Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction

Hao Cai; Honglan Jiang; Menglin Han; Zhaohao Wang; You Wang; Jun Yang; Jie Han; Leibo Liu; Weisheng Zhao

doi:10.1109/ISVLSI.2019.00029

Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction

Hao Cai
, Honglan Jiang
, Menglin Han
, Zhaohao Wang
, You Wang
, Jun Yang
, Jie Han
, Leibo Liu
, Weisheng Zhao

School of Integrated Circuit Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

In order to realize high efficient magnetization switching in magnetic tunnel junction (MTJ), several potential alternative mechanisms have been realized to replace spin transfer torque (STT) method, such as the STT-assisted precessional voltage controlled magnetic anisotropy (VCMA), and the spin orbit torque (SOT) erasing plus STT programing. In this paper, we propose a method denoted as the Process-in-memory with Joint magnetization switching for Approximate computing in Magnetic Tunnel Junction (Pj-AxMTJ), by using the 1T-1M and 3T-1M bit-cell structures. The proposed method aims to implement a low-precision computational memory with dynamic approximate computing. Specifically, four nonvolatile approximate full adders (AxFAs) are proposed based on the writing operations of different types of magnetic random access memory. As no peripheral circuits but the memory bit-cells are used in the proposed design, the resultant area is significantly small. Moreover, the AxFAs can be easily reconfigured into memory units with simple wire connections. The simulation results for the proposed designs are then presented to show the precision-power-area-speed tradeoffs for addition operation. Finally, the accuracy of the AxFAs are further evaluated in an image processing application.

Original language	English
Title of host publication	Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019
Publisher	IEEE Computer Society
Pages	111-115
Number of pages	5
ISBN (Electronic)	9781538670996
DOIs	https://doi.org/10.1109/ISVLSI.2019.00029
State	Published - Jul 2019
Event	18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019 - Miami, United States Duration: 15 Jul 2019 → 17 Jul 2019

Publication series

Name	Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI
Volume	2019-July
ISSN (Print)	2159-3469
ISSN (Electronic)	2159-3477

Conference

Conference	18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019
Country/Territory	United States
City	Miami
Period	15/07/19 → 17/07/19

Keywords

Approximate computing
SOT erasing
STT programming
STT-assisted VCMA
magnetic tunnel junction with joint switching
process-in-memory

Access to Document

10.1109/ISVLSI.2019.00029

Cite this

Cai, H., Jiang, H., Han, M., Wang, Z., Wang, Y., Yang, J., Han, J., Liu, L., & Zhao, W. (2019). Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction. In Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019 (pp. 111-115). Article 8839314 (Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI; Vol. 2019-July). IEEE Computer Society. https://doi.org/10.1109/ISVLSI.2019.00029

@inproceedings{f37a4908b7154ea7b1baca03a0e232d8,

title = "Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction",

abstract = "In order to realize high efficient magnetization switching in magnetic tunnel junction (MTJ), several potential alternative mechanisms have been realized to replace spin transfer torque (STT) method, such as the STT-assisted precessional voltage controlled magnetic anisotropy (VCMA), and the spin orbit torque (SOT) erasing plus STT programing. In this paper, we propose a method denoted as the Process-in-memory with Joint magnetization switching for Approximate computing in Magnetic Tunnel Junction (Pj-AxMTJ), by using the 1T-1M and 3T-1M bit-cell structures. The proposed method aims to implement a low-precision computational memory with dynamic approximate computing. Specifically, four nonvolatile approximate full adders (AxFAs) are proposed based on the writing operations of different types of magnetic random access memory. As no peripheral circuits but the memory bit-cells are used in the proposed design, the resultant area is significantly small. Moreover, the AxFAs can be easily reconfigured into memory units with simple wire connections. The simulation results for the proposed designs are then presented to show the precision-power-area-speed tradeoffs for addition operation. Finally, the accuracy of the AxFAs are further evaluated in an image processing application.",

keywords = "Approximate computing, SOT erasing, STT programming, STT-assisted VCMA, magnetic tunnel junction with joint switching, process-in-memory",

author = "Hao Cai and Honglan Jiang and Menglin Han and Zhaohao Wang and You Wang and Jun Yang and Jie Han and Leibo Liu and Weisheng Zhao",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019 ; Conference date: 15-07-2019 Through 17-07-2019",

year = "2019",

month = jul,

doi = "10.1109/ISVLSI.2019.00029",

language = "英语",

series = "Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI",

publisher = "IEEE Computer Society",

pages = "111--115",

booktitle = "Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019",

address = "美国",

}

Cai, H, Jiang, H, Han, M, Wang, Z, Wang, Y, Yang, J, Han, J, Liu, L & Zhao, W 2019, Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction. in Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019., 8839314, Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI, vol. 2019-July, IEEE Computer Society, pp. 111-115, 18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019, Miami, United States, 15/07/19. https://doi.org/10.1109/ISVLSI.2019.00029

Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction. / Cai, Hao; Jiang, Honglan; Han, Menglin et al.
Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019. IEEE Computer Society, 2019. p. 111-115 8839314 (Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI; Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Pj-AxMTJ

T2 - 18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019

AU - Cai, Hao

AU - Jiang, Honglan

AU - Han, Menglin

AU - Wang, Zhaohao

AU - Wang, You

AU - Yang, Jun

AU - Han, Jie

AU - Liu, Leibo

AU - Zhao, Weisheng

PY - 2019/7

Y1 - 2019/7

N2 - In order to realize high efficient magnetization switching in magnetic tunnel junction (MTJ), several potential alternative mechanisms have been realized to replace spin transfer torque (STT) method, such as the STT-assisted precessional voltage controlled magnetic anisotropy (VCMA), and the spin orbit torque (SOT) erasing plus STT programing. In this paper, we propose a method denoted as the Process-in-memory with Joint magnetization switching for Approximate computing in Magnetic Tunnel Junction (Pj-AxMTJ), by using the 1T-1M and 3T-1M bit-cell structures. The proposed method aims to implement a low-precision computational memory with dynamic approximate computing. Specifically, four nonvolatile approximate full adders (AxFAs) are proposed based on the writing operations of different types of magnetic random access memory. As no peripheral circuits but the memory bit-cells are used in the proposed design, the resultant area is significantly small. Moreover, the AxFAs can be easily reconfigured into memory units with simple wire connections. The simulation results for the proposed designs are then presented to show the precision-power-area-speed tradeoffs for addition operation. Finally, the accuracy of the AxFAs are further evaluated in an image processing application.

AB - In order to realize high efficient magnetization switching in magnetic tunnel junction (MTJ), several potential alternative mechanisms have been realized to replace spin transfer torque (STT) method, such as the STT-assisted precessional voltage controlled magnetic anisotropy (VCMA), and the spin orbit torque (SOT) erasing plus STT programing. In this paper, we propose a method denoted as the Process-in-memory with Joint magnetization switching for Approximate computing in Magnetic Tunnel Junction (Pj-AxMTJ), by using the 1T-1M and 3T-1M bit-cell structures. The proposed method aims to implement a low-precision computational memory with dynamic approximate computing. Specifically, four nonvolatile approximate full adders (AxFAs) are proposed based on the writing operations of different types of magnetic random access memory. As no peripheral circuits but the memory bit-cells are used in the proposed design, the resultant area is significantly small. Moreover, the AxFAs can be easily reconfigured into memory units with simple wire connections. The simulation results for the proposed designs are then presented to show the precision-power-area-speed tradeoffs for addition operation. Finally, the accuracy of the AxFAs are further evaluated in an image processing application.

KW - Approximate computing

KW - SOT erasing

KW - STT programming

KW - STT-assisted VCMA

KW - magnetic tunnel junction with joint switching

KW - process-in-memory

UR - https://www.scopus.com/pages/publications/85072974889

U2 - 10.1109/ISVLSI.2019.00029

DO - 10.1109/ISVLSI.2019.00029

M3 - 会议稿件

AN - SCOPUS:85072974889

T3 - Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI

SP - 111

EP - 115

BT - Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019

PB - IEEE Computer Society

Y2 - 15 July 2019 through 17 July 2019

ER -

Cai H, Jiang H, Han M, Wang Z, Wang Y, Yang J et al. Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction. In Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019. IEEE Computer Society. 2019. p. 111-115. 8839314. (Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI). doi: 10.1109/ISVLSI.2019.00029

Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction

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