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Center for High Performance Computing

Research Computing and Data Support for the University Community

 

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 and data 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, advanced networking, and more.

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Announcing the Upcoming Retirements of Julia Harrison and Anita M. Orendt
Julia Harrison
Julia Harrison

After nearly four decades of dedicated service at the University of Utah, Julia Harrison is retiring as the Operations Director of the Center for High Performance Computing.

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Anita M. Orendt
Anita M. Orendt

Anita M. Orendt is a dedicated educator and researcher with a rich background in physical chemistry. Anita has made significant contributions to the academic community at the University of Utah.

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Upcoming Events:

CHPC PE DOWNTIME: Partial Protected Environment Downtime  -- Oct 24-25, 2023

Posted October 18th, 2023


CHPC INFORMATION: MATLAB and Ansys updates

Posted September 22, 2023


CHPC SECURITY REMINDER

Posted September 8th, 2023

CHPC is reaching out to remind our users of their responsibility to understand what the software being used is doing, especially software that you download, install, or compile yourself. Read More...

News History...

VTA Surfaces Modeled

The Activating Function Based Volume of Tissue Activated (VTA)

By Gordon Duffley1,2, Daria Nesterovich Anderson1,2, Johannes Vorwerk, PhD2, Alan "Chuck" Dorval, PhD1, Christopher R. Butson, PhD1-4

1Department of Biomedical Engineering, 2Scientific Computing & Imaging (SCI) Institute, 3Departments of Neurology and Neurosurgery, 4Department of Psychiatry, University of Utah

Computational models of the volume of tissue activated (VTA) are commonly used both clinically and for research. Because of the computational demands of the traditional axon model approach, alternative approaches to approximate the VTA have been developed. The goal of this study is to evaluate multiple approaches of calculating approximations of the VTA for monopolar and bipolar stimulations on cylindrical and directional lead designs.

Activating function and electric field norm threshold values were dependent on stimulation amplitude, electrode configuration, and pulse width. All methods resulted in highly similar approximations of the VTA for monopolar stimulation for both the directional the cylindrical DBS lead designs. For bipolar stimulation, the axon model method and AF(Max, Tang) produced similar approximations of the VTA. For bipolar stimulation, AF(GP, Max) produced an approximation of the VTA that was larger than any of the other methods. AF(GP, Max) is not biased by only using tangentially oriented axons, unlike the axon model method and AF(Max, Tang).

Read the paper in the Journal of Neural Engineering.

System Status

General Environment

last update: 2024-11-20 15:31:02
General Nodes
system cores % util.
kingspeak 942/952 98.95%
notchpeak 2940/3212 91.53%
lonepeak 1875/1932 97.05%
Owner/Restricted Nodes
system cores % util.
ash Status Unavailable
notchpeak 17124/22004 77.82%
kingspeak 2506/5244 47.79%
lonepeak 72/416 17.31%

Protected Environment

last update: 2024-11-20 15:30:04
General Nodes
system cores % util.
redwood 548/628 87.26%
Owner/Restricted Nodes
system cores % util.
redwood 2717/6444 42.16%


Cluster Utilization

Last Updated: 11/4/24