A Survey on Architecture Advances Enabled by Emerging Beyond-CMOS Technologies

被引：16
作者：
Chen, An [1 ]
Datta, Supriyo [2 ]
Hu, X. Sharon [3 ]
Niemier, Michael T. [4 ]
Rosing, Tajana Simunic [5 ]
Yang, J. Joshua [6 ]
机构：
[1] Semicond Res Corp, Durham, NC USA
[2] Purdue Univ, W Lafayette, IN 47907 USA
[3] Univ Notre Dame, Dept Elect Engn, Notre Dame, IN 46556 USA
[4] Univ Notre Dame, Notre Dame, IN 46556 USA
[5] Univ Calif San Diego, Dept Elect & Commun Engn, San Diego, CA 92103 USA
[6] Univ Massachusetts, Dept Elect & Comp Engn, UMass, Amherst, MA 01003 USA
来源：
IEEE DESIGN & TEST | 2019年 / 36卷 / 03期
关键词：
NEURAL-NETWORK; LOW-POWER; SPECULATIVE ADDITION; ASSOCIATIVE MEMORY; BOOTH MULTIPLIERS; PERFORMANCE; DEVICES; ERROR; LOGIC; CLASSIFICATION;
D O I：
10.1109/MDAT.2019.2902359
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Editor's note: Emerging non-CMOS devices have various advantages and challenges. It is important to undertake device-architecture codesign to harness the true benefits of beyond-CMOS devices. This article discusses the landscape of designing computing systems with emerging devices.
引用
收藏
页码：46 / 68
页数：23
相关论文
共 164 条
  • [1] ACKLEY DH, 1985, COGNITIVE SCI, V9, P147
  • [2] Compute Caches
    Aga, Shaizeen
    Jeloka, Supreet
    Subramaniyan, Arun
    Narayanasamy, Satish
    Blaauw, David
    Das, Reetuparna
    [J]. 2017 23RD IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTER ARCHITECTURE (HPCA), 2017, : 481 - 492
  • [3] The effect of LUT and cluster size on deep-submicron FPGA performance and density
    Ahmed, E
    Rose, J
    [J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2004, 12 (03) : 288 - 298
  • [4] Adiabatic quantum computation
    Albash, Tameem
    Lidar, Daniel A.
    [J]. REVIEWS OF MODERN PHYSICS, 2018, 90 (01)
  • [5] Pattern classification by memristive crossbar circuits using ex situ and in situ training
    Alibart, Fabien
    Zamanidoost, Elham
    Strukov, Dmitri B.
    [J]. NATURE COMMUNICATIONS, 2013, 4
  • [6] Alsuwaiyan A, 2015, IEEE INT SYMP NANO, P13, DOI 10.1109/NANOARCH.2015.7180577
  • [7] Equivalent-accuracy accelerated neural-network training using analogue memory
    Ambrogio, Stefano
    Narayanan, Pritish
    Tsai, Hsinyu
    Shelby, Robert M.
    Boybat, Irem
    di Nolfo, Carmelo
    Sidler, Severin
    Giordano, Massimo
    Bodini, Martina
    Farinha, Nathan C. P.
    Killeen, Benjamin
    Cheng, Christina
    Jaoudi, Yassine
    Burr, Geoffrey W.
    [J]. NATURE, 2018, 558 (7708) : 60 - +
  • [8] [Anonymous], NAN COMPUTING RES NC
  • [9] [Anonymous], WORKSH APPR COMP
  • [10] [Anonymous], NATURE NANOTECHNOL
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