SHIP: a computational framework for simulating and validating novel technologies in hardware spiking neural networks.

ABSTRACT: Investigations in the field of spiking neural networks (SNNs) encompass diverse, yet overlapping, scientific disciplines. Examples range from purely neuroscientific investigations, researches on computational aspects of neuroscience, or applicative-oriented studies aiming to improve SNNs performance or to develop artificial hardware counterparts. However, the simulation of SNNs is a complex task that can not be adequately addressed with a single platform applicable to all scenarios. The optimization of a simulation environment to meet specific metrics often entails compromises in other aspects. This computational challenge has led to an apparent dichotomy of approaches, with model-driven algorithms dedicated to the detailed simulation of biological networks, and data-driven algorithms desi

SUBMITTER: Gemo E 

PROVIDER: S-EPMC10804805 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature