Integration and Co-design of Memristive Devices and Algorithms for Artificial Intelligence

iScience

Qinru Qiu¹  J. Joshua Yang¹  Joseph Van Nostrand²  Wei Wang³  Daniele Ielmini⁴  Peng Yao⁵  Wenhao Song⁵  Yang Li⁶ 

[1] Corresponding author;Air Force Research Laboratory, Information Directorate, Rome, NY, USA;Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET, Piazza L. da Vinci 32, Milano 20133, Italy;Electrical Engineering and Computer Science Department, Syracuse University, NY, USA;Electrical and Computer Engineering Department, University of Southern California, Los Angeles, CA, USA;The Andrew and Erna Viterbi Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel;

关键词: Computer Architecture;    Hardware Co-design;    Materials Science;   

DOI  :  

来源: DOAJ

【 摘 要 】

Summary: Memristive devices share remarkable similarities to biological synapses, dendrites, and neurons at both the physical mechanism level and unit functionality level, making the memristive approach to neuromorphic computing a promising technology for future artificial intelligence. However, these similarities do not directly transfer to the success of efficient computation without device and algorithm co-designs and optimizations. Contemporary deep learning algorithms demand the memristive artificial synapses to ideally possess analog weighting and linear weight-update behavior, requiring substantial device-level and circuit-level optimization. Such co-design and optimization have been the main focus of memristive neuromorphic engineering, which often abandons the “non-ideal” behaviors of memristive devices, although many of them resemble what have been observed in biological components. Novel brain-inspired algorithms are being proposed to utilize such behaviors as unique features to further enhance the efficiency and intelligence of neuromorphic computing, which calls for collaborations among electrical engineers, computing scientists, and neuroscientists.

【 授权许可】

Unknown