Amber

There are two installations of Amber, one which only supports running on CPUs, and one which supports running on GPUs (using CUDA). Use the module command to load the required version (note that you can not use both at the same time):

load the desired Amber module
$ module load Amber/22.3-foss-2022b-AmberTools-23.0
$ module load Amber/22.4-foss-2022a-AmberTools-22.5-CUDA-11.7.0

The following job script could be used to submit an Amber workflow to the cluster, using 1 core and 4.8GB of memory for 2 hours. The following assumes that you have defined in the script amber_cpu_example.sh an Amber workflow, e.g. minimisation and molecular dynamics:

Example CPU Amber Script
 1#!/usr/bin/env bash
 2#SBATCH --job-name=amber_cpu_example           # Job name
 3#SBATCH --account=dept-proj-year               # Project account to use
 4#SBATCH --partition=nodes                      # Partition for the job
 5#SBATCH --ntasks=1                             # Run a single task
 6#SBATCH --cpus-per-task=1                      # Number of cores per task
 7#SBATCH --mem=4800MB                           # Job memory request
 8#SBATCH --time=00:02:00                        # Time limit hrs:min:sec
 9#SBATCH --output=%x.log                        # Standard output and error log
10#SBATCH --mail-type=ALL                        # Events to receive emails about
11#SBATCH --mail-user=a.user@york.ac.uk          # Where to send mail
12
13# Abort if any command fails
14set -e
15
16module purge
17module load Amber/22.3-foss-2022b-AmberTools-23.0
18./amber_cpu_example.sh

The following job script could be used to submit an Amber workflow to the GPU partition in the cluster, using 1 core, 4.8GB of memory, and 1 GPU for 2 hours. The following assumes that you have defined in the script amber_gpu_example.sh an Amber workflow which makes use of GPUs:

Example GPU Amber Script
 1#!/usr/bin/env bash
 2#SBATCH --job-name=amber_gpu_example           # Job name
 3#SBATCH --account=dept-proj-year               # Project account to use
 4#SBATCH --partition=gpu                        # Partition for the job ('gpu' for the GPU partition)
 5#SBATCH --ntasks=1                             # Run a single task
 6#SBATCH --cpus-per-task=1                      # Number of cores per task
 7#SBATCH --mem=4800MB                           # Job memory request
 8#SBATCH --gres=gpu:1                           # Select 1 GPU
 9#SBATCH --time=02:00:00                        # Time limit hrs:min:sec
10#SBATCH --output=%x.log                        # Standard output and error log
11#SBATCH --mail-type=END,FAIL                   # Events to receive emails about
12#SBATCH --mail-user=a.user@york.ac.uk          # Where to send mail
13
14# Abort if any command fails
15set -e
16
17module purge
18module load Amber/22.4-foss-2022a-AmberTools-22.5-CUDA-11.7.0
19./amber_gpu_example.sh