programming
Affinity Groups
Announcements
Upcoming Events & Trainings
Title | Date |
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Spatial Data Science in the Cloud using Python | 8/13/24 |
Topics from Ask.CI
Knowledge Base Resources
Title | Category | Tags | Skill Level |
---|---|---|---|
AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure | Docs | ACES, documentation, TAMU, ai, visualization, deep-learning, machine-learning, neural-networks, login, authentication, composable-systems, gpu, nvidia, slurm, bash, modules, vim, anaconda, conda, programming, python, scikit-learn | Intermediate |
Using Linux commands in a python script (and the difference between the subprocess and os python modules) | Learning | cluster-management, programming, python | Beginner, Intermediate |
GPU Computing Workshop Series for the Earth Science Community | Learning | optimization, performance-tuning, profiling, parallelization, github, pytorch, tensorflow, oceanography, gpu, hpc-arch-and-perf, training, c, c++, fortran, cuda, jupyterhub, programming, programming-best-practices, python | Beginner |
Engagements
![](/sites/default/files/styles/landscape/public/match_engagement/2024-01/icesheetflow.jpg?itok=oUv2ml50)
GPU-accelerated Ice Sheet Flow Modeling
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.
People with Expertise
Jason Yalim
Arizona State University
Programs
Campus Champions
Roles
researcher/educator, research computing facilitator
![](/sites/default/files/styles/medium/public/pictures/movie.gif?itok=-FxSJKrr)
Expertise
Mark Perri
Sonoma State University
Programs
Campus Champions
Roles
researcher/educator, research computing facilitator
Expertise
Expertise
People with Interest
Paul Rulis
University of Missouri-Kansas City
Programs
Campus Champions
Roles
researcher/educator, research computing facilitator
![Paul Rulis](/sites/default/files/styles/medium/public/pictures/web-photo-medium.jpg?itok=BFjg77XD)
Interests
![Photo of Alexandra Lamtyugina](/sites/default/files/styles/medium/public/pictures/headshotMay2023.jpg?itok=4TIftxSE)
Interests
Martin Cuma
University of Utah
Programs
RMACC, Campus Champions
Roles
mentor, research computing facilitator