Software Packages
Conventional Operations
For using conventional tools such as conda, VSCode, pytorch, tensorflow, or containers with the Galvani cluster, please read through the Tutorials in this User Guide for instructions.
Development Tools
To see the development tools installed on Galvani run the following:
scl list-collections
gcc-toolset-10
gcc-toolset-11
gcc-toolset-9
source scl_source enable <devtoolset-x>
Selecting a CUDA version
You can find a list of the different cuda versions on the compute nodes under:
ls -1 /usr/local/cuda* -d
which should provide terminal output like this:
/usr/local/cuda-11
/usr/local/cuda-11.7
/usr/local/cuda-11.8
/usr/local/cuda-12
/usr/local/cuda-12.1
You can select a specific CUDA version to use (e.g. cuda 11.8) by running (replace 11.8
with the desired CUDA version):
export CUDA_VER=11.8 ; export PATH=/usr/local/cuda-$CUDA_VER/bin:$PATH ; export LD_LIBRARY_PATH=/usr/local/cuda-$CUDA_VER/lib64:/usr/local/cuda-$CUDA_VER/extras/CUPTI/lib64:$LD_LIBRARY_PATH
PATH
and LD_LIBRARY_PATH
for this session.
You can verify this worked by running nvcc --version
and reading the output.
If you want to select the same CUDA version every time, please add the above command to your .bashrc
file or sbatch
file.
Last update:
June 28, 2024
Created: June 21, 2024
Created: June 21, 2024