PyTorch installation with GPU support on Ubuntu

[ptrblck]

@rynczakd

Then, I checked that I have CUDA installed using nvcc --version command and I got: Build cuda_11.5.r11.5/compiler, so it also means that I have CUDA installed.

This won’t matter as PyTorch ships with its own CUDA runtime dependencies and your locally installed CUDA toolkit will be used if you are building PyTorch from source or a custom CUDA extension.

@rynczakd

Which Compute Platform should I choose?

I would recommend the latest CUDA toolkit (currently 12.1) as long as it’s compatible with your NVIDIA driver. Again, the locally CUDA toolkit doesn’t matter.

@rynczakd

Installing PyTorch from the command below will make me have PyTorch installed along with the CUDA drivers?

No, you need to install the NVIDIA driver yourself. The PyTorch binaries ship with CUDA runtime libraries, cuDNN, NCCL, etc.

@rynczakd

Can I use this command without having CUDA drivers installed before?

No, you need to install an NVIDIA driver, but don’t need a CUDA toolkit.

@rynczakd

Assuming I don’t have NVIDIA and CUDA drivers installed what steps should I follow before installing PyTorch?

Install an NVIDIA driver, then run pip install torch, which is enough to execute PyTorch workloads on your GPU.

I don’t respond to the other questions separately as they mainly target the locally installed CUDA toolkit which won’t be used if you install the binaries.