amber

Versions and Availability

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Module Names for amber on qb3
Machine Version Module Name
qb3 18 amber/18/intel-19.0.5-mvapich-2.3.3

▶ Module FAQ?

The information here is applicable to LSU HPC and LONI systems.

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Shells

A user may choose between using /bin/bash and /bin/tcsh. Details about each shell follows.

/bin/bash

System resource file: /etc/profile

When one access the shell, the following user files are read in if they exist (in order):

  1. ~/.bash_profile (anything sent to STDOUT or STDERR will cause things like rsync to break)
  2. ~/.bashrc (interactive login only)
  3. ~/.profile

When a user logs out of an interactive session, the file ~/.bash_logout is executed if it exists.

The default value of the environmental variable, PATH, is set automatically using Modules. See below for more information.

/bin/tcsh

The file ~/.cshrc is used to customize the user's environment if his login shell is /bin/tcsh.

Modules

Modules is a utility which helps users manage the complex business of setting up their shell environment in the face of potentially conflicting application versions and libraries.

Default Setup

When a user logs in, the system looks for a file named .modules in their home directory. This file contains module commands to set up the initial shell environment.

Viewing Available Modules

The command

$ module avail

displays a list of all the modules available. The list will look something like:

--- some stuff deleted ---
velvet/1.2.10/INTEL-14.0.2
vmatch/2.2.2

---------------- /usr/local/packages/Modules/modulefiles/admin -----------------
EasyBuild/1.11.1       GCC/4.9.0              INTEL-140-MPICH/3.1.1
EasyBuild/1.13.0       INTEL/14.0.2           INTEL-140-MVAPICH2/2.0
--- some stuff deleted ---

The module names take the form appname/version/compiler, providing the application name, the version, and information about how it was compiled (if needed).

Managing Modules

Besides avail, there are other basic module commands to use for manipulating the environment. These include:

add/load mod1 mod2 ... modn . . . Add modules
rm/unload mod1 mod2 ... modn  . . Remove modules
switch/swap mod . . . . . . . . . Switch or swap one module for another
display/show  . . . . . . . . . . List modules loaded in the environment
avail . . . . . . . . . . . . . . List available module names
whatis mod1 mod2 ... modn . . . . Describe listed modules

The -h option to module will list all available commands.

▶ Did not find the version you want to use??

If a software package you would like to use for your research is not available on a cluster, you can request it to be installed. The software requests are evaluated by the HPC staff on a case-by-case basis. Before you send in a software request, please go through the information below.

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Types of request

Depending on how many users need to use the software, software requests are divided into three types, each of which corresponds to the location where the software is installed:

  • The user's home directory
    • Software packages installed here will be accessible only to the user.
    • It is suitable for software packages that will be used by a single user.
    • Python, Perl and R modules should be installed here.
  • /project
    • Software packages installed in /project can be accessed by a group of users.
    • It is suitable for software packages that
      • Need to be shared by users from the same research group, or
      • are bigger than the quota on the home file syste.
    • This type of request must be sent by the PI of the research group, who may be asked to apply for a storage allocation.
  • /usr/local/packages
    • Software packages installed under /usr/local/packages can be accessed by all users.
    • It is suitable for software packages that will be used by users from multiple research groups.
    • This type of request must be sent by the PI of a research group.

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How to request

Please send an email to sys-help@loni.org with the following information:

  • Your user name
  • The name of cluster where you want to use the requested software
  • The name, version and download link of the software
  • Specific installation instructions if any (e.g. compiler flags, variants and flavor, etc.)
  • Why the software is needed
  • Where the software should be installed (locally, /project, or /usr/local/packages) and justification explaining how many users are expected.

Please note that, once the software is installed, testing and validation are users' responsibility.

About the Software

Amber is a suite of biomolecular simulation programs.

Usage

Make sure Module keys are matched up with corresponding versions of the compiler and MPI library. For instance on the SuperMike2, SuperMIC or Queenbee2:

module load amber/18/INTEL-170-MVAPICH2-2.2

MPI

Note: the usual executable name used is pmemd (serial, not recommended) or pmemd.MPI (parallel).

pmemd and pmemd.MPI in Amber 18 was built with Intel 17.0.0 and mvapich2 2.2. The Module key "amber/18/INTEL-170-MVAPICH2-2.2" will load corresponding versions of the compiler and MPI library as dependencies. Other versions of Intel compiler and mpi compilers should be removed from the Module list before loading the Amber 18 module key.

On SuperMike2, SuperMIC and QB2, use "pmemd.MPI" to run Amber. Below is a sample script which runs Amber with 2 nodes (40 CPU cores):

	#!/bin/bash
	#PBS -A my_allocation
	#PBS -q checkpt
	#PBS -l nodes=2:ppn=20
	#PBS -l walltime=HH:MM:SS
	#PBS -j oe
	#PBS -N JOB_NAME
	#PBS -V

	cd $PBS_O_WORKDIR
	mpirun -np 40 $AMBERHOME/bin/pmemd.MPI -O -i mdin.CPU -o mdout -p prmtop -c inpcrd
    

GPU acceleration

Note: the usual executable name used for Amber 16 and Amber 18 GPU acceleration is pmemd.cuda (serial) or pmemd.cuda.MPI (parallel).

pmemd.cuda and pmemd.cuda.MPI in Amber 16 was built with Intel 15.0.0 and CUDA 7.5. Please load Intel 15.0.0 compiler and CUDA 7.5 into your user environment in order to run pmemd.cuda.

pmemd.cuda and pmemd.cuda.MPI in Amber 18 was built with Intel 17.0.0, mvapich2 2.2 and CUDA 9. The Module key "amber/18/INTEL-170-MVAPICH2-2.2" will load these dependencies. Other versions of Intel compiler, mpi compilers and cuda should be removed from the Module list before loading the Amber 18 module key.

Please do not attempt to run regular GPU MD runs across multiple nodes. Infiniband is way too slow these days to keep up with the computation speed of the GPUs.

Using hybrid or v100 queue is required if running gpu simulation with Amber 18 on SuperMIC.

On SuperMIC and QB2, use "pmemd.cuda" to run Amber 16 with GPU acceleration in serial. Below is a sample script which runs Amber 16 on 1 node:

		#!/bin/bash
		#PBS -A my_allocation
		#PBS -q hybrid
		#PBS -l nodes=1:ppn=20
		#PBS -l walltime=HH:MM:SS
		#PBS -j oe
		#PBS -N JOB_NAME
		#PBS -V

		cd $PBS_O_WORKDIR
		$AMBERHOME/bin/pmemd.cuda -O -i mdin.GPU -o mdout_gpu -p prmtop -c inpcrd
    

GPU acceleration must use hybrid or v100 node if using SuperMIC. Note pmemd.cuda is a serial program, so no parallel exe such as mpirun is required, or set mpirun -np 1

On QB2 , as each compute node has two GPUs, "pmemd.cuda.MPI" can be used to run Amber 16 with GPU acceleration in parallel. Below is a sample script which runs Amber 16 on 1 node (2 GPUs) on QB2:

  		#!/bin/bash
  		#PBS -A my_allocation
  		#PBS -q hybrid
  		#PBS -l nodes=1:ppn=20
  		#PBS -l walltime=HH:MM:SS
  		#PBS -j oe
  		#PBS -N JOB_NAME
  		#PBS -V

  		cd $PBS_O_WORKDIR
		mpirun -np 2 $AMBERHOME/bin/pmemd.cuda.MPI -O -i mdin.GPU -o mdout_2gpu -p prmtop -c inpcrd -ref inpcrd
      

Use -np # where # is the number of GPUs you are requesting, NOT the number of CPUs. Note pmemd.cuda.MPI is significantly faster than pmemd.cuda only for the production run of a large model.

Resources

  • The Amber Home Page has a variety of on-line resources available, including manuals and tutorials.

On QB2 , as each compute node has two GPUs, "pmemd.cuda.MPI" can be used to run Amber 16 with GPU acceleration in parallel. Below is a sample script which runs Amber 16 on 1 node (2 GPUs) on QB2:

  		#!/bin/bash
  		#PBS -A my_allocation
  		#PBS -q hybrid
  		#PBS -l nodes=1:ppn=20
  		#PBS -l walltime=HH:MM:SS
  		#PBS -j oe
  		#PBS -N JOB_NAME
  		#PBS -V

  		cd $PBS_O_WORKDIR
		mpirun -np 2 $AMBERHOME/bin/pmemd.cuda.MPI -O -i mdin.GPU -o mdout_2gpu -p prmtop -c inpcrd -ref inpcrd
      

Use -np # where # is the number of GPUs you are requesting, NOT the number of CPUs. Note pmemd.cuda.MPI is significantly faster than pmemd.cuda only for the production run of a large model.

Resources

  • The Amber Home Page has a variety of on-line resources available, including manuals and tutorials.

Last modified: September 10 2020 11:58:50.