Project Grant 2416361
Award Date
7/1/24
Completion Date
6/30/27
Dollars Obligated
$300K
Federal Agency
Division of Computing and Communication Foundations
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
College Station, TX 77843, USA
Similar Awards
This $300,000 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program will support research to develop new error-correcting codes for reliable in-memory computing in next-generation artificial intelligence (AI) systems. The project, titled "COLLABORATIVE RESEARCH: NSF-BSF: CIF: SMALL: ERROR-CORRECTING CODES FOR NEXT-GENERATION ARTIFICIAL INTELLIGENCE," will explore a new approach called...
This National Science Foundation (NSF) Project Grant award under the STEM Education (CFDA 47.076) program provides $450,000 to Georgia TECH Research Corporation to develop fundamental algorithms and infrastructure that enable error-resilient operation of artificial intelligence (AI) systems. The key objectives are to: 1) Implement efficient post-manufacturing testing and tuning methods for deep neural networks implemented on energy-efficient analog crossbar arrays, to address vulnerability to...
This $500,000 federal Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program is aimed at accelerating the development of fault-tolerant quantum computing. The award to the University of California, Los Angeles (UCLA) will fund an interdisciplinary research effort to co-design error-correcting codes and quantum computing hardware to achieve useful quantum advantage sooner. The project will focus on optimizing the...
The National Science Foundation awarded a $1,247,506 Project Grant to the University of Texas at Dallas under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the period of October 1, 2022 through September 30, 2025. The grant funds research to comprehend and mitigate errors in analog implementations of on-die neural networks. Specifically, the university will investigate and develop methods to address the impact of manufacturing and operational...
This National Science Foundation Project Grant award of $599,970 provides funding from May 2023 through April 2026 to support research activities at the University of Illinois under the Computer and Information Science and Engineering program (CFDA 47.070). The award will fund research to develop new algorithmic tools and techniques for interpreting error-correcting codes that have been designed using deep learning methods. The research goals include gaining a better understanding of how and why...
The National Science Foundation (NSF) awarded a $266,000 Project Grant to the Georgia Tech Research Corporation, doing business as the Office of Sponsored Programs, under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of a compact and energy-efficient "compute-in-memory" accelerator for deep learning applications leveraging ferroelectric vertical NAND memory technology. Key objectives include designing and evaluating...
This $392,619 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant award (CFDA 47.070) will support Arizona State University's (ASU) research on developing an energy-efficient, dynamic, and robust in-memory computing system for artificial intelligence (AI) applications. The key objectives are to: Design and fabricate a hybrid resistive random-access memory (RRAM) and static random-access memory (SRAM) based in-memory computing chip. Develop...
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...
This federal Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to support the development of a verifiable quantum compiler that integrates formal methods to enable fault-tolerant quantum computing. The $500,000 award, with a period of performance from September 1, 2024 to August 31, 2028, will fund research to optimize the translation of quantum algorithms into fault-tolerant...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $600,000 to the University of Arizona to develop practical quantum low-density parity-check (QLDPC) codes and novel anisotropic iterative decoders to advance fault-tolerant quantum computing. The research aims to create QLDPC codes that minimize trapping sets and design decoders capable of near-optimal error correction without high...