Adaptive Iterative Improvement GP-based Methodology for HW/SW Co-synthesis of Embedded Systems

Adam Górski, Maciej Ogorzalek

Abstract

The paper presents a novel adaptive genetic programming based iterative improvement algorithm for hardware/software co-synthesis of distributed embedded systems. The algorithm builds solutions by starting from suboptimal architecture (the fastest) and using system-building options improves the system’s quality. Most known genetic programming algorithms for co-synthesis of embedded systems are built choosing fixed probability. In our approach we decided to change the probability during the work of the program.

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Paper Citation


in Harvard Style

Górski A. and Ogorzalek M. (2017). Adaptive Iterative Improvement GP-based Methodology for HW/SW Co-synthesis of Embedded Systems . In Proceedings of the 7th International Joint Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PEC, (PECCS 2017) ISBN 978-989-758-266-0, pages 56-59. DOI: 10.5220/0006476500560059


in Bibtex Style

@conference{pec17,
author={Adam Górski and Maciej Ogorzalek},
title={Adaptive Iterative Improvement GP-based Methodology for HW/SW Co-synthesis of Embedded Systems},
booktitle={Proceedings of the 7th International Joint Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PEC, (PECCS 2017)},
year={2017},
pages={56-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006476500560059},
isbn={978-989-758-266-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PEC, (PECCS 2017)
TI - Adaptive Iterative Improvement GP-based Methodology for HW/SW Co-synthesis of Embedded Systems
SN - 978-989-758-266-0
AU - Górski A.
AU - Ogorzalek M.
PY - 2017
SP - 56
EP - 59
DO - 10.5220/0006476500560059