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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.

CHPC DOWNTIME: Notchpeak cluster and frisco1, Tuesday May 25 starting at 8:00am

Posted May 5th, 2021

Allocation Requests for Summer 2021 are Due June 1st, 2021

Posted May 3rd, 2021

Spring 2021 CHPC Presentation Schedule

All presentations provided remotely via Zoom:

Upcoming Presentations:

Summer 2021 CHPC Presentation Schedulee Now Available!

Posted April 20th, 2021

CHPC OUTAGE: Science DMZ network, Thursday April 29 at 7pm

Posted: April 28th, 2021

CHPC ANNOUNCEMENT: /scratch/general/lustre 93% full - cleanup of usage

Re-posted April 12th, 2021
Posted March 28th, 2021

CHPC ANNOUNCEMENT: Changes to notchpeak-shared-short partition

Posted April 9th, 2021

CHPC ANNOUNCEMENT: SLURM access to  data transfer nodes in both the general and protected env

Posted April 8th, 2021

Spring 2021 CHPC Newsletter

CHPC system Issues

Posted April 2nd, 8:21am
Updated April 2nd, 9:34am
Updated April 2nd, 11am

  • (resolved) Apr 1, 11pm until Apr 2, 9:30am  kingspeak, notchpeak and ash cluster stopped allowing logins, and some other systems affected.
  • (resolved) Ondemand was down form late Apr 1 until about 11 am Apr 2.

Please let us know if you see further issues.

CHPC ANNOUNCEMENT: CHPC staff working remotely

News History...

An Agent-Based Model for Estimating Human Activity Patterns on the Wasatch Front

By Albert M. Lund1,2, Nicole B. Burnett2,3, Ramkiran Gouripeddi1,2, and Julio C. Facelli1,2

1Department of Biomedical Informatics, 2Center for Clinical and Translational Science, 3Department of Chemistry

It is difficult to measure the impact of air quality on human health because populations are mobile. Additionally, air quality data is reported at low geographic resolutions (> 1 km2), which makes it difficult to characterize acute local variations in air quality. There are few examples of combining human movement and activity data with high resolution air quality data to capture trajectory based exposure profiles in a comprehensive way. An agent-based model helps simulate human activities and locations throughout an arbitrary day. Simulation is used to overcome the limitations of existing datasets; simulated households based on aggregate data for the state of Utah are modeled and activity profiles generated from the American Time Use Survey of the U.S. Bureau of Labor Statistics. The activity profiles are combined with the simulated households to build individual trajectories of activity and location over the desired region of study.

System Status

General Environment

last update: 2021-05-08 13:03:03
General Nodes
system cores % util.
kingspeak 672/816 82.35%
notchpeak 1086/3212 33.81%
lonepeak 2652/2664 99.55%
Owner/Restricted Nodes
system cores % util.
ash 4372/4392 99.54%
notchpeak 10217/10844 94.22%
kingspeak 5669/5672 99.95%
lonepeak 76/416 18.27%

Protected Environment

last update: 2021-05-08 13:00:01
General Nodes
system cores % util.
redwood 28/460 6.09%
Owner/Restricted Nodes
system cores % util.
redwood 239/4724 5.06%

Cluster Utilization

Last Updated: 5/7/21