The National Science Foundation (NSF) awarded a $622,431 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the Regents of the University of Minnesota. This award will fund interdisciplinary research to develop novel 3D vertical ferroelectric memcapacitor devices and in-memory computing circuits to dramatically improve the energy efficiency of artificial intelligence and machine learning computing systems. The research aims to tackle the growing energy demands of AI and data centers, which could increase by over 10x by 2026.
The project will involve co-designing materials, devices, circuits, and computing architectures to enable more efficient analog-based in-memory computing. A sub-award of $269,920 was made to The Trustees of Columbia University in the City of New York to support this effort. The overall goal is to create a deep neural network accelerator with a fully analog datapath and digital control, reducing the energy footprint of AI computing. This award reflects NSF's mission to advance scientific discovery and technological innovation to address critical national challenges.
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