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

Adam Górski, Maciej Ogorzalek

2017

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.

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