Title:	neker
DNr:	LiU-2019-27
Project Type:	LiU Compute
Principal Investigator:	Magnus Sethson <magnus.sethson@liu.se>
Affiliation:	Linköpings universitet
Duration:	2019-06-07 – 2023-07-01
Classification:	20207
Keywords:

Abstract

neker is a first attempt for a spiking neuron network computational engine aiming for deep learning tests with a highly efficient memory footprint. Its unique feature is to project an unstructured net onto a structured computational core. This is accomplished by mixing sparse and dense matrix operations using C functions primarily from the GSL project. (neker means "sädeskärve" in old Swedish language and refers to its structured look). The main application is for evaluating condition monitoring strategies using a large set of measurements on a pneumatic test stand in our laboratory here at LiU. The project goal is to develop a small and efficient spiking neural network engine that can possible run on embedded systems. Training need super computer power though.