Project Grant 2526432

Award Date 1/1/25
Completion Date 5/31/25
Dollars Obligated $211K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Boston, MA 02115, USA
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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 biological systems. Key research thrusts include: (1) advancing analog/mixed-signal (AMS) design automation and neural network-inspired model abstractions, (2) supporting flexible and efficient in-memory computing architectures, and (3) exploring energy-efficient, context-aware analog-to-information frontend designs for sensor systems. The project seeks to enable joint optimization of circuits, architectures, and algorithms across a range of applications, including in-memory computing and near-sensor processing, to address challenges in performance, efficiency, safety, and security in heterogeneous systems.

Generated 4/29/25, 4:38 AM