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Center for High Performance Computing

Research Computing and Data Support for the University Community

 

In addition to deploying and operating high-performance computational resources and providing advanced user support and training, CHPC serves as an expert team to broadly support the increasingly diverse research computing and data needs on campus. These needs include support for big data, big data movement, data analytics, security, virtual machines, Windows science application servers, protected environments for data mining and analysis of protected health information, advanced networking, and more.

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Announcing the Upcoming Retirements of Julia Harrison and Anita M. Orendt
Julia Harrison
Julia Harrison

After nearly four decades of dedicated service at the University of Utah, Julia Harrison is retiring as the Operations Director of the Center for High Performance Computing.

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Anita M. Orendt
Anita M. Orendt

Anita M. Orendt is a dedicated educator and researcher with a rich background in physical chemistry. Anita has made significant contributions to the academic community at the University of Utah.

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Upcoming Events:

CHPC PE DOWNTIME: Partial Protected Environment Downtime  -- Oct 24-25, 2023

Posted October 18th, 2023


CHPC INFORMATION: MATLAB and Ansys updates

Posted September 22, 2023


CHPC SECURITY REMINDER

Posted September 8th, 2023

CHPC is reaching out to remind our users of their responsibility to understand what the software being used is doing, especially software that you download, install, or compile yourself. Read More...

News History...

Multiscale Modeling of Anion-exchange Membrane for Fuel Cells

By Jibao Lu, Liam Jacobson, Justin Hooper, Hongchao Pan, Dmitry Bedrov, and Valeria Molinero, Kyle Grew and Joshua McClure, and Wei Zhang and Adri Duin

University of Utah, US Army Research Laboratory, Pennsylvania State University

To our knowledge, this is the first coarse grain (CG) model that includes explicitly each water and ion, and accounts for hydrophobic, ionic, and intramolecular interactions explicitly paramterized to reproduce multiple properties of interest for hydrated polyelectrolyte membranes. The CG model of polyphenylene oxide/trimethylamine is about 100 times faster than the reference atomistic GAFF model. The strategy implemented here can also be used in parameterization of CG models for other substances, such as biomolecular systems and membranes for desalination, water purification and redox flow batteries. We anticipate that the large spatial and temporal simulations made possible by the CG model will advance the quest for anion-exchange membranes with improved transport and mechanical properties.

System Status

General Environment

last update: 2024-12-27 09:11:02
General Nodes
system cores % util.
kingspeak 834/952 87.61%
notchpeak 3164/3212 98.51%
lonepeak 940/1596 58.9%
Owner/Restricted Nodes
system cores % util.
ash Status Unavailable
notchpeak 9088/22028 41.26%
kingspeak 3440/5244 65.6%
lonepeak 416/416 100%

Protected Environment

last update: 2024-12-27 09:10:05
General Nodes
system cores % util.
redwood 40/616 6.49%
Owner/Restricted Nodes
system cores % util.
redwood 16/4904 0.33%


Cluster Utilization

Last Updated: 12/17/24