Purpose: electronic Structure Calculations
Latest version: Gaussian16 B.01
License: Provided by CSUC
Closed-source
Website: http://gaussian.com/
Amsterdam Density Functional (ADF) is a proprietary software suite for density functional theory (DFT) calculation of molecular systems, especially inorganic systems.
ADF implements Kohn-Sham-type DFT calculations to finite molecular systems, in gas phase or in solution. It applies LDA, GGA, and in some cases hybrid and meta-GGA functionals, including relativistic effects, to Slater-type orbitals.
SLURM Submit script example
More information about the submit script can be found using the Job Script Generator.
#!/bin/bash #SBATCH -J gaussian_example #SBATCH -e gaussian_example.%j.err #SBATCH -o gaussian_example.%j.out #SBATCH -p std #SBATCH -n 1 #SBATCH -c 4 #SBATCH -t 0-02:00 module load apps/gaussian/g16b01 ## # Modify the input and output files! INPUT_FILE=gaussian_example.com OUTPUT_FILE=gaussian_example.log ## # You don't need to modify nothing more cp -r ${SLURM_SUBMIT_DIR}/${INPUT_FILE} ${SCRATCH} cd ${SCRATCH} srun g16 < ${INPUT_FILE} > ${OUTPUT_FILE} cp ./${OUTPUT_FILE} ${SLURM_SUBMIT_DIR}
Sbatch options:
The options shown in the example are detailed below. For more information and a more comprehensive list of available options, see the sbatch command page.
- -J: Name for the job's allocation.
- -e: Name of the sterr redirection filename.
- -o: Name of the stdout redirection filename.
- -p: Name of the partition (queue) where the job will be submited.
-n: Number of tasks.
- -c: Number of cores per task.
- -t: Set the job's time limit. If the job don't finish before the time runs out, it will be killed.
Software execution information:
We do not support Linda, so MPI parallellization is not available. This implies that:
- The number of tasks must be 1 (-n flag).
- -c flagmust have the same value as %nprocs in the Gaussian input file.
- --mem must be higher than the value defined as %mem in input.com file. More info here.
Tutorial
You can follow this tutorial about geometric optimisation with Gaussian to get hands-on with the program.