Project Grant 2136676

Award Date 8/15/22
Completion Date 7/31/23
Dollars Obligated $256K
Federal Grant Program
47.084
Assistance Type
Project Grant
Place of Performance
Lawrence, KS 66049, USA
Similar Awards
Wolfzyc LLC was awarded a $255,646 Project Grant from the National Science Foundation under the NSF Technology, Innovation, and Partnerships program to develop a neuromorphic computing platform using superconducting neural units with adjustable weights. This Small Business Innovation Research Phase I award will support the company's efforts over 11 months to advance the technological frontier with a high-speed superconductor electronics-based neuromorphic computer centered around a disordered...
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...
This $305,999 federal Project Grant award from the National Science Foundation's Engineering (CFDA 47.041) program supports the development of a novel hybrid CMOS+X-based in-memory analog computing framework. The project aims to create an energy-efficient neuromorphic computing system by leveraging industry-scale 3D NAND flash memory chips and academic laboratory-scale molecular memristors to emulate the human brain's remarkable efficiency. The framework will utilize 3D NAND flash memory to...
This Project Grant award for $200,000 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research by Southern Illinois University Carbondale (SIU) to develop hardware-constraint-aware design and optimization techniques for memristor-crossbar-array (MCA) based neural network accelerators. The research aims to bridge the gap between software design tools and the physical limitations of MCA hardware, enabling more efficient and cost-effective development of...
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 $300,000 Project Grant award from the National Science Foundation (NSF) Integrative Activities program (CFDA 47.083) supports research led by the University of South Alabama (USA) to investigate memristor-based computing-in-memory (CIM) for neuromorphic systems. The primary goals are to advance the design, optimization, and fabrication of these energy-efficient AI computing architectures. The two-year project will establish a long-term collaboration between USA and the Georgia Institute...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) project grant award provides $650,000 to The Trustees of Columbia University in the City of New York to develop energy-efficient optical brain-inspired (neuromorphic) computing devices. The project aims to establish a 3D nanofabrication platform that combines DNA-programmable assembly and conventional lithographic methods to create novel optical metamaterials and integrate them into neuromorphic...
This $959,229 Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The grant supports research to develop atomically tunable memristor devices based on ultra-thin (sub-2 nm) wide-bandgap semiconductors like Ga2O3. The research aims to enable new energy-efficient neuromorphic computing paradigms by precisely controlling the physical and chemical properties of these memristor materials at the atomic scale. Key...
This $500,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports a collaborative research effort between Yale University and its partners to develop energy-efficient algorithms and hardware for spike-based edge computing. The project aims to integrate spiking neural networks (SNNs), a brain-inspired computing paradigm, with modern integrated circuits to enable practical deployment of neuromorphic...
The National Science Foundation awarded a $525,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) to support research investigating energy-efficient persistent learning-in-memory with quantum tunneling dynamic synapses from October 1, 2022 to September 30, 2025. The award will fund the development of novel learning hardware and software tools to significantly improve the energy efficiency of artificial...

This $255,999 National Science Foundation award under the Technology, Innovation, and Partnerships program will support Zenoleap LLC's development of novel superconducting neuromorphic computing circuits. The awardee will design, fabricate, and characterize atomic-tunable memristors and superconducting quantum interference device neurons to enable true biological brain-inspired deep learning network algorithms. This superconducting neuromorphic circuit aims to significantly improve energy efficiency, switching speed, and scalability compared to current neuromorphic computing approaches. The award period runs from August 15, 2022 to July 31, 2023. If successful, this research could advance the foundation of next-generation computing hardware and help maintain U.S. leadership in processor development and manufacturing.

Generated 1/7/24, 3:41 AM