Amber and AmberTools are suite of biomolecular simulation programs. Here, the term “Amber” does not refer to the set of molecular mechanical force fields for the simulation of biomolecules but to the package of molecular simulation programs consisting of the AmberTools (sander and many more) and Amber (pmemd).
AmberTools are open-source while Amber (pmemd) requires a license. NHR@FAU holds a “compute center license” of Amber, thus, Amber is generally available to everyone for non-profit use, i.e. for academic research.
Availability / Target HPC systems
- TinyGPU and Alex: typically use pmemd.cuda which uses a single GPU.
Thermodynamic integration (TI) may require special tuning; contact us!
- throughput cluster Woody and parallel computers: only use sander.MPI if the input is not supported by pmemd.MPI.
cpptraj is also available in parallel versions (cpptraj.OMP and cpptraj.MPI).
New versions of Amber/AmberTools are installed by RRZE upon request.
The CPU-only module is called
amber while the GPU version (which only contains pmemd.cuda) is called
amber-gpu. The numbers in the module name specify the Amber version, Amber patch level, the AmberTools version, and the AmberTools patch level. The number are complemented by the used compilers/tools, e.g.
pmemd and sander do not have internal measures to limit the run time. Thus, you have to estimate the number of time steps which can finish within the requested wall time before hand and use that in your mdin file.
Recent versions of AmberTools install their only version of Python which is independent of the Python of the Linux distribution or the usual Python modules of RRZE.
Sample job scripts
pmemd on TinyGPU
#!/bin/bash -l #SBATCH --time=06:00:00 #SBATCH --job-name=Testjob #SBATCH --gres=gpu:1 #SBATCH --export=NONE unset SLURM_EXPORT_ENV module add amber-gpu/20p08-at20p12-gnu-cuda11.2 ### there is no need to fiddle around with CUDA_VISIBLE_DEVICES! pmemd.cuda -O -i mdin ...
pmemd on Alex
#!/bin/bash -l # #SBATCH --job-name=my-pmemd #SBATCH --ntasks=16 #SBATCH --time=06:00:00 # use gpu:a100:1 and partition=a100 for A100 #SBATCH --gres=gpu:a40:1 #SBATCH --partition=a40 #SBATCH --export=NONE unset SLURM_EXPORT_ENV module load amber/20p12-at21p11-gnu-cuda11.5 srun pmemd.cuda -O -i mdin -c inpcrd -p prmtop -o output
parallel pmemd on Meggie
#!/bin/bash -l # # allocate 4 nodes with 20 cores per node = 4*20 = 80 MPI tasks #SBATCH --nodes=4 #SBATCH --tasks-per-node=20 # # allocate nodes for 6 hours #SBATCH --time=06:00:00 # job name #SBATCH --job-name=my-pmemd # do not export environment variables #SBATCH --export=NONE # # first non-empty non-comment line ends SBATCH options # do not export environment variables unset SLURM_EXPORT_ENV # jobs always start in submit directory module load amber/20p03-at20p07-intel17.0-intelmpi2017 # run srun pmemd.MPI -O -i mdin ...
- Dr. A. Kahler, RRZE, firstname.lastname@example.org
- AG Sticht (Professur für Bioinformatik, MedFak)