JuliaGPU/CUDA.jl

[CUSPARSE] error in conversion of CuSparseMatrix{Int} to dense matrices

Open

#1664 aperta il 6 nov 2022

Vedi su GitHub
 (1 commento) (0 reazioni) (0 assegnatari)Julia (274 fork)batch import
bugcuda librariesgood first issue

Metriche repository

Star
 (1408 star)
Metriche merge PR
 (Merge medio 5g 5h) (16 PR mergiate in 30 g)

Descrizione

Cusparse matrices with float eltype are correctly converted to dense arrays:

julia> using CUDA, SparseArrays

julia> x = sparse([1, 2], [1, 2], [10.0, 20.0]) |> cu
2×2 CuSparseMatrixCSC{Float32, Int32} with 2 stored entries:
 10.0    ⋅ 
   ⋅   20.0

julia> CuArray(x)
2×2 CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}:
 10.0   0.0
  0.0  20.0

julia> Array(x)
2×2 Matrix{Float32}:
 10.0   0.0
  0.0  20.0

With Int eltype instead, we have the following StackOverflow errors:

julia> x = sparse([1,2], [1,2], [10, 20]) |> cu
2×2 CuSparseMatrixCSC{Int64, Int32} with 2 stored entries:
 10   ⋅
  ⋅  20

julia> CuArray(x)
ERROR: StackOverflowError:
Stacktrace:
     [1] macro expansion
       @ ~/.julia/dev/CUDA/lib/cudadrv/libcuda.jl:3136 [inlined]
     [2] cuMemAllocAsync(dptr::Base.RefValue{CuPtr{Nothing}}, bytesize::Int64, hStream::CuStream)
       @ CUDA ~/.julia/dev/CUDA/lib/utils/call.jl:26
     [3] #alloc#1
       @ ~/.julia/dev/CUDA/lib/cudadrv/memory.jl:83 [inlined]
     [4] actual_alloc(bytes::Int64; async::Bool, stream::CuStream)
       @ CUDA ~/.julia/dev/CUDA/src/pool.jl:39
     [5] macro expansion
       @ ~/.julia/dev/CUDA/src/pool.jl:222 [inlined]
     [6] macro expansion
       @ ./timing.jl:382 [inlined]
     [7] #_alloc#164
       @ ~/.julia/dev/CUDA/src/pool.jl:303 [inlined]
     [8] #alloc#163
       @ ~/.julia/dev/CUDA/src/pool.jl:289 [inlined]
     [9] alloc
       @ ~/.julia/dev/CUDA/src/pool.jl:283 [inlined]
    [10] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(#unused#::UndefInitializer, dims::Tuple{Int64, Int64})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:85
    [11] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:334
    [12] (CuArray{Int64, 2})(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:339
    [13] copyto!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA.CUSPARSE ~/.julia/dev/CUDA/lib/cusparse/conversions.jl:596
    [14] copyto_axcheck!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./abstractarray.jl:1127
    [15] Matrix{Int64}(x::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:626
    [16] (Array{Int64})(A::CuSparseMatrixCSC{Int64, Int32})
       @ Core ./boot.jl:484
    [17] convert(#unused#::Type{Array{Int64}}, a::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:617
    [18] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:335
--- the last 7 lines are repeated 11423 more times ---
 [79980] (CuArray{Int64, 2})(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:339
 [79981] copyto!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA.CUSPARSE ~/.julia/dev/CUDA/lib/cusparse/conversions.jl:596
 [79982] copyto_axcheck!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./abstractarray.jl:1127
 [79983] Matrix{Int64}(x::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:626

julia> Array(x)
ERROR: StackOverflowError:
Stacktrace:
     [1] macro expansion
       @ ~/.julia/dev/CUDA/lib/cudadrv/libcuda.jl:3136 [inlined]
     [2] cuMemAllocAsync(dptr::Base.RefValue{CuPtr{Nothing}}, bytesize::Int64, hStream::CuStream)
       @ CUDA ~/.julia/dev/CUDA/lib/utils/call.jl:26
     [3] #alloc#1
       @ ~/.julia/dev/CUDA/lib/cudadrv/memory.jl:83 [inlined]
     [4] actual_alloc(bytes::Int64; async::Bool, stream::CuStream)
       @ CUDA ~/.julia/dev/CUDA/src/pool.jl:39
     [5] macro expansion
       @ ~/.julia/dev/CUDA/src/pool.jl:222 [inlined]
     [6] macro expansion
       @ ./timing.jl:382 [inlined]
     [7] #_alloc#164
       @ ~/.julia/dev/CUDA/src/pool.jl:303 [inlined]
     [8] #alloc#163
       @ ~/.julia/dev/CUDA/src/pool.jl:289 [inlined]
     [9] alloc
       @ ~/.julia/dev/CUDA/src/pool.jl:283 [inlined]
    [10] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(#unused#::UndefInitializer, dims::Tuple{Int64, Int64})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:85
    [11] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:334
    [12] (CuArray{Int64, 2})(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:339
    [13] copyto!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA.CUSPARSE ~/.julia/dev/CUDA/lib/cusparse/conversions.jl:596
    [14] copyto_axcheck!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./abstractarray.jl:1127
    [15] Matrix{Int64}(x::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:626
    [16] (Array{Int64})(A::CuSparseMatrixCSC{Int64, Int32})
       @ Core ./boot.jl:484
    [17] convert(#unused#::Type{Array{Int64}}, a::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:617
    [18] CuArray{Int64, 2, CUDA.Mem.DeviceBuffer}(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:335
--- the last 7 lines are repeated 11423 more times ---
 [79980] (CuArray{Int64, 2})(xs::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA ~/.julia/dev/CUDA/src/array.jl:339
 [79981] copyto!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ CUDA.CUSPARSE ~/.julia/dev/CUDA/lib/cusparse/conversions.jl:596
 [79982] copyto_axcheck!(dest::Matrix{Int64}, src::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./abstractarray.jl:1127
 [79983] Matrix{Int64}(x::CuSparseMatrixCSC{Int64, Int32})
       @ Base ./array.jl:626

Same errors occur with SparseMatrixCSR and with both Int32 and Int64.

Tested on CUDA.jl master and the following versioninfo

julia> CUDA.versioninfo()
CUDA runtime 11.8, artifact installation
CUDA driver 11.6
NVIDIA driver 510.39.1

Libraries: 
- CUBLAS: 11.11.3
- CURAND: 10.3.0
- CUFFT: 10.9.0
- CUSOLVER: 11.4.1
- CUSPARSE: 11.7.5
- CUPTI: 18.0.0
- NVML: 11.0.0+510.39.1

Toolchain:
- Julia: 1.8.2
- LLVM: 13.0.1
- 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, 7.1, 7.2
- 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, sm_86

4 devices:
  0: Tesla V100-SXM2-32GB (sm_70, 2.550 GiB / 32.000 GiB available)
  1: Tesla V100-SXM2-32GB (sm_70, 21.359 GiB / 32.000 GiB available)
  2: Tesla V100-SXM2-32GB (sm_70, 28.537 GiB / 32.000 GiB available)
  3: Tesla V100-SXM2-32GB (sm_70, 9.699 GiB / 32.000 GiB available)

Guida contributor

Direzione di ricerca
Esamina la funzione copyto! per CuSparseMatrixCSC con tipi interi per identificare la ricorsione infinita.
Tech stack
julia
Dominio
backend
Tipo issue
Bug
DifficoltàQuanto dovrebbe essere impegnativa per un nuovo contributor.
3
Tempo stimatoTempo stimato per completare e verificare uno scope piccolo.
1-2 giorni
Stato attivitàQuanto è probabile che la issue sia ancora attiva e reviewable.
Attiva
ChiarezzaQuanto chiaramente la issue descrive problema, scope e risultato atteso.
Chiara
Prerequisiti
JuliaCUDA
Adatta ai principiantiQuanto la issue è adatta a contributor alla prima esperienza.
60