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You can see GPU information using nvidia-smi
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[tervo@gpu-test-centos ~]$ nvidia-smi TueMon AprJan 58 1210:2224:47 2022 59 2024 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 470.82161.01 03 Driver Version: 470.82161.01 03 CUDA Version: 11.4 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 NVIDIA RTXA6000-6C... On | 00000000:00:05.0 Off | 0 | | N/A N/A P8 N/A / N/A | 512MiB3712MiB / 5976MiB48895MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+ |
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CUDA version is currently 11.4 which need to be the same with drivers and thus can't be changed. Tensorflow library compatibility is available at: https://www.tensorflow.org/install/source#gpu. We have tested that TensorFlow > 2.6.1 work.
Using Conda
Update and conda installation
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# change shell to bash for installations
bash
# update default packages
sudo apt-get update
sudo apt-get update
# it's possible to get some update key and dirmngr errors while updating, below commands supply a workaround. After running the workaround, run update & upgrade again.
sudo apt install dirmngr
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys <YOUR-KEY-LIKE-AA16FCBCA621E701>
# install miniforge (or any anaconda manager)
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
chmod +x Miniforge3-Linux-x86_64.sh
./Miniforge3-Linux-x86_64.sh
#When it asks, conda init? answer yes
#Do you wish the installer to initialize Miniforge3
#by running conda init? [yes|no]
#[no] >>>
yes
exit
bash |
Library installations
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sudo apt install -y docker.io
sudo usermod -aG docker $USER |
Confirmation of installations
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sudo apt install -y docker.io
sudo usermod -aG docker $USER |
#Using Docker
If you want to use GPUs in docker, you need to take few extra steps after creating the VM.
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