Artificial neural network emulation on NOC based multi-core FPGA platform

Mand, Nowshad Painda; Robino, Francesco; Öberg, Johnny

doi:10.1109/norchp.2012.6403122

Cited by 8 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Aim of this project is parallel simulation of neurons on NoC Architectures. [15] clarifies how an ANN can be emulated on FPGA based on NoC framework. SyNapse [16], a project by IBM for wide range of cognitive and sensory applications, uses ANN having 2D arrangement of neurons.…”

Section: Background and Related Workmentioning

confidence: 99%

Designing Efficient NoC-Based Neural Network Architectures for Identification of Epileptic Seizure

et al. 2021

View full text Add to dashboard Cite

Artificial Neural Networks (ANNs) mirror the analytical functions of human neural networks. The performance of smart healthcare systems has been limited to the increasing size and intricacy of information. Several ANN architectures help in the analysis of EEG signals for the identification of epileptic seizures. However, real-time performance needs to be accurate and very quick. Consequently, it is important to design efficient ANN models without compromising the feasibility of hardware realization. Since, CPUs and GPUs are based on conventional bus-system architectures, processing large complex datasets decreases the efficiency, scalability and versatility of the systems. To counter the bottlenecks of the bus-based architectures, Network-on-Chip has been efficient for complex computations. In this paper, we develop NoC-based feed-forward neural network and convolutional neural network models for the identification of epileptic seizure by analysis of continuously monitored EEG signal. The trained neural network models are mapped onto the Network-on-Chip to increase the throughput, power efficiency, parallelism and scalability of the architecture. The performance of all models is thoroughly explored in terms of throughput, energy, latency and identification accuracy of an epileptic seizure. Keywords Network-on-Chip • Feed-forward neural network • CNN • Epileptic seizure • Classification • Accelerator This article is part of the topical collection "Hardware for AI, Machine Learning and Emerging Electronic Systems" guest edited by Himanshu Thapliyal, Saraju Mohanty and VS Kanchana Bhaaskaran.

show abstract

Section: Background and Related Workmentioning

confidence: 99%