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A survey of in-spin transfer torque MRAM computing

  • Hao Cai
  • , Bo Liu
  • , Juntong Chen
  • , Lirida Naviner
  • , Yongliang Zhou
  • , Zhen Wang
  • , Jun Yang
  • Southeast University
  • Ltd.

Research output: Contribution to journalReview articlepeer-review

33 Citations (Scopus)

Abstract

In traditional von Neumann computing architectures, the essential transfer of data between the processor and memory hierarchies limits the computational efficiency of next-generation system-on-a-chip. The emerging in-memory computing (IMC) approach addresses this issue and facilitates the movement of significant data and rapid computations. Among the different memory types, intrinsic energy efficiency is demonstrated by in-magnetic random access memory (MRAM) computing with a low-power spintronic magnetic tunnel junction device and hybrid integration at an advanced complementary metal-oxide semiconductor node. This study reviews state-of-the-art techniques for managing IMC with an emphasis on spin-transfer torque-MRAM computing via design schemes at the bit-cell, circuit, and system levels. In addition, this study presents effective design techniques and potential challenges and demonstrates the existing limitations of in-MRAM computing and potential methods for overcoming these issues. This study also considers the design technology co-optimization from the IMC perspective.

Original languageEnglish
Article number160402
JournalScience China Information Sciences
Volume64
Issue number6
DOIs
Publication statusPublished - 1 Jun 2021

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

  • Boolean logic
  • analog computing
  • in-memory computing
  • magnetic tunnel junction
  • neural network
  • nonvolatile memory
  • spin-transfer torque-magnetoresistive random access memory

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