Julia freezes when using Polynomials with CuArray

[ghralima]

Julia freezes when it tries to create a polynomial with CuArray. (Not sure if this issue should be posted here or in Polynomials.jl git.)

using CUDA, Polynomials
a = CuVector([1.0f0, 1.0f0, 1.0f0])
Polynomial(a)

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Expected behavior

CUDA should create the polynomials inside the GPU, and thus use the GPU to calculate their roots using the roots function of Polynomials.jl ou FastPolynomialRoots.jl. However, it freezes when it tries to create the polynomial.

Version info

Details on Julia:

# please post the output of:
versioninfo()
Julia Version 1.7.2
Commit bf53498635 (2022-02-06 15:21 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
Environment:
  JULIA_NUM_THREADS = 4

Details on CUDA:

# please post the output of:
CUDA.versioninfo()
CUDA toolkit 11.6, artifact installation
NVIDIA driver 510.68.2, for CUDA 11.6
CUDA driver 11.6

Libraries: 
- CUBLAS: 11.8.1
- CURAND: 10.2.9
- CUFFT: 10.7.0
- CUSOLVER: 11.3.2
- CUSPARSE: 11.7.1
- CUPTI: 16.0.0
- NVML: 11.0.0+510.68.2
- CUDNN: 8.30.2 (for CUDA 11.5.0)
- CUTENSOR: 1.4.0 (for CUDA 11.5.0)

Toolchain:
- Julia: 1.7.2
- LLVM: 12.0.1
- 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
- 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

1 device:
  0: NVIDIA GeForce GTX 1060 (sm_61, 5.307 GiB / 6.000 GiB available)

[jverzani]

See also here: JuliaMath/Polynomials.jl#399 (Need to get CUDA running to look into this.)

[jverzani]

Is there some NVIDIA driver for Mac OS? I don't see something amongst these:

https://developer.nvidia.com/gameworksdownload#?dn=cuda-toolkit-developer-tools-for-macos-11-6-0

but maybe I'm misreading what is being said on that page.

[maleadt]

Works for me. But Polynomials does scalar indexing, so won't just work with GPU arrays out of the box.

Is there some NVIDIA driver for Mac OS?

No.

[maleadt]

Also, please try to provide more details on the freeze: What happens if you hit CTRL-C, which backtrace does it report, try attaching under gdb or lldb if it's really Julia that hangs, etc.

[jverzani]

Thanks for the reply. Is there some abstraction that allows scalar indexing with CuVectors? I didn't see anything in a quick search of the documentation.

[maleadt]

Is there some abstraction that allows scalar indexing with CuVectors

Typically broadcast, or a custom kernel if that doesn't work.

[ghralima]

Use this to backtrace gdb output:

gdb --args julia -g2 CUDA_Polynomials_test.jl 

The backtrace file is attached

gdb.txt

I hope this helps.

[maleadt]

Two things stand out in that backtrace:

• Julia really did hang somewhere in libcuda when trying to report on a failed kernel launch
• before that, there seems to be a stack overflow happening in Polynomials, as the following two methods are repeated thousands of times:

  #41 0x00007fffe00fbc92 in japi1_Polynomial_903 (coeffs=..., var=0x0) at /home/ghralima/.julia/packages/Polynomials/1aa8e/src/abstract.jl:51
  #42 0x00007fffe00fc18c in japi1_Polynomial_905 (x=..., var=0x0) at /home/ghralima/.julia/packages/Polynomials/1aa8e/src/abstract.jl:53
  

I'd focus on fixing the stack overflow first -- who knows what it causes down the line (e.g. exhausting stack space is a good way to make any function, like the ones called in libcuda here, fail or behave erroneously).

[maleadt]

Closing because this looks like a Polynomials bug (see above). Feel free to re-open if there's evidence this is still a CUDA.jl bug.