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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.

Registration Open for XSEDE HPC Workshop OpenMP

Registration is available at

CHPC Fall 2019 Presentations

All presentations are located in INSCC Auditorium (Room 110)

K80 GPUs on notchpeak-shared-short partition

Posted October 4th, 2019

UofU Downtown Data Center Tour, November 1st, 2019 at 2 pm

Eventbrite - UofU Downtown Data Center Tour - October 24, 2017

Call for content for CHPC's SC19 booth

Posted September 26th, 2019

CHPC DOWNTIME: OS kernel updates on Clusters

  • (COMPLETED) October 8thstarting at 7:30
    Compute and interactive nodes onlonepeak, kingspeak, tangent, ash, and redwood.  Includes the frisco, atmos and meteo nodes
  • (COMPLETED) September 25th starting at 7:30
    Compute and interactive nodes on ember and notchpeak 

News History...


Who's who? Detecting and resolving sample anomalies in human DNA sequencing studies with Peddy.

By Brent S. Pedersen & Aaron R. Quinlan, University of Utah

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The potential for genetic discovery in human DNA sequencing studies is greatly diminished if DNA samples from the cohort are mislabelled, swapped, contaminated, or include unintended individuals. The potential for such errors is significant since DNA samples are often manipulated by several protocols, labs or scientists in the process of sequencing. We have developed Peddy to identify and facilitate the remediation of such errors via interactive visualizations and reports comparing the stated sex, relatedness, and ancestry to what is inferred from each individual's genotypes. Peddy predicts a sample's ancestry using a machine learning model trained on individuals of diverse ancestries from the 1000 Genomes Project reference panel. Peddy's speed, text reports and web interface facilitate both automated and visual detection of sample swaps, poor sequencing quality and other indicators of sample problems that, were they left undetected, would inhibit discovery. Peddy is used as part of our Base2 Genomics system for analyzing whole-genome sequencing data.

Available at

System Status

General Environment

last update: 2019-10-18 11:23:02
General Nodes
system cores % util.
ember 876/876 100%
kingspeak 819/832 98.44%
notchpeak 1060/1084 97.79%
lonepeak 1112/1112 100%
Owner/Restricted Nodes
system cores % util.
ash 7376/7376 100%
notchpeak 3858/3896 99.02%
ember 1220/1220 100%
kingspeak 5705/5812 98.16%
lonepeak 400/400 100%

Protected Environment

last update: 2019-10-18 11:20:04
General Nodes
system cores % util.
redwood 84/408 20.59%
Owner/Restricted Nodes
system cores % util.
redwood 3358/3392 99%

Cluster Utilization

Last Updated: 10/10/19