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Knowledge Base Resources

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

Jeffrey Weekley

University of California - Santa Cruz

Programs

Campus Champions

Roles

research computing facilitator

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Expertise

Xiaoqin Huang

Rice University

Programs

ACCESS CSSN

Roles

mentor, research computing facilitator, research software engineer, cssn

xqhuang at Rice

Expertise

Patrick Clemins

Vermont EPSCoR, University of Vermont

Programs

Northeast

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Expertise

People with Interest

ali eydgahi

Programs

CCMNet

Roles

CCMNet

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Interests

Timothy Meeker

Programs

ACCESS CSSN

Roles

cssn

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Interests

Dung Vu

California State University-San Bernardino

Programs

ACCESS CSSN, Campus Champions

Roles

research computing facilitator, CIP

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Interests