CHPC - Research Computing and Data Support for the University

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, and advanced networking.

If you are new to CHPC, the best place to start to get more information on CHPC resources and policies is our Getting Started page.

Upcoming Events:

Allocation Requests for Summer 2024 are Due June 1st, 2024

Posted May 1st, 2024

CHPC Downtime: Tuesday March 5 starting at 7:30am

Posted February 8th, 2024

Two upcoming security related changes

Posted February 6th, 2024

Allocation Requests for Spring 2024 are Due March 1st, 2024

Posted February 1st, 2024

CHPC ANNOUNCEMENT: Change in top level home directory permission settings

Posted December 14th, 2023

CHPC Spring 2024 Presentation Schedule Now Available

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: 2024-07-15 20:53:04

General Nodes
system	cores	% util.
kingspeak	764/972	78.6%
notchpeak	2241/3212	69.77%
lonepeak	2970/3060	97.06%
Owner/Restricted Nodes
system	cores	% util.
ash	384/1152	33.33%
notchpeak	8815/19820	44.48%
kingspeak	1444/5340	27.04%
lonepeak	32/416	7.69%

Protected Environment

last update: 2024-07-15 20:50:04

General Nodes
system	cores	% util.
redwood	22/616	3.57%
Owner/Restricted Nodes
system	cores	% util.
redwood	1930/6408	30.12%