Installation

Requirements

  1. Linux operating system (e.g., Debian, Ubuntu)

  2. NVidia GPU (compute capability >= 3; see https://developer.nvidia.com/cuda-gpus)

  3. GPU driver installed (https://www.nvidia.com/en-us/drivers/unix/)

Installation via Conda

The recommended way to install GinJinn2 is via Conda, an open-source package management system for Python and R, which also includes facilities for environment management. See the official installation guide for further information.

To install Conda, run the following commands in your Linux terminal:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Once Conda ist installed run the following command to install GinJinn2 (insert your CUDA version, 10.1 should work for most modern GPUs):

conda install -c agoberprieler -c conda-forge -c pytorch cudatoolkit=10.1 ginjinn2

Finally, test your installation:

ginjinn -h