Please use this identifier to cite or link to this item: https://doi.org/10.1145/2463585.2463590
Title: Dual Pillar Spin-Transfer Torque MRAMs for Low Power Applications
Authors: Mojumder, Niladri N
Fong, Xuanyao 
Augustine, Charles
Gupta, Sumeet K
Choday, Harsha
Roy, Kaushik 
Keywords: Science & Technology
Technology
Computer Science, Hardware & Architecture
Engineering, Electrical & Electronic
Nanoscience & Nanotechnology
Computer Science
Engineering
Science & Technology - Other Topics
RANDOM-ACCESS MEMORY
MAGNETIC TUNNEL-JUNCTIONS
STT-MRAM
Issue Date: 1-May-2013
Publisher: ASSOC COMPUTING MACHINERY
Citation: Mojumder, Niladri N, Fong, Xuanyao, Augustine, Charles, Gupta, Sumeet K, Choday, Harsha, Roy, Kaushik (2013-05-01). Dual Pillar Spin-Transfer Torque MRAMs for Low Power Applications. ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS 9 (2). ScholarBank@NUS Repository. https://doi.org/10.1145/2463585.2463590
Abstract: Electron-spin based data storage for on-chip memories has the potential for ultra-high density, low power consumption, very high endurance, and reasonably low read/write latency. In this article, we discuss the design challenges associated with spin-transfer torque (STT) MRAM in its state-of-the-art configuration. We propose an alternative bit cell configuration and three new genres of magnetic tunnel junction (MTJ) structures to improve STT-MRAM bit cell stabilities, write endurance, and reduce write energy consumption. The proposed multi-port, multi-pillar MTJ structures offer the unique possibility of electrical and spatial isolation of memory read and write. In order to realize ultralow power under process variations, we propose device, bit-cell and architecture level design techniques. Such design alternatives at multiple levels of design abstraction has been found to achieve substantially enhanced robustness, density, reliability and low power as compared to their charge-based counterparts for future embedded applications. © 2013 ACM.
Source Title: ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS
URI: https://scholarbank.nus.edu.sg/handle/10635/156171
ISSN: 15504832
15504840
DOI: 10.1145/2463585.2463590
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