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Our High Performance Computing (HPC) resources allow researchers to run compute intensive, large memory programs quickly and efficiently; and store data securely and accessibly.
- Polaris:
- easy to log in at the command line and use
- used for running computationally intensive programs such as Matlab, Stata, Mathematica and statistical applications, or programs that require a lot of shared memory. It has ~5 TB of local scratch space available, as of January 2024
- more about requesting an account to get started with Polaris
- Andes
- easy to log in at the command line and use
- used for running statistical packages and scientific applications which need large amounts of memory and scratch space. ~5 TB of fast scratch space is available as of January 2024
- more about requesting an account to get started with Andes
- Discovery
- uses a 'scheduler' program to submit jobs to a queue, rather than interactively (for example, .m Matlab programs can be run, but not from within the Matlab GUI interface)
- has features to view and monitor the load on the computational resources environment
- Job submissions to Discovery are then channeled through a job scheduler to allow for efficient management and allocation of computational resources. This scheduler is known as a 'Slurm' scheduler, and uses a batch-scripting language. This method ensures an equitable distribution of resources and optimal CPU usage. For guidance on scheduling jobs, please refer to the Scheduling Jobs to Run-Slurm Overview
- see this page on cost of the community model
- tutorials and details about Discovery and the Slurm scheduler and the overall service description