Magnetoresistive Circuits and Systems: Embedded Non-Volatile Memory to Crossbar Arrays

被引:14
作者
Agrawal, Amogh [1 ]
Wang, Cheng [1 ]
Sharma, Tanvi [1 ]
Roy, Kaushik [1 ]
机构
[1] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
基金
美国国家科学基金会;
关键词
Magnetic tunneling; Transistors; Switches; Stochastic processes; Standards; Resistance; Magnetization; Non-volatile memory; MRAM; spintronics; in-memory computing; crossbar arrays; stochastic computing; MAGNETIC TUNNEL-JUNCTION; REFERENCE SENSING SCHEME; SPIN-ORBIT; FLIP-FLOP; STT-MRAM; HIGH-SPEED; TORQUE; DESIGN; SRAM; ARCHITECTURE;
D O I
10.1109/TCSI.2021.3069682
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This overview article describes Magnetoresistive Random Access Memory (MRAM) from a circuits and systems perspective. We discuss various tradeoffs and design challenges of MRAM in three broad application areas: 1) embedded non-volatile memory (eNVMs), 2) crossbar-based analog in-memory computing, and 3) stochastic computing. Certain MRAM characteristics, such as high retention, high endurance and fast read and write operations, make them ideal for replacing the standard CMOS memories for last-level cache applications with future scaling. However, various tradeoffs in power, performance and area pose conflicting requirements on MRAM design. We explore these challenges and various circuit techniques that have been developed to mitigate them. Further, we present various requirements of memristive crossbar arrays for accelerating matrix-vector-multiplication (MVM) operations in light of MRAM devices, and highlight various challenges, design considerations, and applicability of MRAM as crossbar arrays. Finally, we will elaborate on how inherent stochasticity of MRAM devices can be leveraged for implementing energy-efficient true random number generators (TRNGs) and stochastic units for performing certain tasks, such as developing fast solvers for combinatorial optimization, and stochastic neural networks.
引用
收藏
页码:2281 / 2294
页数:14
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