Gaussian

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.

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

modules documentation

Serial

gaussian

Parallel (Shared memory with OpenMP)

gaussian

System Variables

HPC_{{#uppercase:gaussian}}_DIR
GV_DIR
g09root
GAUSS_BSDDIR
GAUSS_EXEDIR
_DSM_BARRIER

Additional Information

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

Command-line Job Submission: See the next section.
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 interface. For specific instructions concerning how to submit a Gaussian job using Galaxy, there is also a step-by-step procedure wiki entry: Gaussian Galaxy

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

Sample Submission Scripts

See the Gaussian_PBS page for sample Gaussian job submission scripts.

Considerations

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 requires 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.

Gaussview

There is a separate Gaussview page for use of the Gaussview viewing software.

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.