Install for a remote GPU with SSH access#

Glossary#

Local Machine: the machine that has VSCode installed along with the Remote-SSH extension. This is the machine you use to connect to your remote machine.

Remote Machine: the machine that is equipped with a NVIDIA GPU and CUDA installed. This is machine that contains your development environment and runs your Deep Learning workloads.

Prerequisites#

  • A remote machine equipped with an NVIDIA GPU and Driver installed

  • CUDA versions: 11.1, 11.3, 11.6, 11.7

  • Python: 3.7 - 3.10

  • A local machine with VSCode

Note that most of packages will installed will be on your remote machine.

Note

NVIDIA GeForce RTX 30xx with CUDA capability sm_86 is not compatible with the current PyTorch installation.

The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70. If you want to use the NVIDIA GeForce RTX 3060 Ti GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

Note

Create your own virtual environment using your preferred virtual environment manager. Ensure that the appropriate version of PyTorch is installed in your virtual environment.

Installing Deepview.Profile#

On your remote machine, run the following commands to install Deepview.Profile

pip install deepview_profile

Installing the VSCode Extension#

Launch VSCode on your local machine and connect to your remote machine with VSCode SSH. Inside your remote VSCode connection, install DeepView.Explore (the VSCode extension) by searching for it in the extension marketplace.

Run your first analysis#

Now you are ready for your first analysis!