# LinearAlgebra./ breaks CuArray

**URL:** <https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570>\
**Category:** GPU\
**Tags:** question\
**Created:** [July 21, 2022, 2:27am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570 "2022-07-21T02:27:16Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![Lian\_Yunlong](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lian_yunlong/32/14437_2.png) [@Lian\_Yunlong](https://discourse.julialang.org/u/Lian_Yunlong)\
**Post date:** [July 21, 2022, 2:27am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570/1 "2022-07-21T02:27:16Z")

</div>

Hi,  
I have made a minimal reproducible example on the errors reported in my previous posts.  
It seems to me that the `A / b` operation breaks sonething in the CuArray, which is obscure to the user.  
Mysterious as it is, the code can run without errors in the “VSCode + Julia extension” mode.

```julia
(base) dabajabaza@XXXX:~$ cat jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl 
using LinearAlgebra
using CUDA
b = CUDA.rand(ComplexF64,5,5)
A = CUDA.rand(ComplexF64,5,5)
w = CUDA.rand(ComplexF64,5)
#V = A \ b
V = A / b
V * w
(base) dabajabaza@XXXX:~$ julia jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl 
ERROR: LoadError: CUBLASError: an invalid value was used as an argument (code 7, CUBLAS_STATUS_INVALID_VALUE)
Stacktrace:
 [1] throw_api_error(res::CUDA.CUBLAS.cublasStatus_t)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/cublas/error.jl:50
 [2] macro expansion
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/error.jl:63 [inlined]
 [3] cublasZgemv_v2(handle::Ptr{Nothing}, trans::Char, m::Int64, n::Int64, alpha::Bool, A::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}, lda::Int64, x::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer}, incx::Int64, beta::Bool, y::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer}, incy::Int64)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/utils/call.jl:26
 [4] gemv!
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/wrappers.jl:331 [inlined]
 [5] gemv_dispatch!(Y::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer}, A::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}, B::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer}, alpha::Bool, beta::Bool)
   @ CUDA.CUBLAS ~/.julia/packages/CUDA/DfvRa/lib/cublas/linalg.jl:179
 [6] mul!
   @ ~/.julia/packages/CUDA/DfvRa/lib/cublas/linalg.jl:188 [inlined]
 [7] mul!
   @ ~/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:275 [inlined]
 [8] *(A::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}, x::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:51
 [9] top-level scope
   @ ~/jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl:8
in expression starting at /home/dabajabaza/jianguoyun/Nutstore/RigorousCoupledWaveAnalysis.jl-master/examples/test.ma2018.jl:8
(base) dabajabaza@XXXX:~$ 
(base) dabajabaza@XXXX:~$ julia --version
julia version 1.7.2
(base) dabajabaza@XXXX:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:45:30_PST_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0
(base) dabajabaza@XXXX:~$ 
(base) dabajabaza@XXXX:~$ julia
               _
   _ _ _(_)_ | Documentation: https://docs.julialang.org
  (_) | (_) (_) |
   _ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` | |
  | | |_| | | | (_| | | Version 1.7.2 (2022-02-06)
 _/ |\ __'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |

julia> using CUDA
julia> CUDA.version
version (generic function with 2 methods)

julia> CUDA.version()
v"11.5.0"

julia> 

```

 ![Screenshot from 2022-07-21 10-26-48](https://global.discourse-cdn.com/julialang/original/3X/1/5/150be9c2af3e045a8d8c8f192c5cf5a9dad4b700.jpeg)

---

<div class="post-metadata">

**Author:** ![Lian\_Yunlong](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lian_yunlong/32/14437_2.png) [@Lian\_Yunlong](https://discourse.julialang.org/u/Lian_Yunlong)\
**Post date:** [July 21, 2022, 2:29am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570/2 "2022-07-21T02:29:33Z")

</div>

@maleadt Do you have any suggestions?

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<div class="post-metadata">

**Author:** ![Lian\_Yunlong](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lian_yunlong/32/14437_2.png) [@Lian\_Yunlong](https://discourse.julialang.org/u/Lian_Yunlong)\
**Post date:** [July 21, 2022, 2:35am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570/3 "2022-07-21T02:35:28Z")

</div>

just guess … maybe it is related to the [stream-ordered allocations](https://juliagpu.org/post/2021-04-09-cuda_3.0/index.html#cuda_112_and_stream-ordered_allocations) feature.

The following line has been involked many times as I profiling some code in a project (working inside VSCode environment). There was no issues with the `A/b` operations. But running the code from command line produces the issue, and I have then minimized it to the example in the original post

> <https://github.com/JuliaGPU/CUDA.jl/blob/8e58e13df1e8e55ccf5e9b9fdc2a9200852fc845/lib/cudadrv/stream.jl#L169>

---

<div class="post-metadata">

**Author:** ![Lian\_Yunlong](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lian_yunlong/32/14437_2.png) [@Lian\_Yunlong](https://discourse.julialang.org/u/Lian_Yunlong)\
**Post date:** [July 21, 2022, 5:18am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570/4 "2022-07-21T05:18:49Z")

</div>

```julia
julia> @code_typed (A/b)
CodeInfo(
1 ── %1 = Base.getfield(A, :dims)::Tuple{Int64, Int64}
│ %2 = Base.getfield(%1, 2, true)::Int64
│ %3 = Base.getfield(B, :dims)::Tuple{Int64, Int64}
│ %4 = Base.getfield(%3, 2, true)::Int64
│ %5 = (%2 === %4)::Bool
│ %6 = Base.not_int(%5)::Bool
└─── goto #3 if not %6
2 ── %8 = LinearAlgebra.DimensionMismatch("Both inputs should have the same number of columns")::Any
│ LinearAlgebra.throw(%8)::Union{}
└─── unreachable
3 ── %11 = %new(Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}, B)::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}
│ %12 = %new(Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}, A)::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}
└─── goto #5 if not false
4 ── nothing::Nothing
5 ┄─ goto #6
6 ── goto #7
7 ── goto #8
8 ── goto #9
9 ── goto #10
10 ─ goto #12 if not false
11 ─ nothing::Nothing
12 ┄ goto #13
13 ─ goto #14
14 ─ goto #15
15 ─ goto #16
16 ─ goto #17
17 ─ goto #18
18 ─ goto #19
19 ─ goto #20
20 ─ %30 = %new(CUDA.CUSOLVER.var"#2765#2766"{ComplexF64})::CUDA.CUSOLVER.var"#2765#2766"{ComplexF64}
│ %31 = invoke %30(%11::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}})::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}
│ %32 = invoke %30(%12::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}})::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}
└─── goto #21
21 ─ %34 = CUDA.CUSOLVER.getrf!::typeof(CUDA.CUSOLVER.getrf!)
│ %35 = invoke %34(%31::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer})::Tuple{CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}, CuArray{Int32, 1, CUDA.Mem.DeviceBuffer}, Int32}
│ %36 = Base.getfield(%35, 1)::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}
│ %37 = Base.getfield(%35, 2)::CuArray{Int32, 1, CUDA.Mem.DeviceBuffer}
│ %38 = CUDA.CUSOLVER.getrs!::typeof(CUDA.CUSOLVER.getrs!)
│ %39 = invoke %38('N'::Char, %36::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}, %37::CuArray{Int32, 1, CUDA.Mem.DeviceBuffer}, %32::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer})::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}
└─── goto #22
22 ─ %41 = %new(Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}, %39)::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}}
│ %42 = invoke LinearAlgebra.copy(%41::Adjoint{ComplexF64, CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}})::CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}
└─── return %42
) => CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}

```

I guess the problem may be related to line 22 `%41 = ...` and `%42 = ...`

---

<div class="post-metadata">

**Author:** ![Lian\_Yunlong](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lian_yunlong/32/14437_2.png) [@Lian\_Yunlong](https://discourse.julialang.org/u/Lian_Yunlong)\
**Post date:** [July 23, 2022, 4:15am UTC](https://discourse.julialang.org/t/linearalgebra-breaks-cuarray/84570/5 "2022-07-23T04:15:29Z")

</div>

solved  
[https://github.com/JuliaGPU/CUDA.jl/issues/1568](https://github.com/JuliaGPU/CUDA.jl/issues/1568)  
It is my fault to install incompatible versions of CUBLAS…  
My apology to everyone …