# Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

“Loihi: A Neuromorphic Manycore Processor with On-Chip Learning” (2018), by Mike Davies et al. Engineering research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Mike Davies, Narayan Srinivasa, Tsung-Han Lin, Gautham N. Chinya, Yongqiang Cao, Sri Harsha Choday, Georgios D. Dimou, Prasad Joshi, Nabil Imam, Shweta Jain et al.
- Published: January 1, 2018
- Field: Engineering
- DOI: https://doi.org/10.1109/mm.2018.112130359
- Source: https://doi.org/10.1109/mm.2018.112130359

## 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.

Canonical page: https://nerdi.pages.dev/paper/W2783525259
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