cuDNN.version can cause Julia to crash, missing cudnn_ops_infer64_8.dll

[yl4070]

Describe the bug

After upgrading to CUDA ver. 4.0.1, certain operations will cause Julia to crash.

To reproduce

using cuDNN
cuDNN.version()

This will show Could not locate cudnn_ops_infer64_8.dll. Please make sure it is in your library path!

Manifest.toml

# This file is machine-generated - editing it directly is not advised

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manifest_format = "2.0"
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Expected behavior

Not crash.

Version info

Details on Julia:

Julia Version 1.8.5
Commit 17cfb8e65e (2023-01-08 06:45 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 20 × 12th Gen Intel(R) Core(TM) i7-12700H
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, goldmont)
  Threads: 1 on 20 virtual cores

Details on CUDA:

CUDA runtime 11.8, artifact installation
CUDA driver 12.0
NVIDIA driver 528.24.0

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: 12.0.0+528.24

Toolchain:
- Julia: 1.8.5
- 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

1 device:
  0: NVIDIA GeForce RTX 3070 Ti Laptop GPU (sm_86, 7.844 GiB / 8.000 GiB available)

Additional context

The issue was first encountered when using Flux, ConvTranspose on newest CUDA (4.0.1) will cause crash while order version (3.13) will not. While I don't think this issue exit for everyone, but both my laptop and desktop encounter the same issue.

[maleadt]

@staticfloat, re #1755 (comment), you said that loading these submodules would be fine? Is this not the case on Windows?

[staticfloat]

Everything I said in that comment should still hold, I'm not entirely sure what is causing the crash here. Do we suspect it is because of mismatched library versions?

[sob727]

I'm getting the same issue (Julia crash, unable to find said DLL) on Windows 10, using these versions:

[MostlyHarmless420]

I've been getting the exact same issue as well. Tried deleting the CUDA and cuDNN artifacts and redownloading, but it doesn't resolve itself.

Could not locate cudnn_ops_infer64_8.dll. Please make sure it is in your library path!
ERROR: Package cuDNN errored during testing (exit code: 3221226505)

Julia Version 1.8.5
Commit 17cfb8e65e (2023-01-08 06:45 UTC)
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: 12 × AMD Ryzen 5 5600X 6-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, znver3)
Threads: 1 on 12 virtual cores

┌ Info: CUDA information:
│ CUDA runtime 11.8, artifact installation
│ CUDA driver 12.0
│ NVIDIA driver 528.24.0
│
│ 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: 12.0.0+528.24
│
│ Toolchain:
│ - Julia: 1.8.5
│ - 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
│
│ 1 device:
└ 0: NVIDIA GeForce RTX 3060 Ti (sm_86, 5.312 GiB / 8.000 GiB available)

[potaslab]

I also have the same problem:

Could not locate cudnn_ops_infer64_8.ddl. Please make sure it is in your library path!

Occurred specifically when adding a Flux model into the GPU, then executed Flux.train!.

With everything else the same, including loading all other variables onto the GPU, except the Flux model, it doesn't crash. When I add the flux model onto the GPU, julia terminates completely.

Julia Version 1.8.5
Commit 17cfb8e65e (2023-01-08 06:45 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 24 × AMD Ryzen Threadripper 1920X 12-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, znver1)
  Threads: 24 on 24 virtual cores
Environment:
  JULIA_EDITOR = code

CUDA runtime 11.8, artifact installation
CUDA driver 11.7
NVIDIA driver 516.94.0

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+516.94

Toolchain:
- Julia: 1.8.5
- 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

1 device:
  0: NVIDIA GeForce GTX 1080 Ti (sm_61, 9.700 GiB / 11.000 GiB available)

[maleadt]

Should be fixed with JuliaRegistries/General#79340