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 Project Grant award for $731,058 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) aims to design and evaluate an energy-efficient hardware/software framework for on-chip implementation of deep neural networks (DNNs). The primary objectives are to: Develop a radically innovative energy-efficient framework for DNN implementation, and Customize this framework for real-time signal classification in next-generation...
This five-year, $199,995 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop a co-designed framework of hardware, software, and algorithms enabling extreme-scale machine learning systems for emerging artificial intelligence of things and internet of senses technologies. Specifically, the Saint Louis University team will pursue five research thrusts: developing hardware and compiler approaches for large-scale split learning...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program grant, awarded to Rensselaer Polytechnic Institute (RPI), aims to develop energy-efficient and scalable artificial intelligence (AI) systems through a co-design approach that integrates dynamic model connectivity, heterogeneous architectures, and hardware-aware model adaptation. The $134,992 grant, with a period of performance from January 1, 2025 to December 31, 2029, focuses on three key...
This $200,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enhance the energy efficiency of large language models (LLMs) used in advanced artificial intelligence applications. The key research goals are to: Identify and characterize idleness in LLM workloads to enable lower-power dynamic voltage and frequency scaling (DVFS) control and undervolting to reduce static energy...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $305,999 to the University of Oklahoma to develop a novel hybrid CMOS+X-based in-memory analog computing framework. The framework will utilize industry-scale 3D NAND flash memory chips and academic laboratory-scale molecular memristors to create a highly energy-efficient neuromorphic computing system, with the goal of significantly improving the biological plausibility of artificial...
The National Science Foundation (NSF) awarded a $599,995 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) federal grant program to Carnegie Mellon University (CMU). The grant supports a 3-year research project focused on developing sustainable and energy-efficient approaches to large-scale machine learning across domains such as natural language processing, computer vision, and scientific AI applications. The project aims to enhance training efficiency,...
This Project Grant award for $211,129 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award was granted to Northeastern University on January 1, 2025, with a target completion date of May 31, 2025. The project aims to develop a design framework for efficient information processing that leverages non-binary representations and in-memory computing, inspired by neural networks and...
This $269,579 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at Arizona State University (ASU) to develop an innovative hybrid in-memory computing system. The overarching goal is to design and validate a new hardware platform that integrates emerging non-volatile memory and static RAM technologies, along with specialized deep learning algorithms, to achieve significant...
The National Science Foundation (NSF) awarded a $340,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Missouri System to develop sustainability-aware design methods for approximate deep neural network (DNN) accelerators. The key objectives of this 3-year project are: Investigating efficient neural architecture search techniques for reliable and sustainable approximate DNN accelerator designs. Developing fault mitigation and...