Organization
University of Utah
Contributors
Session Chairs
Presentations
Research and ACM SRC Posters
Research & ACM SRC Posters
TP
Doctoral Showcase
Research & ACM SRC Posters
Livestreamed
Recorded
TP
Birds of a Feather
Applications
Livestreamed
Recorded
TP
XO/EX
Research and ACM SRC Posters
Research & ACM SRC Posters
TP
Paper
HPC for Machine Learning
Performance Measurement, Modeling, & Tools
Programming Frameworks
Livestreamed
Recorded
TP
Panel
AI, Machine Learning, & Deep Learning
Architectures
SC Community Hot Topics
Not Livestreamed
Not Recorded
TP
Paper
Architectures & Networks
BP
System Software and Cloud Computing
Livestreamed
Recorded
TP
Research and ACM SRC Posters
Research & ACM SRC Posters
TP
Workshop
How effective is matrix reordering for improving performance of sparse matrix-vector multiplication?
12:10pm - 12:20pm CST Sunday, 16 November 2025 232Livestreamed
Recorded
TP
W
Panel
AI, Machine Learning, & Deep Learning
Power Use Monitoring & Optimization
SC Community Hot Topics
Livestreamed
Recorded
TP
Panel
AI, Machine Learning, & Deep Learning
HPC Software & Runtime Systems
Parallel Programming Methods, Models, Languages, & Environments
Livestreamed
Recorded
TP
Paper
HPC for Machine Learning
Performance Measurement, Modeling, & Tools
Programming Frameworks
Livestreamed
Recorded
TP
Birds of a Feather
State of the Practice
Livestreamed
Recorded
TP
XO/EX
Paper
Energy Efficiency
Performance Measurement, Modeling, & Tools
Power Use Monitoring & Optimization
State of the Practice
Livestreamed
Recorded
TP
Sessions
Panel
AI, Machine Learning, & Deep Learning
Power Use Monitoring & Optimization
SC Community Hot Topics
Livestreamed
Recorded
TP
Booth
4416
Exhibitor Description
In addition to deploying and operating high performance computational resources and providing advanced user support and training, the Center for High Performance Computing (CHPC) serves as an expert team to broadly support the increasingly diverse research computing needs on the University of Utah campus. These needs include support for big data, big data movement, data analytics, security, virtual machines, containers, machine learning and deep learning, Windows science application servers, protected environments for data mining and analysis of protected health information, and advanced networking.
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