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High-Speed and Energy-Efficient Non-Binary Computing with Polymorphic Electro-Optic Circuits and Architectures

  • Ishan Thakkar
  • , Sairam Sri Vatsavai
  • , Venkata Sai Praneeth Karempudi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we present microring resonator (MRR) based polymorphic E-O circuits and architectures that can be employed for high-speed and energy-efficient non-binary reconfigurable computing. Our polymorphic E-O circuits can be dynamically programmed to implement different logic and arithmetic functions at different times. They can provide compactness and polymorphism to consequently improve operand handling, reduce idle time, and increase amortization of area and static power overheads. When combined with flexible photodetectors with the innate ability to accumulate a high number of optical pulses in situ, our circuits can support energy-efficient processing of data in non-binary formats such as stochastic/unary and high-dimensional reservoir formats. Furthermore, our polymorphic E-O circuits enable configurable E-O computing accelerator architectures for processing binarized and integer quantized convolutional neural networks (CNNs). We compare our designed polymorphic E-O circuits and architectures to several circuits and architectures from prior works in terms of area, latency, and energy consumption.

Original languageEnglish
Title of host publicationGLSVLSI 2023 - Proceedings of the Great Lakes Symposium on VLSI 2023
Pages545-550
Number of pages6
ISBN (Electronic)9798400701252
DOIs
StatePublished - Jun 5 2023
Event33rd Great Lakes Symposium on VLSI, GLSVLSI 2023 - Knoxville, United States
Duration: Jun 5 2023Jun 7 2023

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Conference

Conference33rd Great Lakes Symposium on VLSI, GLSVLSI 2023
Country/TerritoryUnited States
CityKnoxville
Period6/5/236/7/23

Bibliographical note

Publisher Copyright:
© 2023 ACM.

Funding

This research is supported by a grant from NSF (CNS-2139167).

FundersFunder number
National Science Foundation Arctic Social Science Program2139167, CNS-2139167

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Keywords

    • electro-optic polymorphic circuits
    • microring resonators (mrrs)
    • non-binary computing

    ASJC Scopus subject areas

    • General Engineering

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