Dataflow actor network partitioning for multiple FPGAS

Dataflow actor network is used to display the relation between different actors in a directed graph. It is suitable for modelling signal and video processing in software applications. In this paper, the use of dataflow actor network is extended to the hardware implementation of streaming application...

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Main Author:	Chin, Yong Huan
Format:	Thesis
Language:	English
Published:	2016
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/80933/1/ChinYongHuanMFKE2016.pdf
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id	my-utm-ep.80933
record_format	uketd_dc
spelling	my-utm-ep.809332019-07-24T00:10:55Z Dataflow actor network partitioning for multiple FPGAS 2016-06 Chin, Yong Huan TK Electrical engineering. Electronics Nuclear engineering Dataflow actor network is used to display the relation between different actors in a directed graph. It is suitable for modelling signal and video processing in software applications. In this paper, the use of dataflow actor network is extended to the hardware implementation of streaming applications via dataflow actor network partitioning for multiple FPGAs based on the number of cuts, connection workload, resource utilization ratio and latency. Multiple FPGAs partitioning is often required for implementing design with large logic count, for cost reduction, multi clock and multi power domains design implementation. The motivation of using the dataflow actor network is due to the nature of the network which closely resembles the structural view and the inter-connections of a design at the architecture level. This representation in the form of a dataflow actor network is suitable for implementing graph partitioning algorithms. The KL algorithm, GA, PSO, SA and WOA are used for single objective partitioning while the MOPSO, MOSA and MOWOA have been used for multi objective partitioning. The objective of this study is to develop partitioning algorithm suitable for use in dataflow actor network and to determine the appropriate partitioning criteria. Results showed that SA has better performance as compared to other partitioning algorithm for single objective partitioning. On the other hand, for multi objective partitioning the MOPSO has better performance for small design while MOSA has better performance for larger design. 2016-06 Thesis http://eprints.utm.my/id/eprint/80933/ http://eprints.utm.my/id/eprint/80933/1/ChinYongHuanMFKE2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:121153 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Chin, Yong Huan Dataflow actor network partitioning for multiple FPGAS
description	Dataflow actor network is used to display the relation between different actors in a directed graph. It is suitable for modelling signal and video processing in software applications. In this paper, the use of dataflow actor network is extended to the hardware implementation of streaming applications via dataflow actor network partitioning for multiple FPGAs based on the number of cuts, connection workload, resource utilization ratio and latency. Multiple FPGAs partitioning is often required for implementing design with large logic count, for cost reduction, multi clock and multi power domains design implementation. The motivation of using the dataflow actor network is due to the nature of the network which closely resembles the structural view and the inter-connections of a design at the architecture level. This representation in the form of a dataflow actor network is suitable for implementing graph partitioning algorithms. The KL algorithm, GA, PSO, SA and WOA are used for single objective partitioning while the MOPSO, MOSA and MOWOA have been used for multi objective partitioning. The objective of this study is to develop partitioning algorithm suitable for use in dataflow actor network and to determine the appropriate partitioning criteria. Results showed that SA has better performance as compared to other partitioning algorithm for single objective partitioning. On the other hand, for multi objective partitioning the MOPSO has better performance for small design while MOSA has better performance for larger design.
format	Thesis
qualification_level	Master's degree
author	Chin, Yong Huan
author_facet	Chin, Yong Huan
author_sort	Chin, Yong Huan
title	Dataflow actor network partitioning for multiple FPGAS
title_short	Dataflow actor network partitioning for multiple FPGAS
title_full	Dataflow actor network partitioning for multiple FPGAS
title_fullStr	Dataflow actor network partitioning for multiple FPGAS
title_full_unstemmed	Dataflow actor network partitioning for multiple FPGAS
title_sort	dataflow actor network partitioning for multiple fpgas
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2016
url	http://eprints.utm.my/id/eprint/80933/1/ChinYongHuanMFKE2016.pdf
_version_	1747818282762633216

Dataflow actor network partitioning for multiple FPGAS

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