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Bala Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Deborah Penchoff Campus Champions
Daniel Howard ACCESS CSSN, Campus Champions, CCMNet, RMACC
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Eden Furtak-Cole Campus Champions
Eric Brown Great Plains, Northeast
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Gaurav Khanna Campus Champions, CAREERS, Northeast
Gil Speyer ACCESS CSSN, RMACC, Campus Champions
Iman Rahbari Campus Champions, ACCESS CSSN
Yu-Chieh Chi Campus Champions
Jason Wells ACCESS CSSN, Campus Champions
Jason Yalim Campus Champions
Kenneth Bundy CAREERS
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Mohsen Ahmadkhani CCMNet, ACCESS CSSN
Martin Cuma RMACC, Campus Champions
Mattie Niznik Campus Champions
Michael Puerrer Campus Champions, Northeast
Jeffrey J. Nuc… CAREERS
Justin Oelgoetz Campus Champions, CCMNet
Rebecca Belshe Campus Champions, CCMNet
Mike Renfro Campus Champions, CCMNet
Shaohao Chen Northeast
Swabir Silayi ACCESS CSSN, CCMNet, Campus Champions
Sebastian Sensale Campus Champions
Tyler Burkett Kentucky
Xiaoge Wang Campus Champions

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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

Nihar Biradar

Rutgers University

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CAREERS

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student-facilitator

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Tejasvi Munge

New Jersey Institute of Technology

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CAREERS

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student-facilitator

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Expertise

Michael Durst

Middlebury College

Programs

Northeast

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researcher/educator

Expertise

People with Interest

Ying-Chih Sun

Harrisburg University

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student-facilitator

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Ritesh Bachhar

University of Rhode Island

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CAREERS

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student-facilitator

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Sapana Soni

LBNL

Programs

CCMNet

Roles

CCMNet

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Interests