Project Grant 2208771
Award Date
10/1/22
Completion Date
9/30/25
Dollars Obligated
$525K
Federal Agency
Division of Computing and Communication Foundations
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
La Jolla, CA 92093, USA
Similar Awards
This $618,159 National Science Foundation project grant supports research into developing energy-efficient hardware and software for machine learning and artificial intelligence systems. Funded under the Computer and Information Science and Engineering program, the award supports The Washington University in investigating frameworks using quantum-tunneling dynamic-analog memory devices and novel online learning algorithms. Specific objectives include exploring Fowler-Nordheim dynamic analog...
The National Science Foundation awarded $800,000 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the University of California, San Diego from September 1, 2022 to August 31, 2025. The project grant funding will support the development of lifelong learning algorithms using hyperdimensional computing, a brain-inspired framework for distributed computing. Specifically, the awardee will advance algorithms for similarity search, density estimation,...
This $622,431 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop energy-efficient computing systems for artificial intelligence (AI) and machine learning applications. The key technical aims include: Creating a vertical memcapacitor device that can be integrated into the backend of CMOS chip manufacturing for 3D integration; Developing memcapacitor-based in-memory computing...
The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the University of California, San Diego (UCSD) under the Computer and Information Science and Engineering (CFDA 47.070) program. The 3-year grant, effective July 1, 2023, supports research to develop dynamic neural network architectures that can efficiently enable multimodal perception, including vision, audio, and language processing. The research aims to address...
This $299,889 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research at the University of California, San Diego (UCSD) to develop algorithms for compressing and improving the efficiency of large neural networks used in modern artificial intelligence applications. The key products and services to be delivered include: The research project focuses on developing quantization, pruning, and low-rank...
This $189,000 Project Grant award, provided by the National Science Foundation (NSF) Integrative Activities (CFDA 47.083) program, supports the development of a novel hybrid CMOS+X-based in-memory analog computing framework. The project aims to emulate the efficiency of the human brain through neuromorphic in-memory computing fueled by artificial synapses and neurons. Key components include industry-scale 3D NAND flash memory chips and academic laboratory-scale molecular memristors, which will...
This $416,516 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) project grant award to Arizona State University (ASU) is focused on developing an energy-efficient artificial intelligence (AI) processing-in-memory (PIM) system that leverages emerging spin-orbit torque magnetic random access memory (SOT-MRAM) technology. The project aims to advance the materials, devices, circuits, architectures, and AI algorithms for this SOT-MRAM-based AI-PIM...
The National Science Foundation (NSF) Office of Emerging Frontiers and Multidisciplinary Activities awarded a $1,999,968 Project Grant to the University of California, Santa Barbara (UCSB) under the NSF Engineering (CFDA 47.041) program. This grant aims to develop scalable algorithms and hardware for human-brain-scale neuromorphic systems with practical learning capabilities. The key objectives are to create hardware-friendly local learning algorithms, a framework for continual online...
This $731,058 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop an energy-efficient hardware/software framework for on-chip implementation of deep neural networks (DNNs). The primary objectives are to: 1) Design and evaluate a radically innovative energy-efficient architecture that integrates processing elements within memory chips to significantly reduce DNN energy...
The National Science Foundation awarded University of California Irvine a $499,793 Project Grant under the federal Computer and Information Science and Engineering grant program (CFDA 47.070). The grant will support the development of brain-inspired machine learning algorithms to provide real-time feedback to sensors and intelligently control data generation rates. This is expected to reduce sensor data outputs by up to four orders of magnitude for applications in infrastructure, mobile devices,...