Mixed signal processors

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.