Comments (8)
Maybe a version mismatch?
This issue is preventing me from building the CUDA kernels for Knet.jl.
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CUDA 9.1 does not support GCC 7.
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I guess the error message could be better though.
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Do you mean officially? Because my own CUDA kernels compile just fine.
Edit: Nevermind, I'm an idiot. They were using clang.
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For others with this problem, I solved it by running apt install gcc-6 g++-6
on my Ubuntu 17.10 machine. Now the tests pass.
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I solved it by running apt install gcc-6 g++-6 on my Ubuntu 17.10 machine
Great 🙂
Yeah, you can find that info in the installation guide: http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html (although the actual headers are a little more lenient)
from cudaapi.jl.
I skipped that since I had been using clang. I guess CUDAapi
doesn't have that option?
from cudaapi.jl.
Right now, no. Clang support is fairly new. Shouldn't be too hard to add though, in case you want to avoid installing GCC 6.
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Related Issues (20)
- Remove warning HOT 3
- @runtime_ccall thread safety HOT 5
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- could not load library: "C:\Users\USER\.julia\artifacts\~~~\bin\cudnn64_7.dll" HOT 2
- Could not find nvToolsExt (libnvToolsExt.dylib.1.0 or libnvToolsExt.dylib.1) in /Users/imac/.julia/artifacts/b502baf54095dff4a69fd6aba8667124583f6929/lib HOT 1
- ERROR: Could not find a suitable GCC HOT 4
- Unable to find cudnn HOT 9
- Cannot find cuDNN that was installed via anaconda (without sudo) HOT 4
- Fix hardcoded CUDA versions to folder name autodetection? HOT 2
- macOS CI for CUDA 10+ HOT 1
- CI does not spot: libcudadevrt.lib is actually cudadevrt.lib on windows HOT 4
- find_library word_size
- Longer term goal with other CUDA libraries HOT 4
- Finding 8.0 files instead of 10.1 ones HOT 5
- CUDA discovery failing with 1.3.0-rc1 HOT 1
- Discovery fails if CUDA env vars are set to empty variable HOT 2
- Float64 HOT 1
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- Sort paths from CUDAapi.find_toolkit() in the descending order? HOT 2
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