Multiple-Choice Hardware/Software Partitioning for Tree Task-Graph on MPSoC. (23rd February 2019)

• Record Type: Journal Article
• Authors: Shi, Wenjun; Wu, Jigang; Jiang, Guiyuan; Lam, Siew-kei
• Editors: Stewart, Iain
• Is Part Of: Computer journal. Volume 63:Number 5(2020)
• Page Start: 688
• Page End: 700
• Publication Date: 2019-02-23
• Subjects: multiple choices -- hardware/software partitioning -- tree task graph -- multiple processors system on chip -- algorithm; Computers -- Periodicals; 005.1
• DOI: 10.1093/comjnl/bxy140
• Languages: English
• ISSNs: 0010-4620

Abstract

Abstract: 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.