learning
Link to section 'Description' of 'learning' Description
The learning module loads the prerequisites (such as anaconda and cudnn ) and makes ML applications visible to the user
Link to section 'Versions' of 'learning' Versions
- Bell: conda-2020.11-py38-cpu
- Brown: conda-5.1.0-py27-cpu, conda-5.1.0-py36-cpu
- Scholar: conda-5.1.0-py27-cpu, conda-5.1.0-py27-gpu, conda-5.1.0-py36-cpu, conda-5.1.0-py36-gpu
- Gilbreth: conda-5.1.0-py27-cpu, conda-5.1.0-py27-gpu, conda-5.1.0-py36-cpu, conda-5.1.0-py36-gpu, conda-2020.11-py38-cpu, conda-2020.11-py38-gpu
- Anvil: conda-2021.05-py38-gpu
- Workbench: conda-5.1.0-py27-cpu, conda-5.1.0-py36-cpu
Link to section 'Module' of 'learning' Module
You can load the modules by:
module load learning
Link to section 'Example job' of 'learning' Example job
This is the example jobscript for our cluster `Gilbreth`:
#!/bin/bash
#SBATCH -A myallocation # Allocation name
#SBATCH -t 20:00:00
#SBATCH -N 1
#SBATCH -n 10
#SBATCH --gpus-per-node=1
#SBATCH -p PartitionName
#SBATCH --job-name=learning
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out
module --force purge
module load learning/conda-2020.11-py38-gpu
module load ml-toolkit-gpu/pytorch/1.7.1
python torch.py