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Mentors and Regional Facilitators
Name Region Skills Interests
Adam Carlson Campus Champions
Aaron Jezghani Campus Champions
Anita Schwartz Campus Champions
Andrew Sherman ACCESS CSSN, Campus Champions, CAREERS
Brian Gregor Northeast, Campus Champions
Kevin Bryan Campus Champions
Craig Gross Campus Champions, CCMNet
Cody Stevens Campus Champions, CCMNet
Cesar Sul ACCESS CSSN, Campus Champions
Bala Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Deborah Penchoff Campus Champions
Daniel Howard ACCESS CSSN, Campus Champions, CCMNet, RMACC
Darshan Sarojini ACCESS CSSN
Elie Alhajjar ACCESS CSSN, CCMNet
Eden Furtak-Cole Campus Champions
Eric Brown Great Plains, Northeast
Fernando Garzon ACCESS CSSN
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
Lakitha Wijeratne TRECIS
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

Affinity Groups

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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

Eden Furtak-Cole

Desert Research Institute

Programs

Campus Champions

Roles

research computing facilitator

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Expertise

Darshan Sarojini

Virginia Polytechnic Institute and State University

Programs

ACCESS CSSN

Roles

mentor, researcher/educator

Portrait

Expertise

Shaohao Chen

Massachusetts Institute of Technology

Programs

Northeast

Roles

mentor

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Expertise

People with Interest

Lakitha Wijeratne

The University of Texas at Dallas

Programs

TRECIS

Roles

mentor, researcher/educator

Interests

Igor Nachevnik

Rutgers

Programs

CAREERS

Roles

student-facilitator

Interests

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ali eydgahi

Programs

CCMNet

Roles

CCMNet

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Interests