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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.

System Issues December 15th, 2017

Posted: December 15th, 2017


Ember Downtime Notice -- December 14 starting at 8am

Posted: November 30th, 2017

If the ember downtime is successful, remaining clusters will have a similar downtime on December 21st.


CHPC Fall 2017 Newsletter


Tangent Users - issue with jobs not starting - some jobs still not starting successfully 

Updated October 24th, 2017 


Potential troubles running programs after clusters OS September 28th

Posted October 4th, 2017 


 Matlab upgrade (R2017b)


 New general nodes on Lonepeak

Posted: August 24th, 2017 


CHPC on Twitter

News History...

Tracking Pressure Features

By Alexander Jacques, MesoWest/SynopticLabs and Atmospheric Sciences

Center for High Performance Computing resources were used to model the progression of a mesoscale gravity wave generated by a large storm system on April 26–27, 2011.

A mesoscale gravity wave, generated by a large storm system in the southern United States, moved northward through the central United States causing short-term changes in surface wind speed and direction. This animation shows efforts to detect and evaluate the negative mesoscale surface pressure perturbation generated by this wave. Detected positive (red contours) and negative (blue contours) perturbations are determined from perturbation analysis grids, generated every 5 minutes, using USArray Transportable Array surface pressure observations (circle markers). Best-track paths for the perturbations are shown via the dotted trajectories. To identify physical phenomena associated with the perturbations, conventional radar imagery was also leveraged. It can be seen here that the detected feature migrates north away from the majority of the precipitation, which is often seen with mesoscale gravity wave features.

System Status

last update: 12/17/17 6:32 pm
General Nodes
system cores % util.
ember 936/984 95.12%
kingspeak 592/768 77.08%
lonepeak 616/1112 55.4%
Restricted Nodes
system cores % util.
ash 3372/7116 47.39%
apexarch Status Unavailable
ember 1316/1316 100%
kingspeak 3376/7196 46.91%
lonepeak 80/380 21.05%

Cluster Utilization

Last Updated: 12/15/17