May 12, 2022, 1:11 a.m. | Pratik Kumar, Ankita Nandi, Shantanu Chakrabartty, Chetan Singh Thakur

cs.LG updates on arXiv.org arxiv.org

Analog computing is attractive to its digital counterparts due to its
potential for achieving high compute density and energy efficiency. However,
the device-to-device variability and challenges in porting existing designs to
advance process nodes have posed a major hindrance in harnessing the full
potential of analog computations for Machine Learning (ML) applications. This
work proposes a novel analog computing framework for designing an analog ML
processor similar to that of a digital design - where the designs can be scaled …

analog ar arxiv cmos implementation process scalable theory

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