OpenMM on Polaris

What is OpenMM?

OpenMM is a high-performance toolkit for molecular simulations that can be used as a stand-alone application or as a library. It provides a combination of flexibility (through custom forces and integrators), openness, and high performance (especially on recent GPUs).

Using OpenMM at ALCF

ALCF offers assistance with building binaries and compiling instructions for OpenMM. For questions, contact us at support@alcf.anl.gov.

Building OpenMM using Conda module

Update environment
```
$ module load conda/2022-07-19
```

Install OpenMM

$ mkdir conda
$ conda create --prefix /path-to/conda/openmm_env
$ conda activate /path-to/conda/openmm_env
$ conda install -c conda-forge openmm cudatoolkit=11.4
$ conda deactivate /path-to/conda/openmm_env

Validate installation: If successful, information on code version, platform types, CUDA initialization, and force error tolerance will be shown.
```
$ cd /path-to/conda/openmm_env/share/openmm/examples
$ python -m openmm.testInstallation
```

Benchmark testing using the PBS job script below.

$ cd /path-to/conda/openmm_env/share/openmm/examples
$ qsub ./submit.sh

Running OpenMM Benchmark on Polaris

A sample PBS script follows that will run the OpenMM benchmark on one node.

#!/bin/sh
#PBS -l select=1:system=polaris
#PBS -l place=scatter
#PBS -l walltime=0:30:00
#PBS -q debug
#PBS -A PROJECT
#PBS -l filesystems=home:eagle

cd ${PBS_O_WORKDIR}

module load cudatoolkit-standalone/11.4.4

python benchmark.py --platform=CUDA --test=pme --precision=mixed --seconds=30 --heavy-hydrogens > test.output

Building OpenMM from Source

Update environment

$ module load cudatoolkit-standalone/11.4.4
$ module load cray-python/3.9.12.1

Download OpenMM

$ git clone https://github.com/openmm/openmm.git
$ cd openmm ; mkdir build

Download and build Doxygen

$ git clone https://github.com/doxygen/doxygen.git
$ cd doxygen ; cmake . ; make ; make install ; cd ../

Download and install SWIG in the OpenMM directory.

$ tar xzf swig-4.0.2.tar.gz
$ cd swig-4.0.2
$ ./configure --prefix=/path-to/openmm/swig-4.0.2 ; make -j 8 ; make install

Build OpenMM

$ cmake -DDOXYGEN_EXECUTABLE=/path-to/openmm/doxygen/bin/doxygen \
        -DSWIG_EXECUTABLE=/path-to/openmm/swig-4.0.2/bin/swig \
        -DCMAKE_INSTALL_PREFIX=/path-to/openmm/build \
        -DCUDA_HOME=/soft/compilers/cudatoolkit/cuda-11.4.4 \
        -DCUDA_INCLUDE_DIR=/soft/compilers/cudatoolkit/cuda-11.4.4/include \
        -DCUDA_LIB_DIR=/soft/compilers/cudatoolkit/cuda-11.4.4/lib64
$ make -j 8
$ make install

Validate installation: If successful, information on code version, platform types, CUDA initialization, and force error tolerance will be shown.
```
$ cd /path-to/openmm/examples
$ python -m openmm.testInstallation
```

Benchmark testing using the PBS job script above.

$ cd /path-to/openmm/examples
$ qsub ./submit.sh