Difference between revisions of "Gaussian"

From UFRC
Jump to navigation Jump to search
Line 64: Line 64:
 
<!--PBS scripts-->
 
<!--PBS scripts-->
 
{{#if: {{#var: pbs}}|==PBS Script Examples==
 
{{#if: {{#var: pbs}}|==PBS Script Examples==
Please note that our version of Gaussian only supports shared-memory parallelism. This means that if you want to use more than one processor for a Gaussian job, you are limited to the number of processors in a single machine. You cannot run Gaussian 09 across multiple machines on the HPC Center cluster.
+
Please note that our version of Gaussian only supports shared-memory parallelism. This means that if you want to use more than one processor for a Gaussian job, you are limited to the number of processors in a single machine. You cannot run Gaussian across multiple machines on the HPC Center cluster.
  
 
This forces you to a resource request of the form
 
This forces you to a resource request of the form
Line 70: Line 70:
 
#PBS -l nodes=1:ppn=<N>   
 
#PBS -l nodes=1:ppn=<N>   
 
</pre>
 
</pre>
where N is the number of processors and is constrained as follows:
+
where N is constrained by the number of "cores" (i.e. processors) in a single machine.  The HPC Center has a heterogeneous cluster consisting of nodes having 4, 8, 12, and 16 processors.  As you can see from the table below, all of our machines have at least 4 cores.  By asking for more than 4 cores, you will restrict your job to some subset of the available machines.  This may result in increased queue times.
 
<pre>
 
<pre>
PhaseII: N<=4
+
Phase 2: N<=4
PhaseIII: N<=8
+
Phase 3: N<=8
PhaseIV: N<=12
+
Phase 4: N<=12
PhaseV:   N<=16
+
Phase 5: N<=16
 +
</pre>
  
PhaseII through PhaseV refer to the set of machines we purchased during certain time period.
+
''Phase 2'' through ''Phase 5'' refer to sets of machines purchased at roughly the same time and, thus, are of similar architecture.  
The larger N you request, the more restricted your job will be in terms of resource availability.
 
</pre>
 
  
 
See the [[{{PAGENAME}}_PBS]] page for {{#var: app}} PBS script examples.
 
See the [[{{PAGENAME}}_PBS]] page for {{#var: app}} PBS script examples.

Revision as of 17:50, 19 September 2012

Description

gaussian website  
Gaussian 09 is the latest in the Gaussian series of electronic structure programs. Gaussian 09 is used by chemists, chemical engineers, biochemists, physicists and others for research in established and emerging areas of chemical interest. Starting from the basic laws of quantum mechanics, Gaussian predicts the energies, molecular structures, and vibrational frequencies of molecular systems, along with numerous molecular properties derived from these basic computation types. It can be used to study molecules and reactions under a wide range of conditions, including both stable species and compounds which are difficult or impossible to observe experimentally such as short-lived intermediates and transition structures. This article introduces several of its new and enhanced features.

Gaussian License

Please note that Gaussian is restricted software. Users who intend to use it must sign the Gaussian Confidentiality Agreement. This form is available in NPB 2238. You may come by during office hours and sign the agreement. Once the form is signed, you will be added to the "gaussian" user group and will have access to the software. See Gaussian License.

Required Modules for g09 and gview (GaussView)

modules documentation

Serial

  • gaussian

Parallel (Shared memory with OpenMP)

  • gaussian

System Variables

  • HPC_{{#uppercase:gaussian}}_DIR
  • GV_DIR
  • g09root


Additional Information

There are two mechanisms by which you can submit Gaussian Jobs.

  1. Command-line Job Submission: See the next section.
  2. Galaxy Framework: Galaxy can be accessed at: http://galaxy.hpc.ufl.edu. Gaussian is listed in the "Tools" pane under "Chemistry". Please refer to Galaxy for more information on how to use this framework.

Please see the Gaussian_galaxy-input page for a sample input file to run Gaussian using Galaxy.

PBS Script Examples

Please note that our version of Gaussian only supports shared-memory parallelism. This means that if you want to use more than one processor for a Gaussian job, you are limited to the number of processors in a single machine. You cannot run Gaussian across multiple machines on the HPC Center cluster.

This forces you to a resource request of the form

#PBS -l nodes=1:ppn=<N>  

where N is constrained by the number of "cores" (i.e. processors) in a single machine. The HPC Center has a heterogeneous cluster consisting of nodes having 4, 8, 12, and 16 processors. As you can see from the table below, all of our machines have at least 4 cores. By asking for more than 4 cores, you will restrict your job to some subset of the available machines. This may result in increased queue times.

Phase 2: N<=4
Phase 3: N<=8
Phase 4: N<=12
Phase 5: N<=16

Phase 2 through Phase 5 refer to sets of machines purchased at roughly the same time and, thus, are of similar architecture.

See the Gaussian_PBS page for gaussian PBS script examples.


Citation

If you publish research that uses gaussian you have to cite it as follows:

Gaussian 09, Revision A.1, M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H. P. Hratchian, A. F. Izmaylov, J. Bloino, G. Zheng, J. L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J. A. Montgomery, Jr., J. E. Peralta, F. Ogliaro, M. Bearpark, J. J. Heyd, E. Brothers, K. N. Kudin, V. N. Staroverov, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J. C. Burant, S. S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J. M. Millam, M. Klene, J. E. Knox, J. B. Cross, V. Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R. E. Stratmann, O. Yazyev, A. J. Austin, R. Cammi, C. Pomelli, J. W. Ochterski, R. L. Martin, K. Morokuma, V. G. Zakrzewski, G. A. Voth, P. Salvador, J. J. Dannenberg, S. Dapprich, A. D. Daniels, Ö. Farkas, J. B. Foresman, J. V. Ortiz, J. Cioslowski, and D. J. Fox, Gaussian, Inc., Wallingford CT, 2009.