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Any luck running this on a 3000 series GPU? #1

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reynoldscem opened this issue Jun 9, 2022 · 2 comments
Open

Any luck running this on a 3000 series GPU? #1

reynoldscem opened this issue Jun 9, 2022 · 2 comments

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@reynoldscem
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It appears the version of cuda toolkit and maybe some other stuff set in the environment.yml isn't compatible with the sm_86 compute arch. Have you tried running this on nVidia 3000 series cards and can you advise how one might successfully install / compile / run the code on them?

@haoyuhsu
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haoyuhsu commented Jun 13, 2022

For running this on NVIDIA 3000 series cards, you can follow the instructions below for environment installation & CUDA code compile. (note that this has been tested on RTX 3090 card successfully)

Install PyTorch

conda create -n neurmips python=3.8
conda activate neurmips
conda install -c pytorch pytorch=1.8.0 torchvision cudatoolkit=11.1
conda install -c conda-forge -c fvcore -c iopath fvcore iopath

Option 1: Install Pytorch3D

conda install pytorch3d -c pytorch3d

Option 2: Install Pytorch3D from Github (recommended) (if option 1 do NOT work)

pip install "git+https://github.com/facebookresearch/pytorch3d.git"

Install Hydra

conda install -c conda-forge hydra-core

Install associate packages

pip install vedo
pip install scikit-image

change nvcc to installed version (CUDA 11.1)

export PATH=/usr/local/cuda-11.1/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

compile CUDA code

cd cuda
python setup.py develop

@reynoldscem
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Thank you, I will try that out.

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