Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

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,...

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Bibliographic Details
Published in:IEEE MICRO 2018-01, Vol.38 (1), p.82-99
Main Authors: Davies, Mike, Srinivasa, Narayan, Lin, Tsung-Han, Chinya, Gautham, Cao, Yongqiang, Choday, Sri Harsha, Dimou, Georgios, Joshi, Prasad, Imam, Nabil, Jain, Shweta, Liao, Yuyun, Lin, Chit-Kwan, Lines, Andrew, Liu, Ruokun, Mathaikutty, Deepak, McCoy, Steven, Paul, Arnab, Tse, Jonathan, Venkataramanan, Guruguhanathan, Weng, Yi-Hsin, Wild, Andreas, Yang, Yoonseok, Wang, Hong
Format: Article
Language:English
Subjects:
Algorithm design and analysis
artificial intelligence
Biological neural networks
Central processing units
Computational modeling
Computer architecture
CPUs
Machine learning
Microprocessors
Neural networks
neuromorphic computing
Neuromorphics
Neurons
Solvers
Spiking
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Summary: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.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2018.112130359