Award Abstract # 2120019
Division Of Computer and Network Systems
|Initial Amendment Date:||July 25, 2021|
|Latest Amendment Date:||November 9, 2021|
|Award Instrument:||Standard Grant|
|Program Manager:||Deepankar Medhi
CNS Division Of Computer and Network Systems
CSE Direct For Computer & Info Scie & Enginr
|Start Date:||October 1, 2021|
|End Date:||September 30, 2024 (Estimated)|
|Total Intended Award Amount:||$1,800,000.00|
|Total Awarded Amount to Date:||$1,816,000.00|
|Funds Obligated to Date:||
FY 2022 = $16,000.00
|History of Investigator:||
|Awardee Sponsored Research Office:||
Office of Contract & Grant Admin
CA US 92093-0934
|Sponsor Congressional District:|
|Primary Place of Performance:||
9500 Gilman Drive #0934
CA US 92093-0934
|Primary Place of Performance
|Parent DUNS ID:|
|NSF Program(s):||Special Projects – CNS,
CCRI-CISE Cmnty Rsrch Infrstrc
|Primary Program Source:|
|Program Reference Code(s):|
|Program Element Code(s):|
|Award Agency Code:||4900|
|Fund Agency Code:||4900|
Machine learning (ML) is a rapidly expanding field. Computationally intensive workflows train neural nets and then use the results in smartphones, robots, drones, self-driving vehicles, and to run the Internet of Things. Access to graphics processing units (GPUs) is provided through CHASE-CI’s Nautilus, a highly distributed but centrally managed on-demand computer cluster designed for ML and Computational Media (CM). CHASE-CI provides over 20 campuses the scaffold for adding on-premises compute cycles and fast data handling and it offers researcher-focused support and training. Using CHASE-CI’s detailed measurements of performance, researchers learn to become experts in optimization of their computational resources.
CHASE-CI is a community-building effort that sustains a growing community of ML/CM researchers using a purpose-built continuously enhanced nationally distributed computing and data storage infrastructure. Researchers explore combinations of algorithms and architectures optimized with the help of graphed performance metrics. Researchers benefit from extensive shared workflows and open-source software. They use CHASE-CI’s on-line social media platform to receive and give support and share techniques. Community use of CHASE-CI informs computer architecture discussions about future national cyberinfrastructure research and instructional lab needs. CHASE-CI forms a national on-line community that is easy to join, designed for sharing code, data, and results.
The hardware, software, and socio-technical approaches developed by CHASE-CI have provided a roadmap for broader research uses and student training in ML/CM technologies. Researchers get expanded access to hundreds of GPUs for developing algorithms and software to train sensing devices and visualize results thus engaging the students who will soon join the essential workforce for the ongoing massive expansion of mobile platforms such as robots, drones, and self-driving cars. CHASE-CI impacts social diversity in computer science, broadening participation among Minority-Serving Institutions and underserved states. CHASE-CI thoroughly measures and monitors data access by applications over the regional and national R&E networks.
The repository for the project may be found at prp.ucsd.edu, to be maintained for the length of the project at a minimum. It is the anchor website containing pointers to all the research efforts that build upon the Pacific Research Platform. It contains code repositories, presentations, references like publications, presentations, and recorded lectures, and it maintains and archives an active social media channel. CHASE-CI is led by UC San Diego, partnering with investigators at UC Santa Cruz, The University of Nebraska-Lincoln, Florida Agricultural and Mechanical University, New York University, The University of Illinois at Chicago, and San Diego State University.
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.