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Completed STANDARD GRANT National Science Foundation (US)

CC* Networking Infrastructure: Cyberinfrastructure improvements for multi-disciplinary data-intensive scientific research

$4.91M USD

Funder National Science Foundation (US)
Recipient Organization College of William and Mary
Country United States
Start Date Sep 01, 2021
End Date Mar 31, 2024
Duration 942 days
Number of Grantees 5
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2126240
Grant Description

This project addresses four areas of improvement in the College of William & Mary networking that expands its research capacity throughout its two campuses and aims at modernizing the data transfer capabilities. These areas are: Greater transfer speeds between main campus and the Virginia Institute of Marine Science; a Science DMZ for high-speed connectivity for research computing and a dedicated data transfer node which are monitored for quality of service with perfSONAR; addition of dedicated 10Gbps ports for offices and labs of major research network users; and the addition of a Globus license to enable efficient transfers to/from the campus research network.

This work upgrades William & Mary’s research computing network to continue supporting multi-disciplinary research which demands higher transfer rates for larger data files needed to support state-of-the-art research.

These network enhancements support cross-disciplinary transformative research and discovery by investigators from W&M’s School of Marine Science (Virginia Institute of Marine Science or VIMS) and W&M’s Global Research Institute, as well as by researchers from Physics, Computer Science and Data Science. The research from this group of scientists contributes largely to the advancement and transformation of various frontiers of knowledge and discovery.

Projects like 3D Environmental Flow Modeling, Lattice Quantum Chromodynamics (LQCD, Coastal Biogeochemical Modeling, Deep Learning for Estimates of Development Indicators, Location AI for National Security, the building of novel ML model execution optimizations, and simulations of accelerator designs are examples of the projects with great potential to advance knowledge and dependent on the faster network this new cyberinfrastructure expansion provides.

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.

All Grantees

College of William and Mary

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