CC* Campus Compute: Colgate Compute Acceleration for Research and Education
- Institution
- Colgate University, NY
- Principal investigator
- Niranjan Davray
- Funding
- $500K
- Duration
- 2024–2026
Moonbase score
Still being scored
Abstract
The Colgate Compute Acceleration for Research and Education (CCARE) project upgrades Colgate’s cyberinfrastructure and enhances the research capabilities of Colgate University by adding computational capability and increasing the network speed of Colgate’s supercomputer, thus enabling researchers to collaborate with other institutions and access advanced computational scientific software. Through the CCARE project, Colgate contributes computing resources to the Open Science Pool of the OSG, thus contributing to research advancements across diverse domains on a national level. CCARE has a broader impact on the New York six liberal arts consortium by fostering the exchange of research computing knowledge among its members, and on the New York Madison county public schools by leading and supporting STEM educational opportunities via Colgate’s supercomputer computational resources. The CCARE project transforms Colgate’s research-DMZ network with the use of IPv6 and upgrades Colgate supercomputer’s networking infrastructure with latest InfiniBand technology, while adding state-of-the-art GPU-Compute designed for artificial intelligence tasks and training of machine learning models. In the era of generative artificial intelligence, the CCARE project enables an efficient and inclusive approach to scientific discovery, supporting unique and often interdisciplinary research requirements in various fields such as training machine learning models, analyzing biological datasets, studying virus mutations, studying organometallic compounds, analyzing satellite remote sensing data, and applying deep learning techniques in the environmental and social sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Niranjan DavrayPI
- Anthony R Chianese
- Michael Loranty
- Kyriakos Tsoukalas
- Grusha Prasad
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