisticsExt = "Statistics"

[[deps.StaticArraysCore]]
git-tree-sha1 = "36b3d696ce6366023a0ea192b4cd442268995a0d"
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version = "1.4.2"

[[deps.Statistics]]
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[[deps.SuiteSparse_jll]]
deps = ["Artifacts", "Libdl", "Pkg", "libblastrampoline_jll"]
uuid = "bea87d4a-7f5b-5778-9afe-8cc45184846c"
version = "5.10.1+6"

[[deps.TOML]]
deps = ["Dates"]
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
version = "1.0.3"

[[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"
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[[deps.TranscodingStreams]]
deps = ["Random", "Test"]
git-tree-sha1 = "9a6ae7ed916312b41236fcef7e0af564ef934769"
uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
version = "0.9.13"

[[deps.TropicalNumbers]]
git-tree-sha1 = "3574309a7f8a8976bc91552e3ff41b627524cba2"
uuid = "b3a74e9c-7526-4576-a4eb-79c0d4c32334"
version = "0.6.0"

[[deps.URIs]]
git-tree-sha1 = "b7a5e99f24892b6824a954199a45e9ffcc1c70f0"
uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
version = "1.5.0"

[[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+0"

[[deps.gh_cli_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
git-tree-sha1 = "ffd2da4dfa88bbdc1f11694cebb3da96a888a275"
uuid = "5d31d589-30fb-542f-b82d-10325e863e38"
version = "2.2.0+0"

[[deps.libblastrampoline_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
version = "5.8.0+0"

[[deps.nghttp2_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
version = "1.48.0+0"

[[deps.p7zip_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"
version = "17.4.0+0"

Expected behavior

As shown in the MWE, other CuMatrix{T} are fine will 0 as dims.

Version info

Details on Julia:

Julia Version 1.9.3
Commit bed2cd540a1 (2023-08-24 14:43 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 128 × Intel(R) Xeon(R) Platinum 8378A CPU @ 3.00GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, icelake-server)
  Threads: 1 on 128 virtual cores
Environment:
  LD_LIBRARY_PATH = /opt/nvidia/hpc_sdk/Linux_x86_64/23.5/compilers/lib:
  JULIA_PKG_SERVER = https://mirrors.ustc.edu.cn/julia
  JULIA_EDITOR = code
  JULIA_NUM_THREADS =

Details on CUDA:

CUDA runtime 12.2, artifact installation
CUDA driver 12.1
NVIDIA driver 530.30.2

CUDA libraries: 
- CUBLAS: 12.2.5
- CURAND: 10.3.3
- CUFFT: 11.0.8
- CUSOLVER: 11.5.2
- CUSPARSE: 12.1.2
- CUPTI: 20.0.0
- NVML: 12.0.0+530.30.2

Julia packages: 
- CUDA: 5.0.0
- CUDA_Driver_jll: 0.6.0+3
- CUDA_Runtime_jll: 0.9.2+0

Toolchain:
- Julia: 1.9.3
- LLVM: 14.0.6
- 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, 7.3, 7.4, 7.5
- Device capability support: sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75, sm_80, sm_86

6 devices:
  0: NVIDIA A800 80GB PCIe (sm_80, 77.509 GiB / 80.000 GiB available)
  1: NVIDIA A800 80GB PCIe (sm_80, 79.189 GiB / 80.000 GiB available)
  2: NVIDIA A800 80GB PCIe (sm_80, 79.189 GiB / 80.000 GiB available)
  3: NVIDIA A800 80GB PCIe (sm_80, 79.070 GiB / 80.000 GiB available)
  4: NVIDIA A800 80GB PCIe (sm_80, 79.189 GiB / 80.000 GiB available)
  5: NVIDIA A800 80GB PCIe (sm_80, 79.166 GiB / 80.000 GiB available)
@ArrogantGao ArrogantGao added the bug Something isn't working label Sep 25, 2023
@maleadt maleadt mentioned this issue Sep 26, 2023
Merged
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Handle and test zero-size inputs to RNGs. JuliaGPU/CUDA.jl
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@ArrogantGao