Project Grant 2441694
Award Date
5/1/25
Completion Date
4/30/30
Dollars Obligated
$207K
Federal Agency
Division of Computer and Network Systems
Awardee
Auburn University (DMQNDJDHTDG4)
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Auburn University, AL 36849, USA
Similar Awards
The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University, Division (doing business as Orspa), for the project "COLLABORATIVE RESEARCH: SHF: MEDIUM: TINY CHIPLETS FOR BIG AI: A RECONFIGURABLE-ON-PACKAGE SYSTEM". This 4-year project (7/1/2024 - 6/30/2028) aims to pioneer a computing system for massive AI workloads, including new architectural and design automation...
This $800,000 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to pioneer a computing system for massive AI workloads. The project will develop new architectural and design automation tools for a reconfigurable-on-package system using "tiny chiplets" - miniaturized composable computing components. This innovative approach seeks to address the challenges related to chiplet definition,...
Auburn University was awarded a $349,846 Project Grant from the National Science Foundation under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research efforts to address the memory bottleneck problem impacting deep learning hardware through co-optimization of on-chip and off-chip memory system design with AI/DL hardware architecture. Key activities include utilizing emerging magnetic random access memory, chiplet, and packaging...
This $200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) seeks to revolutionize artificial intelligence (AI) training through the development of a novel chip architecture. The project, titled "CO-FABPRO, A DISRUPTIVE APPROACH FOR EFFICIENT TRAINING OF LONG-SEQUENCE MACHINE LEARNING MODELS", aims to make AI training dramatically faster and more energy-efficient than current methods....
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $134,992 to Rensselaer Polytechnic Institute (RPI) from January 1, 2025 to December 31, 2029. The project aims to develop methods to leverage dynamic connectivity in AI models to reduce redundancy and adapt models to specific tasks and data. It also involves exploring heterogeneous architectures that integrate approximate, analog, and...
The National Science Foundation awarded a $157,203 Project Grant to the University of Arizona under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to conduct research related to scaling general-purpose processors into the exascale era. Specifically, the award will fund research to design reconfigurable aggregated virtual chips utilizing heterogeneous aggregated chiplets and a hybrid wireless interconnection network. This is intended to enable systems...
This $127,484 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of an efficient compilation and synthesis flow to create domain-specific reconfigurable heterogeneous acceleration systems. The key innovations include:
A heterogeneous acceleration system template combining hardened digital accelerators, reconfigurable digital logic, and general-purpose processors.
An...
This $557,158 Project Grant award was made by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant supports research to devise novel mathematical operators that address performance bottlenecks in graph-based artificial intelligence (AI) applications. The project aims to unlock scalable and sustainable processing of sparsified graph neural network models, which are critical for emerging AI-powered...
This $638,022 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of an indium-oxide-based neural computing platform. The goal is to create a more reliable, energy-efficient, and scalable platform for running large language models and other AI workloads at the edge. Key objectives include:
Advancing the scientific understanding of oxide semiconductors through...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,200,000 to Purdue University to develop scalable and ultra-low-power neural accelerators based on 2D ferroelectric semiconductors. The research aims to address hardware needs for future artificial intelligence (AI) platforms by utilizing the unique properties of ferroelectric semiconductors to design energy-efficient circuits and...