5

I am currently trying to custom train a neural network using tensorflow 2.4.0 with a RTX 3070 running CUDA 11.0 and and CUDNN 8.

I am having this wierd issue where I can train the model, but I can't actually get any output because when I run:

output = model(x) I am met with the following message and my jupyter kernel automatically restarts.

2021-01-08 20:52:53.437668: W tensorflow/stream_executor/gpu/asm_compiler.cc:191] Falling back to the CUDA driver for PTX compilation; ptxas does not support CC 8.6
2021-01-08 20:52:53.437690: W tensorflow/stream_executor/gpu/asm_compiler.cc:194] Used ptxas at /usr/local/cuda-11.0/bin/ptxas
2021-01-08 20:52:53.438427: W tensorflow/stream_executor/gpu/redzone_allocator.cc:314] Unimplemented: /usr/local/cuda-11.0/bin/ptxas ptxas too old. Falling back to the driver to compile.
Relying on driver to perform ptx compilation. 
Modify $PATH to customize ptxas location.

As a test I have installed CUDA 11.1 and 11.2 and readjusted the $PATH variables accordingly, but tensorflow seems to default to using the ptxas version in the CUDA 11.0 folder.

What can I do to point tensorflow towards the 11.1 and 11.2 version of PTXAS instead of the 11.0 version?

1 Answer 1

2

Add the nVidia toolkit bin directory to your path, for example:

export PATH=/depot/cuda/cuda-11.2/bin:$PATH

This should remove that message.

2
  • 2
    In my case, I had to do ls /usr/local | grep cuda whcih showed me the path to add was /usr/local/cuda-11.2/bin
    – james-see
    Dec 5, 2021 at 23:29
  • 2
    @jamescampbell: This helps! Thank you!
    – nanono
    May 19 at 1:15

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.