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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: Complete

People with Expertise

Sapana Soni

LBNL

Programs

CCMNet

Roles

CCMNet

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Expertise

Kyle Krick

San Diego State University

Programs

ACCESS CSSN, Campus Champions

Roles

research computing facilitator, CIP

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Expertise

Seung Woo Son

University of Massachusetts Lowell

Programs

Northeast

Roles

mentor

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People with Interest

Iman Rahbari

University of Southern California

Programs

Campus Champions, ACCESS CSSN

Roles

mentor, researcher/educator, research computing facilitator, research software engineer, cssn

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Eason Chen

University Of Rhode Island

Programs

CAREERS

Roles

student-facilitator

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Justin Oelgoetz

Austin Peay State University

Programs

Campus Champions, CCMNet

Roles

mentor, researcher/educator, research computing facilitator, CCMNet

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Interests