Project Grant W911NF261A006

This three-year, $290,739 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will support the development of a novel non-volatile nano-second right-grained reconfigurable architecture for data-intensive machine learning and graph computing applications. The proposed computing architecture, called Right-Grained Reconfigurable Architecture (RGRA), combines aspects of coarse-grained reconfigurable arrays and field-programmable gate arrays...

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...

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 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...

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...

The National Science Foundation (NSF) has awarded Ohio University a $120,000 Project Grant under the Engineering program (CFDA 47.041) to develop reconfigurable threshold logic gates (TLGs) for flexible and wearable electronics. The objective is to create novel TLG circuit topologies and thin-film transistor (TFT) device designs to enable efficient neuromorphic computing on resource-constrained flexible systems. This work will also be leveraged to introduce students, including those at a local...

This $2 million Project Grant from the National Science Foundation's Office of Emerging Frontiers and Multidisciplinary Activities will fund research at Cornell University from October 2022 through September 2026 under the federal Engineering program (CFDA 47.041). The grant aims to advance neuromorphic computing by developing algorithms and computational models inspired by biological neural circuits. Researchers will extract principles from neuroscience to design a neural network architecture...

This $340,000 National Science Foundation project grant supports research at the University of Texas at Austin to develop two-dimensional ambipolar materials and device structures for logical and machine learning circuits. The grant is part of NSF's $47 million Engineering program, which funds research and education activities to advance engineering innovations. Specifically, the researchers will study dual-gate ambipolar field-effect transistors made from two-dimensional materials to design new...

This $250,000 Project Grant award from the National Science Foundation's Engineering (CFDA 47.041) program to The Pennsylvania State University (Penn State) supports a collaborative research project on "Spintronics Enabled Stochastic Spiking Neural Networks with Temporal Information Encoding". The goal is to advance neuromorphic computing architectures that can achieve brain-scale efficiency for complex machine learning through a multi-disciplinary approach spanning device physics,...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant, award ID 2403723, provides $500,000.00 to Cornell University to develop novel algorithms and hardware designs for energy-efficient, memory-optimized spiking neural network (SNN) systems on edge computing devices. The project aims to advance the practical deployment of neuromorphic computing for applications like drones, autonomous robots, portable medical devices, and wearable...