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.
Posted May 5th, 2021
Posted May 3rd, 2021
All presentations provided remotely via Zoom:
- XSEDE Summer Boot Camp: Tue-Fri Jun 1-4, 9am - 3pm
Posted April 20th, 2021
Posted: April 28th, 2021
Re-posted April 12th, 2021
Posted March 28th, 2021
Posted April 9th, 2021
Posted April 8th, 2021
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.
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
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.