Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

Abstract

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.

Keywords

Neuromorphic engineeringComputer scienceSpiking neural networkProcess (computing)Parallel computingConvolutional neural networkSpike (software development)ComputationComputer architectureArtificial neural networkEmbedded systemComputer engineeringArtificial intelligenceAlgorithm

Affiliated Institutions

Intel (United States) US

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Publication Info

Year: 2018
Type: article
Volume: 38
Issue: 1
Pages: 82-99
Citations: 3336
Access: Closed

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APA Style

                            
                                
                                    Mike Davies, 
                                
                                    Narayan Srinivasa, 
                                
                                    Tsung-Han Lin
                                
                                et al.
                            
                            (2018). 
                            Loihi: A Neuromorphic Manycore Processor with On-Chip Learning. 
                            IEEE Micro
                            , 38
                            (1)
                            , 82-99.
                            https://doi.org/10.1109/mm.2018.112130359
                        

Identifiers

DOI: 10.1109/mm.2018.112130359