Web: http://arxiv.org/abs/2205.05664

June 17, 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 compared to digital computing due to its
potential for achieving higher computational density and higher energy
efficiency. However, unlike digital circuits, conventional analog computing
circuits cannot be easily mapped across different process nodes due to
differences in transistor biasing regimes, temperature variations and limited
dynamic range. In this work, we generalize the previously reported
margin-propagation-based analog computing framework for designing novel
\textit{shape-based analog computing} (S-AC) circuits that can be easily
cross-mapped across different process nodes. Similar …

ar arxiv bias cmos computing learning machine machine learning process scalable

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