Gaussian 16 Linux Jun 2026

sudo chmod 750 -R /usr/local/g16

Allocate roughly 2 GB to 4 GB per core.

In a multi-user Linux environment, jobs should never be run directly in the terminal shell. Use a scheduler like Slurm to manage resource distribution. Below is a production-ready Slurm submission script ( submit_g16.sh ): gaussian 16 linux

A successful run will end with the message Normal termination of Gaussian 16 in the test.log file. If you encounter an error (e.g., about missing pgi libraries), ensure the g16.login file correctly sources all necessary directories.

sudo mkdir -p /scratch/gaussian sudo chown -R root:g16users /scratch/gaussian sudo chmod 777 /scratch/gaussian Use code with caution. Environment Configuration sudo chmod 750 -R /usr/local/g16 Allocate roughly 2

A 64-bit Linux distribution (Ubuntu, CentOS, Red Hat, etc.). Sufficient RAM (at least 8GB, 16GB+ recommended).

Check that your input file has a blank line at the end. This is a mandatory requirement for Gaussian to parse the route section correctly. Below is a production-ready Slurm submission script (

Gaussian 16 speeds up calculations by dividing workloads across multiple CPU cores and nodes. Shared Memory Parallelism (OpenMP)

: Installation on common distributions like Ubuntu or CentOS involves extracting binary packages (e.g., .tbJ or .tbz ) and configuring environment variables via terminal.

: To keep a job running after closing the terminal, add an ampersand: g16 < input.com > output.log & Matter Modeling Stack Exchange Setting Up the Linux Environment

setenv g16root /usr/local setenv GAUSS_SCRDIR /scratch/g16_scratch source $g16root/g16/bsd/g16.login Use code with caution. Critical Step: The Scratch Directory ( GAUSS_SCRDIR )