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  <h1>High Performance Computing (HPC) at USM</h1>
  <h1>High Performance Computing at USM</h1>
  <p>Welcome to HPC.</p>
  <p>Lets Compute...</p>
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Revision as of 19:35, 29 April 2017

Howdy

High Performance Computing at USM

Lets Compute...

 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.

Documentation topics

 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.

Capabilities

The HPC is expected to be fully operational on April 1, 2017, and will include the following capabilities:

Hardware

  • 2500+ compute cores
  • 5 High memory nodes (512 GB RAM per node)
  • 4GB per core on normal compute nodes
  • Rapid temporary filesystem 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

Citations to 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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