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Engagements

GPU-accelerated Ice Sheet Flow Modeling
University of North Dakota

Sea levels are rising (3.7 mm/year and increasing!)! The primary contributor to rising sea levels is enhanced polar ice discharge due to climate change. However, their dynamic response to climate change remains a fundamental uncertainty in future projections. Computational cost limits the simulation time on which models can run to narrow the uncertainty in future sea level rise predictions. The project's overarching goal is to leverage GPU hardware capabilities to significantly alleviate the computational cost and narrow the uncertainty in future sea level rise predictions. Solving time-independent stress balance equations to predict ice velocity or flow is the most computationally expensive part of ice-sheet simulations in terms of computer memory and execution time. The PI developed a preliminary ice-sheet flow GPU implementation for real-world glaciers. This project aims to investigate the GPU implementation further, identify bottlenecks and implement changes to justify it in the price to performance metrics to a "standard" CPU implementation. In addition, develop a performance portable hardware (or architecture) agnostic implementation.

Status: Finishing Up

People with Expertise

Patrick Clemins

Vermont EPSCoR, University of Vermont

Programs

Northeast

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Expertise

Jeff Falgout

United States Geological Survey

Programs

Campus Champions, RMACC

Roles

research computing facilitator, ci systems engineer

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Expertise

Chris Reidy

University of Arizona

Programs

Campus Champions, CCMNet

Roles

mentor, research computing facilitator, CCMNet

Chris Reidy

Expertise

People with Interest

Matthew Chung

University of California Riverside

Programs

Campus Champions

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Interests

DooSoo Yoon

University of Iowa

Programs

Campus Champions

Roles

research computing facilitator

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Interests

Xiaoyi Lu

University of California, Merced

Programs

ACCESS CSSN

Roles

cssn

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Interests