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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.

DBS Physical Database

The International Neuromodulation Registry: A Graph Database Representation for Neuromodulation Therapies

By Hedges, D.M.1,2, Duffley, G.1,3, Hegman, J.C.1, Gouripeddi, R.2,4, Butson, C.R.1,3,5,6,7

1Scientific Computing and Imaging (SCI) Institute2Department of Biomedical Informatics3Department of Biomedical Engineering4Center for Clinical and Translational Science5Department of Neurology6Department of Neurosurgery7Department of Psychiatry,

Deep Brain Stimulation (DBS) is a form of Neuromodulation therapy, often used in patients with many different types of neurological disorders. However, DBS is a rare treatment and medical centers have few patients who qualifying for DBS, meaning that most DBS studies are statistically underpowered and have chronically low n values. Here, we present a platform designed to combine disparate datasets from different centers. Using this platform, researchers and clinicians will be able to aggregate patient datasets, transforming DBS studies from being center-based to being population-based.

Graph databases are increasing in popularity due to their speed of information retrieval, powerful visualization of complex data relationships, and flexible data models. Our Neo4j DBMS is physically located in the University of Utah Center for High-Performance Computing (CHPC) Protected Environment on a virtual machine, giving needs-based flexibility for both memory and storage.

This patient registry has been build on a next-generation graph database. Through a formal, but flexible, data model and ontology, this platform is able to harmonize disparate data types and allows for simple visualizations of complex data types.

Anticipated Use Cases: Cohort discovery, data and imaging download, exploratory analysis.

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System Status

General Environment

last update: 2019-04-21 00:33:03
General Nodes
system cores % util.
ember 912/960 95%
kingspeak 880/880 100%
notchpeak 900/1028 87.55%
lonepeak 1088/1088 100%
Owner/Restricted Nodes
system cores % util.
ash 7252/7304 99.29%
notchpeak 1632/1648 99.03%
ember 1220/1220 100%
kingspeak 5920/5920 100%
lonepeak 220/400 55%

Protected Environment

last update: 2019-04-21 00:30:05
General Nodes
system cores % util.
redwood 0/500 0%
Owner/Restricted Nodes
system cores % util.
redwood 192/3232 5.94%

Cluster Utilization

Last Updated: 4/17/19