Gaussian 16 supports shared-memory parallelism (Linda is required for distributed memory across nodes).
#SBATCH --job-name=benzene_opt #SBATCH --nodes=1 #SBATCH --ntasks-per-node=16 #SBATCH --mem=32G g16 input.com Use code with caution. 5. Troubleshooting Common Linux Issues gaussian 16 linux
Computational chemistry gains little from virtual cores; stick to physical ones. Efficient Scratch Management gaussian 16 linux
Gaussian 16 on Linux is a powerhouse for molecular modeling. By correctly configuring your environment and managing your scratch space, you can significantly reduce calculation times and improve reliability. gaussian 16 linux
At least 2GB per core, though 4GB+ is recommended for large frequency or CCSD(T) calculations.
To get the most out of your hardware, keep these Linux-specific tips in mind: Parallel Processing
Ensure you have source d the g16.profile .