CHPC - Research Computing 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 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. Visit our Getting Started page for more information.

Tangent users -- issue of new jobs not starting -- resolved Sunday May 29

Please feel free to resume submitting jobs on this cluster.

Posted May 230th, 2016: 

Summer Presentation Series begins June 2nd

Recently added the python presentation

Changes to /scratch/kingspeak/serial

May 2nd, Noon: Read Only

June 6th, Noon:  Taken offline to be rebuilt

Unplanned Network outage starting around 7 a.m. May 19th, may last into May 20th

Posted May 19th, 2016 

Spring 2016 Newsletter

Use of general CHPC interactive Nodes

Posted May 3rd, 2016

Research Data Services Survey


Allocation Requests for Summer 2016 are due June 1st, 2016 


Workshop on being a "Cyberinfrastructure Research and Education Facilitator"

Sunday August 7th - Saturday August 13th, 2016

Applications are now open!

/scratch/general/lustre now available for use on ember and lonepeak

XSEDE HPC Monthly Workshop Series Event

June 14-17, 2016
Topics covered: OpenMP (shared memory parallelization), OpenACC (GPU programming) and MPI (distributed memory parallelization)


Open Science Grid (OSG) User School 2016

Application Period: Mar 14 - Apr 15, 2016
OSG User School: 25-29 July 2016
Website and brief application:

CHPC on Twitter


Prediction of Crystal Structures from First Principle Calculations

Using CHPC resources a team of researchers from the University of Utah and the University of Buenos Aires has demonstrated that it is possible to predict the crystal structures of a biomedical molecule using solely first principles calculations.  The results on glycine polymorphs shown in the figure were obtained using the Genetic Algorithms search implemented in Modified Genetic Algorithm for Crystals coupled with the local optimization and energy evaluation provided by Quantum Espresso. All three of the ambient pressure stable glycine polymorphs were found in the same energetic ordering as observed experimentally.  The agreement between the experimental and predicted structures is of such accuracy that they are visually almost indistinguishable.

The ability to accomplish this goal has far reaching implications well beyond just intellectual curiosity.  Crystal structure prediction can be used to obtain an understanding of the principles that control crystal growth.  More practically, the ability to successfully predict crystal structures and energetics based on computation alone will have a significant impact in many industries for which crystal structure and stability plays a critical role in product formulation and manufacturing, including pharmaceuticals, agrochemicals, pigments, dyes and explosives.

Lund AM, Pagola GI, Orendt AM, Ferraro, MB, Facelli, JC (2015). Crystal structure prediction from first principles: The crystal structure of glycine. Chemical Physics Letters, 626, 20-24. 

System Status

last update: 05/31/16 1:51 pm
General Nodes
system procs % util.
ember 912/1008 90.48%
kingspeak 800/800 100%
lonepeak 256/256 100%
Restricted Nodes
system procs % util.
ash 6808/7448 91.41%
apexarch Status Unavailable
ember 276/708 38.98%
kingspeak 4616/4808 96.01%
lonepeak 832/896 92.86%

Cluster Utilization