Algorithmic aspects for multiple-choice hardware/software partitioning

Hardware–software partitioning (HW/SW) divides an application into software and hardware. It is one of the crucial steps in embedded system design. For a given task, hardware with different areas may provide different execution speeds due to the potential of parallel execution in hardware implementa...

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Main Authors: Wu, Jigang, Sun, Qiqiang, Srikanthan, Thambipillai
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/97336
http://hdl.handle.net/10220/13130
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-973362020-05-28T07:17:16Z Algorithmic aspects for multiple-choice hardware/software partitioning Wu, Jigang Sun, Qiqiang Srikanthan, Thambipillai School of Computer Engineering DRNTU::Engineering::Computer science and engineering Hardware–software partitioning (HW/SW) divides an application into software and hardware. It is one of the crucial steps in embedded system design. For a given task, hardware with different areas may provide different execution speeds due to the potential of parallel execution in hardware implementation. Thus, one task may have multiple-choice in hardware implementation according to the available hardware areas. Existing HW/SW partitioning approaches typically consider only a single implementation manner in hardware, overlooking the multiple-choice of hardware implementations. This paper presents a computing model to cater for the HW/SW partitioning problems with the multiple-choice implementation in hardware. An efficient heuristic algorithm is proposed to rapidly generate approximate solution, that is further refined by a tabu search algorithm also customized in this paper. Moreover, a dynamic programming algorithm is proposed for the exact solution of the relatively small problems. Extensive simulation results show that the approximate solutions are very close to the exact ones, and they can be refined by tabu search to the solutions with the error no more than 1.5% for all cases considered in this paper. 2013-08-15T08:06:30Z 2019-12-06T19:41:37Z 2013-08-15T08:06:30Z 2019-12-06T19:41:37Z 2012 2012 Journal Article Wu, J., Sun, Q.,& Srikanthan, T. (2012). Algorithmic aspects for multiple-choice hardware/software partitioning. Computers & Operations Research, 39(12), 3281-3292. 0305-0548 https://hdl.handle.net/10356/97336 http://hdl.handle.net/10220/13130 10.1016/j.cor.2012.04.013 en Computers & operations research
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Wu, Jigang
Sun, Qiqiang
Srikanthan, Thambipillai
Algorithmic aspects for multiple-choice hardware/software partitioning
description Hardware–software partitioning (HW/SW) divides an application into software and hardware. It is one of the crucial steps in embedded system design. For a given task, hardware with different areas may provide different execution speeds due to the potential of parallel execution in hardware implementation. Thus, one task may have multiple-choice in hardware implementation according to the available hardware areas. Existing HW/SW partitioning approaches typically consider only a single implementation manner in hardware, overlooking the multiple-choice of hardware implementations. This paper presents a computing model to cater for the HW/SW partitioning problems with the multiple-choice implementation in hardware. An efficient heuristic algorithm is proposed to rapidly generate approximate solution, that is further refined by a tabu search algorithm also customized in this paper. Moreover, a dynamic programming algorithm is proposed for the exact solution of the relatively small problems. Extensive simulation results show that the approximate solutions are very close to the exact ones, and they can be refined by tabu search to the solutions with the error no more than 1.5% for all cases considered in this paper.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Wu, Jigang
Sun, Qiqiang
Srikanthan, Thambipillai
format Article
author Wu, Jigang
Sun, Qiqiang
Srikanthan, Thambipillai
author_sort Wu, Jigang
title Algorithmic aspects for multiple-choice hardware/software partitioning
title_short Algorithmic aspects for multiple-choice hardware/software partitioning
title_full Algorithmic aspects for multiple-choice hardware/software partitioning
title_fullStr Algorithmic aspects for multiple-choice hardware/software partitioning
title_full_unstemmed Algorithmic aspects for multiple-choice hardware/software partitioning
title_sort algorithmic aspects for multiple-choice hardware/software partitioning
publishDate 2013
url https://hdl.handle.net/10356/97336
http://hdl.handle.net/10220/13130
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