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Energy-Efficient Memristive Analog and Digital Electronics

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Advances in Neuromorphic Memristor Science and Applications

Part of the book series: Springer Series in Cognitive and Neural Systems ((SSCNS,volume 4))

Abstract

This chapter reviews recent technology trends in memristive analog and digital electronics, with particular attention to programmable analog and digital circuits, ultra-dense nonvolatile resistive memory architectures, and zero leakage nonvolatile logic gates. A reconfigurable nonvolatile computing platform that harnesses memristor properties is used to deploy massive local nonvolatile memories and advance computing capabilities with much lowered energy consumption than the conventional charge-based VLSI systems. With application of memristive devices for nonvolatile memories, programmable interconnects, stateful logic gates, and nonvolatile latches with high integration density and CMOS compatibility, combining memristor technology with the prevailing CMOS technology poses to prolong the Moore’s Law beyond the hitherto observed technological limitations.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Jack Baskin School of Engineering, University of California, Santa Cruz, CA, USA

    Sung Mo Steve Kang & Sangho Shin

Authors
  1. Sung Mo Steve Kang
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  2. Sangho Shin
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Corresponding author

Correspondence to Sung Mo Steve Kang .

Editor information

Editors and Affiliations

  1. Dept. Mathematical Sciences, University of Memphis, Memphis, 38152, Tennessee, USA

    Robert Kozma

  2. , RITC, Information Directorate, Air Force Research Laboratory, Electronics Parkway 26, Rome, 13441-4514, New York, USA

    Robinson E. Pino

  3. , Mathematical Sciences, The University of Memphis, Dunn Hall 373, Memphis, 38152, Tennessee, USA

    Giovanni E. Pazienza

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© 2012 Springer Science+Business Media Dordrecht

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Kang, S., Shin, S. (2012). Energy-Efficient Memristive Analog and Digital Electronics. In: Kozma, R., Pino, R., Pazienza, G. (eds) Advances in Neuromorphic Memristor Science and Applications. Springer Series in Cognitive and Neural Systems, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4491-2_11

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