Neuromorphic hardware as a self-organizing computing system

Autor:	Khacef, Lyes, Girau, Bernard, Rougier, Nicolas, Upegui, Andres, Miramond, Benoit
Rok vydání:	2018
Předmět:	Computer Science - Neural and Evolutionary Computing Computer Science - Artificial Intelligence Computer Science - Hardware Architecture Computer Science - Distributed Parallel and Cluster Computing
Druh dokumentu:	Working Paper
Popis:	This paper presents the self-organized neuromorphic architecture named SOMA. The objective is to study neural-based self-organization in computing systems and to prove the feasibility of a self-organizing hardware structure. Considering that these properties emerge from large scale and fully connected neural maps, we will focus on the definition of a self-organizing hardware architecture based on digital spiking neurons that offer hardware efficiency. From a biological point of view, this corresponds to a combination of the so-called synaptic and structural plasticities. We intend to define computational models able to simultaneously self-organize at both computation and communication levels, and we want these models to be hardware-compliant, fault tolerant and scalable by means of a neuro-cellular structure. Comment: Published in IEEE World Congress on Computational Intelligence (WCCI), International Workshop: Neuromorphic Hardware in Practice and Use (NHPU), Jul. 2018, Rio de Janeiro, Brazil
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1810.12640 Zobrazit plný text záznamu View this record from Arxiv