Gaussian 09

Single-node (multi-threaded) jobs

You have to use the parallel environment smp to ensure that your job runs on a single host. The following example illustrates this for a Gaussian job using 12 processors (CPU cores):

#$ -l h_vmem=1900MB
#$ -l h_fsize=500G

#$ -pe smp 12
#$ -R y

module load gaussian
g09run myinputfile

The total amount of memory reserved for the job is 12 x 1900 MB = 22.8 GB (remember that for parallel jobs, the value of h_vmem is multiplied by the number of slots), which is close to the maximum memory available on a standard compute node of HERO (23 GB). If you requested less than 12 slots, the remaining slots may be filled by jobs of other users (provided there is enough memory and other resources available). Of course, you may also need to reserve sufficient local disk (scratch space) for your job (in the above example, 500 GB are

The Gaussian input file myinputfile of the above example would then contain, e.g., the following lines in the link 0 section:

%Mem=21000MB
%NProcShared=12

Important: Memory management is critical for the performance of Gaussian jobs. Which parameter values are optimal is highly dependent on the type of the calculation, the system size, and other factors. Therefore, optimizing your Gaussian job with respect to memory allocation almost always requires (besides experience) some trial and error. The following general remarks may be useful:

• In the above example, we have told Gaussian to use almost all of the total memory reserved for the job (22.8 GB), leaving only a small margin of 1.8 GB which is necessary, among others, since the G09 executables are rather large and have to be resident in memory (a margin of about 1 GB should be sufficient in most cases). This is usually a good choice for DFT calculations.
• For MP2 calculations, on the other hand, Gaussian requests about twice the amount of memory specified by the Mem=... directive. If this total (physical + virtual) memory requested by Gaussian is lower than the memory reserved for the job via the SGE h_vmem=... directive, the process stays in main memory. If it exceeds the memory reserved for the job, the operating systems starts swapping, which may lead to a dramatic performance decrease. In that case, you may significantly speed up your calculation by giving Gaussian access to only half of the total memory reserved for the job, i.e., in the above example, a good starting point for a MP2 calculation would be:

  %Mem=11000MB
  %NProcShared=12
  

  In any case, as mentioned above, testing and some trial and error are indispensable and well worth the effort!

You may also want to check the Efficiency Considerations website of Gaussian Inc.