Novel In-Memory Computing Adder Using 8+T SRAM

被引:5
|
作者
Song, Soonbum [1 ]
Kim, Youngmin [1 ]
机构
[1] Hongik Univ, Sch Elect & Elect Engn, Seoul 04066, South Korea
基金
新加坡国家研究基金会;
关键词
von Neumann bottleneck; memory wall; SRAM; in-memory computing (IMC); Process-in-Memory (PIM);
D O I
10.3390/electronics11060929
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Von Neumann architecture-based computing systems are facing a von Neumann bottleneck owing to data transfer between separated memory and processor units. In-memory computing (IMC), on the other hand, reduces energy consumption and improves computing performance. This study explains an 8(+)T SRAM IMC circuit based on 8(+)T differential SRAM (8(+)T SRAM) and proposes 8(+)T SRAM-based IMC full adder (FA) and 8(+)T SRAM-based IMC approximate adder, which are based on the 8(+)T SRAM IMC circuit. The 8(+)T SRAM IMC circuit performs SRAM read and bitwise operations simultaneously and performs each logic operation parallelly. The proposed IMC FA and the proposed IMC approximate adder can be applied to a multi-bit adder. The two adders are based on the 8(+)T SRAM IMC circuit and thus read and compute simultaneously. In this study, the 8(+)T SRAM IMC circuit was applied to the adder, leveraging its ability to perform read and logic operations simultaneously. According to the performance in this study, the 8(+)T SRAM IMC circuit, proposed FA, proposed RCA, and proposed approximated adder are good candidates for IMC, which aims to reduce energy consumption and improve overall performance.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Realizing In-Memory Computing using Reliable Differential 8T SRAM for Improved Latency
    Dahiya, Ayush
    Mittal, Poornima
    Rohilla, Rajesh
    ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS, 2024, 29 (06)
  • [2] A High-Performance, Low-Power 8-Bit Full-Adder Using 8+T Differential SRAM for Computation-in-Memory
    Jung, Jihyung
    Kim, Youngmin
    2022 19TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2022, : 131 - 132
  • [3] A Reconfigurable 8T SRAM Macro for Bit-Parallel Searching and Computing In-Memory
    Chen, Yuzong
    Mu, Junjie
    Kim, Hyunjoon
    Lu, Lu
    Kim, Tony Tae-Hyoung
    2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22), 2022, : 2556 - 2560
  • [4] AND8T SRAM Macro with Improved Linearity for Multi-bit In-Memory Computing
    Sharma, Vishal
    Kim, Ju Eon
    Jo, Yong-Jun
    Chen, Yuzong
    Kim, Tony Tae-Hyoung
    2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2021,
  • [5] Low Power Ternary XNOR using 10T SRAM for In-Memory Computing
    Lee, Sanghyun
    Kim, Youngmin
    2022 19TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2022, : 352 - 353
  • [6] A Fast Half Adder using 8T SRAM for Computation-in-Memory
    Han, Jaehyeon
    Kim, Youngmin
    2021 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS-ASIA (ICCE-ASIA), 2021,
  • [7] Design of In-Memory Computing Enabled SRAM Macro
    Monga, Kanika
    Behera, Sunit
    Chaturvedi, Nitin
    Gurunarayanan, S.
    2022 IEEE 19TH INDIA COUNCIL INTERNATIONAL CONFERENCE, INDICON, 2022,
  • [8] Novel In-memory Computing Circuit using Muller C-element
    Song, Soonbum
    Kim, Youngmin
    18TH INTERNATIONAL SOC DESIGN CONFERENCE 2021 (ISOCC 2021), 2021, : 81 - 82
  • [9] Design of reliable and fast Schmitt trigger 10T SRAM cells using in-memory computing
    Rani, Mucherla Usha
    Reddy, N. Siva Sankara
    Naik, B. Rajendra
    ENGINEERING RESEARCH EXPRESS, 2024, 6 (04):
  • [10] A 9T-SRAM in-memory computing macro for Boolean logic and multiply-and-accumulate operations
    Dai, Chenghu
    Ren, Zihua
    Guan, Lijun
    Liu, Haitao
    Gao, Mengya
    Lu, Wenjuan
    Pang, Zhiyong
    Peng, Chunyu
    Wu, Xiulong
    MICROELECTRONICS JOURNAL, 2024, 144