AMBER Biomolecular Simulation Package

Assisted Model Building with Energy Refinement

"Amber" refers to two things: a set of molecular mechanical force fields for the simulation of biomolecules (which are in the public domain, and are used in a variety of simulation programs); and a package of molecular simulation programs which includes source code and demos.

A good general overview of the Amber codes can be found in: D.A. Case, T.E. Cheatham, III, T. Darden, H. Gohlke, R. Luo, K.M. Merz, Jr., A. Onufriev, C. Simmerling, B. Wang and R. Woods. The Amber biomolecular simulation programs. J. Computat. Chem. 26, 1668-1688 (2005)

Available releases on Rider

Important Notes 

Running amber interactively

Request an interactive node:

srun -N 1 --time=1:00:00 --pty /bin/bash

Check available amber module versions:

module spider amber

output:

...

Versions:

  amber/16-17

  amber/18-18

  amber/18-19

Load an amber module:

module load intel/17 openmpi/2.0.1

module load amber/18-19

You can then run any of amber command line executables, e.g. tleap, sander, pmemd, and so on (ls $AMBERHOME/bin)

Running amber in a scheduler script

AMBER MPI Job

Copy mpitest directory from /usr/local/doc/AMBER and cd to it

cp -r /usr/local/doc/AMBER/mpitest .

cd mpitest

Find the job file "job-mpi.slurm" and run the job

sbatch job-mpi.slurm

Check the output file  "mdout"

...

|  Setup wall time:           4    seconds

|  NonSetup wall time:      172    seconds

|  Total wall time:         176    seconds     0.05 hours

Refer to HPC Guide to Molecular Modeling and Visualization and HPC Software Guide for more information.

AMBER GPU Job

Copy the directory gpujob from /usr/local/doc/AMBER to your home directory and cd to it

cp -r /usr/local/doc/AMBER/gputest . 

cd gputest

Submit the job:

job.slurm

Find the output in mdout file:

.....

|------------------- GPU DEVICE INFO --------------------

|

|            CUDA_VISIBLE_DEVICES: 1

|   CUDA Capable Devices Detected:      1

|           CUDA Device ID in use:      0

|                CUDA Device Name: Tesla P100-PCIE-12GB

|     CUDA Device Global Mem Size:  12198 MB

| CUDA Device Num Multiprocessors:     56

|           CUDA Device Core Freq:   1.33 GHz

....

 PME Reciprocal Force CPU Time:

|

|     Routine              Sec        %

|     ---------------------------------

|     1D bspline           0.00    0.00

|     Grid Charges         0.00    0.00

|     Scalar Sum           0.00    0.00

|     Gradient Sum         0.00    0.00

|     FFT                  0.00    0.00

|     ---------------------------------

|     Total                0.00    0.00

|  Final Performance Info:

|     -----------------------------------------------------

|     Average timings for last   72500 steps:

|     Elapsed(s) =      50.41 Per Step(ms) =       0.70

|         ns/day =     497.09   seconds/ns =     173.81

|

|     Average timings for all steps:

|     Elapsed(s) =     173.76 Per Step(ms) =       0.70

|         ns/day =     497.23   seconds/ns =     173.76

|     -----------------------------------------------------

|  Setup CPU time:            0.54 seconds

|  NonSetup CPU time:       173.73 seconds

|  Total CPU time:          174.27 seconds     0.05 hours

References