In:
Neuromorphic Computing and Engineering, IOP Publishing, Vol. 2, No. 4 ( 2022-12-01), p. 042501-
Kurzfassung:
The data throughput in the von Neumann architecture-based computing system is limited by its separated processing and memory structure, and the mismatching speed between the two units. As a result, it is quite difficult to improve the energy efficiency in conventional computing system, especially for dealing with unstructured data. Meanwhile, artificial intelligence and robotics nowadays still behave poorly in autonomy, creativity, and sociality, which has been considered as the unimaginable computational requirement for sensorimotor skills. These two plights have urged the imitation and replication of the biological systems in terms of computing, sensing, and even motoring. Hence, the so-called neuromorphic system has drawn worldwide attention in recent decade, which is aimed at addressing the aforementioned needs from the mimicking of neural system. The recent developments on emerging memory devices, nanotechnologies, and materials science have provided an unprecedented opportunity for this aim.
Materialart:
Online-Ressource
ISSN:
2634-4386
DOI:
10.1088/2634-4386/ac7a5a
Sprache:
Unbekannt
Verlag:
IOP Publishing
Publikationsdatum:
2022
ZDB Id:
3099608-9
