CrossNets: Neuromorphic Hybrid CMOS/Nanoelectronic Networks

被引:90
作者
Likharev, Konstantin K. [1 ]
机构
[1] SUNY Stony Brook, Dept Phys & Astron, Stony Brook, NY 11794 USA
关键词
Nanoelectronics; Hybrid Circuits; Crossbar; Latching Switches; Memristive Devices; Neuromorphic Circuits; Neural Networks; Plasticity; Adaptation; Cognitive Tasks; RECENT PROGRESS; ARCHITECTURES; CMOL; CIRCUITS; LITHOGRAPHY;
D O I
10.1166/sam.2011.1177
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Hybrid CMOS/nanoelectronic circuits, combining CMOS chips with simple nanoelectronic crossbar add-ons, may extend the exponential Moore-Law progress of microelectronics beyond the 10-nm frontier. This paper reviews the development of neuromorphic networks ("CrossNets") based on this prospective technology. In these networks, the neural cell bodies ("somas") are implemented in the CMOS subsystem, crossbar nanowires are used as axons and dendrites, while two-terminal crosspoint devices are used as elementary synapses. Extensive analysis and simulations have shown that such networks may perform virtually all information processing tasks demonstrated with software-implemented neural networks, with much higher performance. Estimates show that Cross Nets may eventually overcome bio-cortical circuits in density, at comparable connectivity, while operating 4 to 6 orders of magnitude faster, at manageable power dissipation.
引用
收藏
页码:322 / 331
页数:10
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