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Cited by 304

The DOI matches its Crossref record; 114 of the 114 references it cites were found in a registry or an index.

Spintronics for Energy- Efficient Computing: An Overview and Outlook

Guo, Zongxia, Yin, Jialiang, Bai, Yue, Zhu, Daoqian, Shi, Kewen, Wang, Gefei, Cao, Kaihua, Zhao, Weisheng·2021·Proceedings of the IEEE

Abstract

From the discovery of giant magnetoresistance (GMR) to tunnel magnetoresistance (TMR), their subsequent application in large capacity hard disk drives (HDDs) greatly speeded up the information era over the past decades. However, the growing demand for big-data storage and processing is limited by the von-Neumann architecture due to the memory bottleneck and power dissipation. Taking advantage of nonvolatility, high speed, and low power, magnetic random access memory (MRAM) becomes a promising candidate to overcome this limitation through processing-in-memory (PIM) architectures. In this article, we provide an overview of existing technology and give a roadmap of spintronic devices for future energy-efficient computing and its relevant integration architectures. We begin with the fundamentals of Toggle-MRAM and spin-transfer torque (STT)-MRAM, which already have commercial applications. We then introduce spin-orbit torque (SOT), a critical mechanism to realize low-power data manipulation in the next generation of MRAM and summarize the recent experimental breakthroughs of field-free SOT switching schemes. Finally, we present MRAM-based PIM architectures and novel spintronic devices, provide an application outlook, and deliver the future development potential of energy-efficient computing systems.

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Metadata

Authors
Guo, Z., Yin, J., Bai, Y., Zhu, D., Shi, K., Wang, G., Cao, K., & Zhao, W.
Venue
Proceedings of the IEEE
Published
2021-08
Volume
109
Issue
8
Pages
1398-1417
ISSN
  • 0018-9219 (ISSN-L)
  • 1558-2256
OpenAlex
W3172819050
Cited by
304
References
114
FWCI
18.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Spintronics for Energy- Efficient Computing: An Overview and Outlook. https://app.cochat.ai/papers/10.1109/jproc.2021.3084997
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Guo, Z., Yin, J., Bai, Y., Zhu, D., Shi, K., Wang, G., Cao, K., & Zhao, W. (2021). Spintronics for Energy- Efficient Computing: An Overview and Outlook. Proceedings of the IEEE. https://doi.org/10.1109/jproc.2021.3084997

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