Modeling of router structure for SNN-applicable NoC definitions

Modeling of router structure for SNN-applicable NoC definitions

Zhou, Yongkang (TU Delft Electrical Engineering, Mathematics and Computer Science)

van Leuken, T.G.R.M. (mentor)
Zjajo, Amir (graduation committee)

Delft University of Technology

Electrical Engineering | Circuits and Systems

2022-04-19

Spiking neural networks (SNN), as the third-generation artificial neural network, has a similar potential pulse triggering mechanism to the biological neuron. This mechanism enables the spiking neural network to increase computing power compared to the traditional artificial neural network to process complex information. However, a large number of interconnection resources is required. This requirement is highly consistent with the characteristics of the network on chip (NoC). This thesis is aimed at developing a scalable cycle-accurate simulator based on Noxim, which provides a configurable NoC that can simulate neuron-to-neuron communication for delivering spiking traffic. This simulator achieves several configurable metrics including topology and routing schemes, network size, the number of channels, and neuron mapping methods. This thesis then evaluates the effects of these metrics on performance for two kinds of traffic patterns. To take power consumption and area into account, this thesis also provides an approximate estimate of area and power consumption for trade-offs in the early-design stage.

Spiking Neural Networks(SNNs))
Network-on-chip(NoC)
Router design

http://resolver.tudelft.nl/uuid:4885cd26-755d-4693-8543-58c70c70bd40

2024-04-20

Student theses

master thesis

© 2022 Yongkang Zhou