Gaussian 09 (G09) is a widely used computational chemistry software that performs quantum mechanical calculations. By default, Gaussian 09 limits memory allocation to 1500 MB and 4 processors per job. However, for large molecular systems or high-level calculations, increasing memory and processor usage can significantly improve performance.
In this blog post, we will explore how to increase compute memory size and processor allocation in Gaussian 09 beyond these default limits.
Understanding Gaussian 09 Memory and Processor Limits
Gaussian 09 utilizes memory and CPU resources based on user-defined parameters in the input file or system settings. The key parameters affecting memory and processors are:
- %Mem – Controls the amount of memory allocated per job.
- %NProcShared – Defines the number of CPU cores to be used.
By default, Gaussian 09 sets:
- %Mem = 1500MB
- %NProcShared = 4
For demanding calculations, increasing these values can lead to faster and more efficient computations.
How to Increase Memory Allocation in Gaussian 09
To allocate more memory beyond 1500 MB, modify the %Mem directive in your Gaussian input file.
Example: Allocating More Memory
%Mem=8000MB
This command increases the memory allocation to 8000 MB (8GB).
If you have sufficient RAM, you can assign more memory. However, avoid allocating all available RAM to prevent system slowdowns or crashes.
How to Increase the Number of Processors
Gaussian 09 allows multi-core processing. To use more than 4 processors, modify the %NProcShared directive.
Example: Assigning More Processors
%NProcShared=8
This command instructs Gaussian 09 to utilize 8 CPU cores. Ensure your system has at least 8 physical or logical cores to handle the workload.
System-Level Configuration for Higher Resource Allocation
If Gaussian 09 still limits memory or processor usage, check the system settings:
1. Increase Memory Allocation in Gaussian Configuration File
In some cases, Gaussian 09’s global configuration file restricts memory usage. Modify the Gaussian environment settings:
For Linux/Mac Users:
- Edit the
.bashrcor.bash_profilefile and add:export GAUSS_MEMDEF=8000MB export GAUSS_SCRDIR=/scratch - Restart the terminal for changes to take effect.
For Windows Users:
- Modify the Gaussian 09 environment variables in the system settings.
2. Check System RAM Availability
Ensure your system has sufficient free RAM before allocating more memory. Use commands like:
- Linux:
free -m - Windows: Task Manager > Performance > Memory
3. Check CPU Availability
Confirm available cores using:
- Linux:
lscpu - Windows: Task Manager > Performance > CPU
Optimizing Gaussian 09 Performance
1. Use Scratch Disk Storage
Gaussian 09 uses temporary storage (%Scr) for calculations. Assign a fast SSD or high-speed disk as the scratch directory:
%Scr=/path_to_fast_storage
2. Distribute Tasks Across Multiple Nodes (Cluster Computing)
For high-performance computing (HPC) setups, distribute tasks across multiple nodes:
%NProcShared=32
Ensure Gaussian 09 is configured for parallel execution on the cluster.
3. Use Efficient Basis Sets and Methods
Instead of increasing memory drastically, optimize calculations by selecting:
- Smaller but accurate basis sets (6-31G instead of 6-311G*).
- Density Functional Theory (DFT) instead of Post-Hartree-Fock methods when applicable.
Common Errors and Troubleshooting
1. Memory Allocation Error
Error Message:
Error in input file: Requested memory exceeds available memory.
Solution:
- Check available RAM using
free -m. - Reduce
%Memallocation. - Ensure Gaussian’s configuration allows higher memory allocation.
2. Processor Limit Error
Error Message:
Cannot use more than 4 processors.
Solution:
- Verify system supports more cores (
lscpu). - Ensure Gaussian 09 is correctly installed for multi-threading.
3. Gaussian 09 Crashing on Startup
Solution:
- Check environmental variables (
GAUSS_MEMDEF,GAUSS_SCRDIR). - Run Gaussian as an administrator (Windows) or use
sudo(Linux).
Final Thoughts
Yes! It is possible to increase memory and processor usage in Gaussian 09 beyond 1500 MB and 4 processors by modifying input file settings and system configurations. However, ensure your system has enough resources to support the changes.
If you are using large calculations, consider parallel computing or upgrading to a high-performance computing system for better efficiency.