NAMD

This article is a draft

This is not a complete article: This is a draft, a work in progress that is intended to be published into an article, which may or may not be ready for inclusion in the main wiki. It should not necessarily be considered factual or authoritative.

General

NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. Simulation preparation and analysis is integrated into the visualization package VMD.

• Project web site: http://www.ks.uiuc.edu/Research/namd/
• Manual: http://www.ks.uiuc.edu/Research/namd/current/ug/
• Downloads: http://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=NAMD
• Tutorials: http://www.ks.uiuc.edu/Training/Tutorials/

A registration required to download software.

Quickstart Guide

This section summarizes configuration details.

Environment Modules

The following modules providing NAMD are available on graham and cedar.

Compiled without CUDA support:

• namd-multicore/2.12
• namd-verbs/2.12

Compiled with CUDA support:

• namd-multicore/2.12
• namd-verbs-smp/2.12

To access these modules which require CUDA, first execute:

module load cuda/8.0.44

Note: using verbs library is more efficient than using OpenMPI, hence only verbs versions are provided.

Submission Scripts

Please refer to the page "Running jobs" for help on using the SLURM workload manager.

Serial Job

Here's a simple job script for serial simulation:

File : serial_namd_job.sh

#!/bin/bash
#
#SBATCH --ntasks 1            # number of tasks
#SBATCH --mem 1024            # memory pool per process
#SBATCH -o slurm.%N.%j.out    # STDOUT
#SBATCH -t 0:20:00            # time (D-HH:MM)
#SBATCH --account=def-specifyaccount


module load namd-multicore/2.12
namd2 +p1 +idlepoll apoa1.namd

Verbs Job

These provisional Instructions will be refined further once this configuration can be fully tested on the new clusters. This example uses 64 processes in total on 2 nodes, each node running 32 processes, thus fully utilizing its 32 cores. This script assumes full nodes are used, thus ntasks/nodes should be 32 (on graham). For best performance, NAMD jobs should use full nodes.

NOTE: The verbs version will not run on cedar because of its different interconnect. Use the MPI version instead.

File : verbs_namd_job.sh

#!/bin/bash
#
#SBATCH --ntasks 64            # number of tasks
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=32
#SBATCH --mem 0            # memory per node, 0 means all memory
#SBATCH -o slurm.%N.%j.out    # STDOUT
#SBATCH -t 0:05:00            # time (D-HH:MM)
#SBATCH --account=def-specifyaccount

slurm_hl2hl.py --format CHARM > nodefile.dat
NODEFILE=nodefile.dat
P=$SLURM_NTASKS

module load namd-verbs/2.12
CHARMRUN=`which charmrun`
NAMD2=`which namd2`
$CHARMRUN ++p $P ++nodelist $NODEFILE  $NAMD2  +idlepoll apoa1.namd

MPI Job

NOTE: Use this only on cedar, where verbs version will not work.

File : mpi_namd_job.sh

#!/bin/bash
#
#SBATCH --ntasks 64            # number of tasks
#SBATCH --nodes=2
#SBATCH --mem 4024            # memory pool per process
#SBATCH -o slurm.%N.%j.out    # STDOUT
#SBATCH -t 0:05:00            # time (D-HH:MM)
#SBATCH --account=def-specifyaccount

module load namd-mpi/2.12
NAMD2=`which namd2`
srun $NAMD2 apoa1.namd

GPU Job

This example uses 8 CPU cores and 1 GPU on a single node.

File : multicore_gpu_namd_job.sh

#!/bin/bash
#
#SBATCH --ntasks 8            # number of tasks
#SBATCH --mem 1024            # memory pool per process
#SBATCH -o slurm.%N.%j.out    # STDOUT
#SBATCH -t 0:05:00            # time (D-HH:MM)
#SBATCH --gres=gpu:1
#SBATCH --account=def-specifyaccount


module load cuda/8.0.44
module load namd-multicore/2.12
namd2 +p8 +idlepoll apoa1.namd

Verbs-GPU Job

These provisional Instructions will be refined further once this configuration can be fully tested on the new clusters. This example uses 64 processes in total on 2 nodes, each node running 32 processes, thus fully utilizing its 32 cores. Each node uses 2 GPUs, so job uses 4 GPUs in total. This script assumes full nodes are used, thus ntasks/nodes should be 32 (on graham). For best performance, NAMD jobs should use full nodes.

NOTE: The verbs version will not run on cedar because of its different interconnect.

File : verbsgpu_namd_job.sh

#!/bin/bash
#
#SBATCH --ntasks 64            # number of tasks
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=32
#SBATCH --mem 1024            # memory pool per process
#SBATCH --gres=gpu:2
#SBATCH -o slurm.%N.%j.out    # STDOUT
#SBATCH -t 0:05:00            # time (D-HH:MM)
#SBATCH --account=def-specifyaccount

slurm_hl2hl.py --format CHARM > nodefile.dat
NODEFILE=nodefile.dat
OMP_NUM_THREADS=32
P=$SLURM_NTASKS

module load cuda/8.0.44
module load namd-verbs-smp/2.12
CHARMRUN=`which charmrun`
NAMD2=`which namd2`
$CHARMRUN ++p $P ++ppn $OMP_NUM_THREADS ++nodelist $NODEFILE  $NAMD2  +idlepoll apoa1.namd

Installation

NAMD is installed by the Compute Canada software team and is available as a module. If a new version is required, please email tech support and request it. Also, if for some reason you need to do your own installation, please contact tech support for advice and help with that. You can also ask for details of how our NAMD modules were compiled.

Links

• NAMD website at www.ks.uiuc.edu
• NAMD Users's guide for version 2.12
• NAMD version 2.12 release notes

Message Passing Interface