神经形态工程学
计算机科学
过程(计算)
卷积神经网络
计算机体系结构
Spike(软件开发)
计算
嵌入式系统
并行计算
尖峰神经网络
计算机工程
人工神经网络
算法
人工智能
操作系统
软件工程
作者
Mike Davies,Narayan Srinivasa,Tsung-Han Lin,Gautham N. Chinya,Yongqiang Cao,Sri Harsha Choday,Georgios D. Dimou,Prasad Joshi,Nabil Imam,Shweta Jain,Yuyun Liao,Chit-Kwan Lin,Andrew Lines,Ruokun Liu,Deepak A. Mathaikutty,Steven McCoy,Arnab Paul,Jonathan Tse,Guruguhanathan Venkataramanan,Yi-Hsin Weng
出处
期刊:IEEE Micro
[Institute of Electrical and Electronics Engineers]
日期:2018-01-01
卷期号:38 (1): 82-99
被引量:3411
标识
DOI:10.1109/mm.2018.112130359
摘要
Loihi is a 60-mm2 chip fabricated in Intels 14-nm process that advances the state-of-the-art modeling of spiking neural networks in silicon. It integrates a wide range of novel features for the field, such as hierarchical connectivity, dendritic compartments, synaptic delays, and, most importantly, programmable synaptic learning rules. Running a spiking convolutional form of the Locally Competitive Algorithm, Loihi can solve LASSO optimization problems with over three orders of magnitude superior energy-delay-product compared to conventional solvers running on a CPU iso-process/voltage/area. This provides an unambiguous example of spike-based computation, outperforming all known conventional solutions.
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