Circuit Reliability Comparison Between Stochastic Computing and Binary Computing

被引:8
|
作者
Zhang, Zuodong [1 ]
Wang, Runsheng [1 ]
Zhang, Zhe [1 ]
Zhang, Yawen [1 ]
Guo, Shaofeng [1 ]
Huang, Ru [1 ]
机构
[1] Peking Univ, Inst Microelect, Key Lab Microelect Devices & Circuits MOE, Beijing 100871, Peoples R China
关键词
Aging; Integrated circuit reliability; Integrated circuit modeling; Stochastic processes; Transistors; Computational modeling; Reliability-enhanced design; NBTI; stochastic computing; reliability simulation; FinFET; frequency guardband; AGING SENSOR;
D O I
10.1109/TCSII.2020.2993273
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
Reliability-enhanced circuit design is increasingly demanded due to severer transistor aging and variations at nanoscale. In this brief, new insights of inherently enhancing reliability are presented, based on the emerging computing paradigm of stochastic computing (SC). A new cross-layer reliability simulation flow supporting statistical static timing analysis (SSTA) is proposed, with a new long-term compact transistor aging model validated by 16/14nm FinFET experimental data. Then, the reliability of SC circuits in practical applications is investigated and compared with that of conventional binary circuits, for the first time. The results indicate that, the performance of SC circuits is intrinsically resistant to aging and variations ascribed to the circuit topology and the probability encoding. It suggests that, SC can provide more relaxed circuit design margins, offering promises to the application of emerging nanodevices in the future.
引用
收藏
页码:3342 / 3346
页数:5
相关论文
共 50 条
  • [21] Additional Local Propagation Stopper Circuit for Asynchronous Binary Wave Computing
    Paasio, Ari
    2014 14TH INTERNATIONAL WORKSHOP ON CELLULAR NANOSCALE NETWORKS AND THEIR APPLICATIONS (CNNA), 2014,
  • [22] Mean Circuit Design Using Correlated Random Bitstreams in Stochastic Computing
    Li, Feiyu
    Xie, Guangjun
    Han, Jie
    Zhang, Yongqiang
    2022 IEEE 22ND INTERNATIONAL CONFERENCE ON NANOTECHNOLOGY (NANO), 2022, : 4 - 7
  • [23] Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit
    Ashok, P.
    Sundari, B. Bala Tripura
    COMPUTATION, 2023, 11 (12)
  • [24] Bio-Inspired Stochastic Computing Using Binary CBRAM Synapses
    Suri, Manan
    Querlioz, Damien
    Bichler, Olivier
    Palma, Giorgio
    Vianello, Elisa
    Vuillaume, Dominique
    Gamrat, Christian
    DeSalvo, Barbara
    IEEE TRANSACTIONS ON ELECTRON DEVICES, 2013, 60 (07) : 2402 - 2409
  • [25] ANALYZED BINARY COMPUTING
    METROPOLIS, NC
    IEEE TRANSACTIONS ON COMPUTERS, 1973, C 22 (06) : 573 - 576
  • [26] Computing on binary strings
    Bu, Tian-Ming
    Yuan, Chen
    Zhang, Peng
    THEORETICAL COMPUTER SCIENCE, 2015, 562 : 122 - 128
  • [27] INTRODUCTION TO STOCHASTIC COMPUTING
    KOHL, A
    FREQUENZ, 1977, 31 (10) : 315 - 319
  • [28] Asynchronous Stochastic Computing
    Gonzalez-Guerrero, Patricia
    Stan, Mircea R.
    CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2019, : 280 - 285
  • [29] On the Limits of Stochastic Computing
    Neugebauer, Florian
    Polian, Ilia
    Hayes, John P.
    PROCEEDINGS OF THE 2019 FOURTH IEEE INTERNATIONAL CONFERENCE ON REBOOTING COMPUTING (ICRC), 2019, : 98 - 105
  • [30] Survey of Stochastic Computing
    Alaghi, Armin
    Hayes, John P.
    ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2013, 12