Multiple-choice hardware/software partitioning for tree task-graph on MPSoC
Hardware/software (HW/SW) partitioning, that decides which components of an application are implemented in hardware and which ones in software, is a crucial step in embedded system design. On modern heterogeneous embedded system platform, each component of application can typically have multiple fea...
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sg-ntu-dr.10356-1523002021-08-04T03:27:57Z Multiple-choice hardware/software partitioning for tree task-graph on MPSoC Shi, Wenjun Wu, Jigang Jiang, Guiyuan Lam, Siew-Kei School of Computer Science and Engineering Engineering::Computer science and engineering Multiple Choices Hardware/Software Partitioning Hardware/software (HW/SW) partitioning, that decides which components of an application are implemented in hardware and which ones in software, is a crucial step in embedded system design. On modern heterogeneous embedded system platform, each component of application can typically have multiple feasible configurations/implementations, trading off quality aspects (e.g. energy consumption, completion time) with usage for various types of resources. This provides new opportunities for further improving the overall system performance, but few works explore the potential opportunity by incorporating the multiple choices of hardware implementation in the partitioning process. This paper proposes three algorithms for multiple-choice HW/SW partitioning of tree-shape task graph on multiple processors system on chip (MPSoC) with the objective of minimizing execution time, while meeting area constraint. Firstly, an efficient heuristic algorithm is proposed to rapidly generate an approximate solution. The obtained solution produced by the first algorithm is then further refined by a customized Tabu search algorithm. We also propose a dynamic programming algorithm to calculate the exact solutions for relatively smaller scale instances. Simulation results show that the proposed heuristic algorithm is able to quickly generate good approximate solutions, and the solutions become very close to the exact solutions after refined by the proposed Tabu search algorithm, in comparison to the exact solutions produced by the dynamic programming algorithm. This work was supported by the National Key R&D Program of China under Grant No. 2018YFB1003201. It was also supported in part by the National Natural Science Foundation of China under Grant No. 61672171, by Guangdong Natural Science Foundation of China under Grant No. 2018B030311007 and by Guangdong Educational Commission foundation of China under Grant No. 2016KZDXM052 2021-08-04T03:27:57Z 2021-08-04T03:27:57Z 2020 Journal Article Shi, W., Wu, J., Jiang, G. & Lam, S. (2020). Multiple-choice hardware/software partitioning for tree task-graph on MPSoC. The Computer Journal, 63(5), 688-700. https://dx.doi.org/10.1093/comjnl/bxy140 0010-4620 https://hdl.handle.net/10356/152300 10.1093/comjnl/bxy140 2-s2.0-85081668554 5 63 688 700 en The Computer Journal © 2019 The British Computer Society. All rights reserved. |
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Engineering::Computer science and engineering Multiple Choices Hardware/Software Partitioning Shi, Wenjun Wu, Jigang Jiang, Guiyuan Lam, Siew-Kei Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
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Hardware/software (HW/SW) partitioning, that decides which components of an application are implemented in hardware and which ones in software, is a crucial step in embedded system design. On modern heterogeneous embedded system platform, each component of application can typically have multiple feasible configurations/implementations, trading off quality aspects (e.g. energy consumption, completion time) with usage for various types of resources. This provides new opportunities for further improving the overall system performance, but few works explore the potential opportunity by incorporating the multiple choices of hardware implementation in the partitioning process. This paper proposes three algorithms for multiple-choice HW/SW partitioning of tree-shape task graph on multiple processors system on chip (MPSoC) with the objective of minimizing execution time, while meeting area constraint. Firstly, an efficient heuristic algorithm is proposed to rapidly generate an approximate solution. The obtained solution produced by the first algorithm is then further refined by a customized Tabu search algorithm. We also propose a dynamic programming algorithm to calculate the exact solutions for relatively smaller scale instances. Simulation results show that the proposed heuristic algorithm is able to quickly generate good approximate solutions, and the solutions become very close to the exact solutions after refined by the proposed Tabu search algorithm, in comparison to the exact solutions produced by the dynamic programming algorithm. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Shi, Wenjun Wu, Jigang Jiang, Guiyuan Lam, Siew-Kei |
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Article |
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Shi, Wenjun Wu, Jigang Jiang, Guiyuan Lam, Siew-Kei |
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Shi, Wenjun |
title |
Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
title_short |
Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
title_full |
Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
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Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
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Multiple-choice hardware/software partitioning for tree task-graph on MPSoC |
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multiple-choice hardware/software partitioning for tree task-graph on mpsoc |
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2021 |
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https://hdl.handle.net/10356/152300 |
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1707774596245094400 |