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Research Spending & Results

Award Detail

Awardee:WEST VIRGINIA UNIVERSITY RESEARCH CORPORATION
Doing Business As Name:West Virginia University Research Corporation
PD/PI:
  • Blake Mertz
  • (304) 293-9166
  • blake.mertz@mail.wvu.edu
Co-PD(s)/co-PI(s):
  • Sarah Spolaor
  • Werner Geldenhuys
  • Piyush M Mehta
  • Gianfranco Doretto
Award Date:09/17/2021
Estimated Total Award Amount: $ 1,099,448
Funds Obligated to Date: $ 1,099,448
  • FY 2021=$1,099,448
Start Date:10/01/2021
End Date:09/30/2024
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:MRI: Acquisition of Dolly Sods GPU Cluster for Accelerated High-Performance Computing and Applications in Machine Learning and Artificial Intelligence in West Virginia
Federal Award ID Number:2117575
DUNS ID:191510239
Program:Major Research Instrumentation
Program Officer:
  • Alejandro Suarez
  • (703) 292-7092
  • alsuarez@nsf.gov

Awardee Location

Street:P.O. Box 6845
City:Morgantown
State:WV
ZIP:26506-6845
County:Morgantown
Country:US
Awardee Cong. District:01

Primary Place of Performance

Organization Name:Pittsburg Supercomputing Center
Street:4350 Northern Pike
City:Monroeville
State:PA
ZIP:15146-2808
County:Monroeville
Country:US
Cong. District:18

Abstract at Time of Award

This project will enable West Virginia University (WVU) to acquire a special-purpose graphics processing unit (GPU) cluster called Dolly Sods. Dolly Sods will be a critical driver of WVU's goal of developing capabilities in utilizing big data, artificial intelligence (AI), and machine learning (ML) to enable transformational research in a broad range of fields encompassing drug development, interstellar phenomena, biometrics, material design, and business logistics and management. In conjunction with other institutions of higher learning in West Virginia, development of these capabilities will in turn lead to training an AI-ready West Virginian workforce that can leverage their skills to strengthen current relationships with regional high performance computing (HPC) centers as well as forging new relationships with federal and industrial partners. The creation of training opportunities for first generation college students, female students, and those from marginalized communities will aid in the diversification of the computationally intensive workforce and will be invaluable to West Virginia. Finally, this acquisition will contribute to keeping the United States at the forefront of AI development. The rapid adoption of hardware accelerators (e.g., GPUs) in the research computing community has facilitated massively increased compute capability and application of ML and AI approaches to solving big data problems in every STEM field and non-traditional fields like business data analytics. The requested acquisition of the Dolly Sods cluster will enable cutting-edge research for efforts in diagnostic imaging of tumors, high-throughput screening of small molecule drug design, on-the-fly detection of interstellar phenomena, design and optimization of data compression algorithms used in space flight, computer vision of medical images, and informatics of business-based managerial decisions and system/process analysis, among others. This research will put WVU at the forefront of the movement to integrate ML and AI into the fabric of data-driven research, allowing for timely and relevant scientific and societal issues to be addressed as well as providing training opportunities for the next generation of data scientists, led by 24 faculty in conjunction with 92 postdocs, graduate students, and undergraduate students. Dolly Sods will also serve as an integral teaching resource for a newly formed undergraduate degree in Data Science, which will incorporate ML and AI throughout the curriculum. Combined with outreach to statewide institutions of higher learning, Dolly Sods will drive continued efforts in training a diverse HPC workforce, drawing from communities historically underrepresented in STEM, including first generation college students, women, and other underrepresented groups. The project will strengthen partnerships with regional federal labs (DOE National Energy Technology Laboratory, NOAA Environmental Security Computing Center, NASA Independent Validation and Verification Facility, and the FBI Criminal Justice Services Division), industrial partners (Leidos and PPG), and the nation’s leading center for ML and AI (Pittsburgh Supercomputing Center (PSC)). It will further WVU’s long-term goal of transforming the economically disadvantaged region of Appalachia into a top-level destination for investment from the technology sector. 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.

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