Name | Region | Skills | Interests |
---|---|---|---|
Adam Carlson | Campus Champions | ||
Charles Forsyth | Campus Champions | ||
Cody Stevens | Campus Champions | ||
Stephen Cousins | Campus Champions | ||
Edwin Posada | Campus Champions | ||
Jeff Falgout | Campus Champions, RMACC | ||
Julie Ma | ACCESS CSSN, At-Large, Campus Champions, CAREERS, Northeast | ||
Jeffrey Weekley | Campus Champions | ||
Jason Wells | ACCESS CSSN, Campus Champions | ||
Marina Kraeva | Campus Champions | ||
Ron Rahaman | Campus Champions | ||
Steven Kuhlo | TRECIS | ||
Sumit Saluja | Campus Champions | ||
Trey Breckenridge | Campus Champions |
Name | Roles | Skills | Interests |
---|---|---|---|
Julie Ma | rcf steering committee |
Title | Date |
---|---|
Request for tutorial proposals for the Supercomputing 2024 conference (SC'24) | 02/25/24 |
Title | Date |
---|---|
COMPLECS: HPC Hardware Overview | 4/04/24 |
Title | Category | Tags | Skill Level |
---|---|---|---|
Slurm Tutorials | Learning | administering-hpc, cluster-management, hpc-cluster-architecture, training | Beginner |
Warewulf documentation | Website | documentation, administering-hpc, distributed-computing, hpc-cluster-architecture, provisioning, containers | Beginner, Intermediate |
A personalized learning system that adapts to learners' interests, needs, prior knowledge, and available resources is possible with artificial intelligence (AI) that utilizes natural language processing in neural networks. These deep learning neural networks can run on high performance computers (HPC) or on quantum computers (QC). Both HPC and QC are emergent technologies. Understanding both systems well enough to select which is more effective for a deep learning AI program, and show that understanding through example, is the ultimate goal of this project. The entry to learning technologies such as HPC and QC is narrow at present because it relies on classical education methods and mentoring. The gap between the knowledge workers needed, which is in high demand, and those with the expertise to teach, which is being achieved at a much slower rate, is widening. Here, an AI cognitive agent, trained via deep learning neural networks, can help in emergent technology subjects by assisting the instructor-learner pair with adaptive wisdom. We are building the foundations for this AI cognitive agent in this project.
The role of the student facilitator will involve optimizing a deep learning neural network, comparing and contrasting with the newest technologies, such as a quantum computer (and/or a quantum computer simulator) and a high performance computer and showing the efficiency of the different computing approaches. The student facilitator will perform these tasks at the rate described in the proposal. Milestone work will be displayed and shared publicly via posting to the Jupyter Notebooks on Google Colab and linked to regular Github uploads.
Mississippi State University
Campus Champions
research computing facilitator
Old Dominion University
Campus Champions, Northeast, ACCESS CSSN
mentor, research computing facilitator, cssn
California State University-San Bernardino
ACCESS CSSN, Campus Champions
research computing facilitator, CIP