Monitor the progress of your calculation in real time using the tail command: tail -f water.log Use code with caution. Troubleshooting Common Linux Errors
Run the job in the background to prevent terminal lockups, redirecting the output to a log file: g16 < water.gjf > water.log & Use code with caution.
Before installing Gaussian 16 (G16), ensure your Linux system meets the necessary hardware and software benchmarks. Hardware Considerations
Select a Unix group that will own the Gaussian files. All users who need to run Gaussian should be members of this group. gaussian 16 linux
Gaussian 16 is the industry-standard electronic structure program used by computational chemists worldwide. Installing and optimizing it on a Linux environment requires careful attention to architecture, environment variables, and parallel processing configurations. This guide covers everything from prerequisites to executing your first quantum chemistry calculations. System Prerequisites and Requirements
Open a new terminal and type g16 . You should see the response “Entering Gaussian System, Link 0=g16” , confirming a successful installation.
🧠 Set %mem slightly below physical RAM to leave room for OS. Monitor the progress of your calculation in real
By mastering the installation, parallel tuning, and scripting techniques outlined in this guide, you transform Gaussian 16 from a black-box tool into a high-throughput, customizable scientific engine.
The GAUSS_SCRDIR directory should have abundant disk space and fast I/O—ideally local SSD or a dedicated scratch filesystem. If left undefined, Gaussian defaults to /tmp or the current directory, which can cause space and performance issues.
Exceeding a certain core count can actually performance due to increased thread management overhead and memory contention. A systematic scaling study for each unique system and method is essential; wasting cores does not speed up the calculation. Hardware Considerations Select a Unix group that will
Navigate to your desired installation directory (e.g., /usr/local or /opt ) and extract the source package.
Gaussian 16 Rev C.01+ supports NVIDIA GPUs for DFT (B3LYP, PBE0, M06-2X) and RI-MP2. On Linux, the speedup is dramatic (3-5x for hybrid functionals).
To run a job across multiple cores on a single machine, use the %NProcShared directive in your input file ( .gjf or .com ): %NProcShared=16 %Mem=32GB #P B3LYP/6-31G(d) Opt Use code with caution.