Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation

Oussama Djedidi, Mohand Arab Djeziri, Nacer K. M’Sirdi, Aziz Naamane

2017

Abstract

This paper deals with the modelling of a CPU-GPUchip embedded in an Android phone. The model is used for the estimation of variables that characterise the operating state of System on Chip (SoC). The proposed model is built to demonstrate the causal relationships between the variables, through its interconnected structure of subsystems. This structure allows the extension of other components or the easy exchange of subsystems in the case of a change in components or operating mode. The model developed here requires no additional instrumentation—other than the one present on the phone—which facilitates its implementation. It is used for the estimation of the state of the system and can also be used for monitoring and behaviour prediction. The model is validated and the results are promising for further implementation.

Paper Citation

in Harvard Style

Djedidi O., Djeziri M., M’Sirdi N. and Naamane A. (2017). Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 338-345. DOI: 10.5220/0006470803380345

in Bibtex Style

@conference{icinco17,
author={Oussama Djedidi and Mohand Arab Djeziri and Nacer K. M’Sirdi and Aziz Naamane},
title={Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={338-345},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006470803380345},
isbn={978-989-758-263-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation
SN - 978-989-758-263-9
AU - Djedidi O.
AU - Djeziri M.
AU - M’Sirdi N.
AU - Naamane A.
PY - 2017
SP - 338
EP - 345
DO - 10.5220/0006470803380345