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Open OnDemand An intuitive, innovative, and interactive interface to remote computing resources.Open OnDemand helps computational researchers and students efficiently utilize remote computing resources by making… ondemandadministering-hpccluster-management +4 more tags Login to join
hpc.social High Performance Computing and related fields, including Big Data, Research Computing, and related hardware and software optimized for these fields, including research software engineering and… administering-hpccluster-managementcluster-support +6 more tags Login to join

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CI Links

Title Category Tags Skill Level
HPCwire Website documentationpytorchdata-science +6 more tags Beginner, Intermediate, Advanced
Open OnDemand Website ondemandadministering-hpccluster-management +4 more tags Beginner, Intermediate, Advanced

Engagements

High Performance Computing vs Quantum Computing for Neural Networks supporting Artificial Intelligence
Pace University

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.

Status: Complete

People with Expertise

Jeff Falgout

United States Geological Survey

Programs

Campus Champions, RMACC

Roles

research computing facilitator, ci systems engineer

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Expertise

Craig Earley

University of Colorado Boulder

Programs

RMACC

Roles

mentor

Placeholder headshot

Expertise

Oriana Silva

University of North Texas

Programs

ACCESS CSSN

Roles

student-facilitator

Oriana Silva

Expertise

People with Interest

Robert Kudyba

Columbia University in the City of New York

Programs

Campus Champions

Roles

research computing facilitator

Placeholder headshot

Interests

Brian Haymore

University of Utah

Programs

RMACC, Campus Champions

Roles

mentor, research computing facilitator

Interests

+66 more tags

Michael Kyle

University of Delaware

Programs

Campus Champions

Roles

research computing facilitator

Interests