High Performance Computing at USM

Available documentation

To find information use the search box on the top right corner of the screen, or categorically browse the wiki using the Documentation topic links provided below.

HPC Wiki Categories((.list-group-item))

Documentation topics

Connecting to Magnolia((.list-group-item)) Tutorials((.list-group-item)) Workshops((.list-group-item)) Capabilities((.list-group-item))

News

FAQs:

New to HPC at USM? Start with the FAQs.

Workshops:

Introduction to GNU/Linux, parallel programming, and MATLAB workshops coming up. Take a look at the current schedule.

For proper citation of the HPC infrastructure, see the citations page.

Capabilities

The HPC, fully operational on September 5, 2017, includes the following capabilities:

Hardware

1896 compute cores
7168 CUDA cores
4 High memory nodes (512 GB RAM per node)
20 cores, and 6 GB RAM per core on normal compute nodes
Rapid temporary filesystem (LUSTRE) for application execution
Network attached storage for data archiving

Software

(See Software page for detailed information)

Intel and GNU Fortran, C, and C++ compilers
Other software can be installed upon request

DataSpace digital archive

(See DataSpace for more information)

Archive for raw data, documents, theses & dissertations
Front-end for searching/processing data

Funding

Support for this project was provided by the National Science Foundation under the Major Research Instrumentation (MRI) program via Grant # ACI 1626217

How to Cite the HPC Infrastructure

Please reference USM HPC in any research report, journal or publication. The recognition of the resources you used to perform research is important for acquiring funding for the next generation hardware, support services, and our Research & Development activities in HPC, visualization, data storage, and grid infrastructure.

The suggested content of a citation is:

The authors acknowledge HPC at The University of Southern Mississippi

supported by the National Science Foundation under the Major Research

Instrumentation (MRI) program via Grant # ACI 1626217.

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