Memristor-based in-memory logic and its application in image processing

Ameer Haj-Ali, Ronny Ronen, Rotem Ben-Hur, Nimrod Wald, Shahar Kvatinsky

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


In modern von Neumann systems, the data are stored in the memory but are processed in a separate unit. Data transfer between these units incurs energy and delay, which are several orders of magnitude greater than the energy and delay incurred by the computation itself. Recent works on in-memory computing (IMC) have been proposed to reduce the overhead of data transfer. Further reduction became possible with the emergence of memristive memory technologies. Numerous logic-in-memory techniques with memristors have been proposed where the computation is performed using the memory arrays. In this chapter, we overview different memristor-based logic techniques. As a case study of memristor-based logic in an IMC system, we demonstrate how Memristor Aided loGIC (MAGIC) allows NOR gates to be performed within a memristive crossbar array structure. We describe a potential memristive Memory Processing Unit (mMPU) where MAGIC NOR is employed as the basis for all data processings. We then show how to perform different image processing tasks within the mMPU to obtain superior performance and energy efficiency for these tasks over other state-of-the-art memristive logic systems.

Original languageEnglish
Title of host publicationMemristive Devices for Brain-Inspired Computing
Subtitle of host publicationFrom Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and Spiking Neural Networks
Number of pages20
ISBN (Electronic)9780081027820
StatePublished - 1 Jan 2020
Externally publishedYes


  • Algorithms
  • In-memory computing
  • Memristors
  • Von Neumann bottleneck

ASJC Scopus subject areas

  • Engineering (all)


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