Affiliation:
1. Jiangnan University, Wuxi 214002, P. R. China
Abstract
As a third generation artificial neural network, spiking neuron network is expected to expand the artificial intelligence world. However, as a more detailed simulation of brain, a single run of spiking neural networks (SNNs) simulation can take hours to days. To get a better prediction of SNN simulation performance, existing work requires gathering result of actual runs to conduct accurate modeling. In this paper, we propose a nonempirical SNN simulation performance prediction method, prototyped in a hybrid CPU-FPGA cluster. Experiments show that our method, without actual simulation run, can get comparable accuracy with orders of magnitude less runtime cost.
Publisher
World Scientific Pub Co Pte Ltd
Subject
Electrical and Electronic Engineering,Hardware and Architecture,Electrical and Electronic Engineering,Hardware and Architecture
Cited by
1 articles.
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