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2-norm for views of CuArray falls back to scalar indexing #2280

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utkinis opened this issue Mar 3, 2024 · 0 comments · May be fixed by #2302
Open

2-norm for views of CuArray falls back to scalar indexing #2280

utkinis opened this issue Mar 3, 2024 · 0 comments · May be fixed by #2302
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cuda array Stuff about CuArray. enhancement New feature or request good first issue Good for newcomers

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@utkinis
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utkinis commented Mar 3, 2024 •
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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
    @ ~/.julia/packages/CUDA/htRwP/src/initialization.jl:206
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[[deps.SHA]]
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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)
@utkinis utkinis added the bug Something isn't working label Mar 3, 2024
@maleadt maleadt added enhancement New feature or request cuda array Stuff about CuArray. and removed bug Something isn't working labels Mar 4, 2024
@luraess luraess mentioned this issue Mar 4, 2024
Open
@maleadt maleadt added the good first issue Good for newcomers label Mar 21, 2024
@sharanry sharanry linked a pull request Mar 22, 2024 that will close this issue
Draft
sharanry added a commit to sharanry/CUDA.jl that referenced this issue Mar 22, 2024
@sharanry
Add a dispatch for LinearAlgebra.norm2
0e2ef84 
`norm(@view x[..], 2)` was previously leading to a call of `LinearAlgebra.generic_norm2` which led to a scalar indexing. This catches such cuda subarray norm2 calls earlier.

Inf-norm and p-norm with cuda subarrays still lead to the following dispatches:
```julia
LinearAlgebra.generic_normInf(x) = float(mapreduce(norm, max, x))
LinearAlgebra.generic_norm1(x) = mapreduce(float ∘ norm, +, x)
```
I am not sure if there is a better way to dispatch the above.

should resolve JuliaGPU#2280
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Add a dispatch for LinearAlgebra.norm2 sharanry/CUDA.jl
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@maleadt @utkinis