Using Blind Optimization Algorithm for Hardware/Software Partitioning | Zendy

Tao Zhang | Zendy; Xin Zhao | Zendy; Xinqi An | Zendy; Haojun Quan | Zendy; Zhichun Lei | Zendy

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Using Blind Optimization Algorithm for Hardware/Software Partitioning

Author(s) -

Tao Zhang,

Xin Zhao,

Xinqi An,

Haojun Quan,

Zhichun Lei

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2669481

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Hardware/software partitioning is playing an important role in designing complex embedded systems. In this paper, by considering the parallelism between hardware and software, we propose a more practical hardware/software partitioning method which can be combined with task scheduling. In one aspect, in order to select a more suitable partitioning algorithm, the concept of blind optimization algorithm for hardware/software partitioning is presented, and the advantages of this kind of algorithms are illustrated by diagrams. We combined the Shuffled Frog Leaping Algorithm (SFLA) with Earliest Time First (ETF), a scheduling algorithm, and proposed a new hardware/software partitioning algorithm named SFLA-ETF. The solution quality and algorithm execution time of SFLA-ETF is better than other blind algorithms and it can also obtain better solutions than non-blind optimization algorithm.

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