Gaussian 16 Linux May 2026

# Reduce swapping echo 10 > /proc/sys/vm/swappiness # Use 'none' or 'noop' scheduler for NVMe scratch disks echo noop > /sys/block/nvme0n1/queue/scheduler If you have abundant RAM, put GAUSS_SCRDIR in RAM:

#!/bin/bash for input in *.gjf; do base=$input%.gjf echo "Running $base at $(date)" >> job.log # Run with 4 cores, save unique log g16 -p=4 $input $base.log # Check for convergence if grep -q "Normal termination" $base.log; then echo "SUCCESS: $base" >> job.log # Extract final SCF energy grep "SCF Done" $base.log | tail -1 >> energies.txt else echo "FAILED: $base" >> job.log fi done Extract Gibbs free energy from a frequency job: gaussian 16 linux

sudo nano /etc/profile.d/gaussian.sh Add: # Reduce swapping echo 10 > /proc/sys/vm/swappiness #

sudo apt update && sudo apt install libc6 libstdc++6 libopenmpi-dev openmpi-bin For RHEL/Fedora: The rule of thumb: %Mem = (Total RAM / Number of cores) * 0

#!/bin/bash #SBATCH --job-name=G16_HF #SBATCH --nodes=1 #SBATCH --ntasks-per-node=16 #SBATCH --mem=64G #SBATCH --time=24:00:00 export GAUSS_SCRDIR=/local/scratch/$SLURM_JOB_ID mkdir -p $GAUSS_SCRDIR Run Gaussian with OpenMPI hybrid g16 < input.com > output.log Clean up rm -rf $GAUSS_SCRDIR Benchmarks: Tuning Gaussian 16 on Linux Raw installation is not enough. You must optimize for your hardware. Memory Tuning In your input file, do not allocate all RAM ( %Mem=64GB ) if you run parallel jobs. The rule of thumb: %Mem = (Total RAM / Number of cores) * 0.8 (leave 20% for OS overhead). Linux Kernel Parameters For heavy DFT calculations (e.g., B3LYP/def2-TZVPP on 100 atoms), tune the swappiness and I/O scheduler:

g16 -p=8 test.com test.log Flag explanation: -p=8 uses 8 cores on the local machine. Most universities run Gaussian 16 Linux on SLURM clusters. Here is an optimal SLURM script: