University of Notre Dame Du Lac

Indranil Palit

Behnam Sedighi

Xiaobo Sharon Hu

Michael Niemier

Various processor architectures for mixed signal computation exploit the unique characteristics of advanced CMOS technologies, such as fin-based, multi-gate field effect transistors, and/or emerging technologies such as tunnel field effect transistors (TFETs). The example processors disclosed herein are cellular neural network (CNN)-inspired and eliminate the need for voltage controlled current sources (VCCSs), which have previously been utilized to realize feedback and feed-forward templates in CNNs and are the dominant source of power consumption in a CNN array. The example processors replace VCCSs with comparators, which can be efficiently realized with TFETs given their high intrinsic gain. Power efficiencies are in the order of 10,000 giga-operations per second per Watt (GOPS/W), which represents an improvement of more than ten times over state-of-the-art architectures seeking to accomplish similar information processing tasks.

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South Bend, IN, United States of America

Indranil Palit