GP-based Methodology for HW/SW Co-synthesis of Multiprocessor Embedded Systems with Increasing Number of Individuals Obtained by Mutation

Adam Górski, Maciej Ogorzalek

Abstract

In this work, a genetic programming methodology for co-synthesis of multiprocessor systems is presented. Genotype is a tree which nodes include system construction procedures. Thus the design methodology is evolving. Next generations are obtained using genetic operators: mutation, reproduction and crossover. Unlike other algorithms in presented methodology number of individuals obtained by mutation operator is not const. Therefore number of individuals in each population is increasing. The size of final generation is found by the algorithm.

References

  1. Acasandrei, L., Barriga, A., 2012. FPGA implementation of an embedded face detection system based on LEON3. In Proceedings of the International Conference on Image Pro-cessing, Computer Vision, and Pattern Recognition.
  2. Mahdjoub, J., Rousseaux, F., 2014. Planning and Optimization of Resources Deployment: Application to Crisis Management. In Proceedings of the 11th IEEE International Conference on Embedded Software and Systems.
  3. Kopetz, H., 2008. The complexity challenge in embedded system design. In Proceedings of the 11th IEEE International Symposium on object Oriented RealTime Distributed Computing.
  4. Martin, G., 2006. Overview of the MPSoC Design Challenge. In Proceedings of the 43rd annual Design Automation Conference.
  5. Henzinger, T.A., Sifakis, J., 2006. The Embedded Systems Design Challenge. In Lecture Notes in Computer Science, vol. 4085, pp 1-15.
  6. Jiang, K., Eles, P., Peng, Z., 2012. Co-design techniques for distributed real-time embedded systems with communication security constrains. Design Automation and Test in Europe (DATE 2012).
  7. Deniziak, S., 2004. Cost-efficient synthesis of multiprocessor heterogeneous systems. In Control and Cybernetics, vol. 33, No. 2.
  8. Yen, T., Wolf, W., 1995. Sensivity-Driven Co-Synthesis of Distributed Embedded Systems. In Proceedings of the International Symposium on System Synthesis.
  9. Górski, A., Ogorzalek, M., 2014a. Iterative Improvement methodology for hardware/software co-synthesis of embedded systems based on genetic programming. In Proceedings of the 11th IEEE International Conference on Embedded Software and Systems (Work in Progress session).
  10. Dave, B., Lakshminarayana, G., Jha, N., 1997. COSYN: Hardware/software Co-synthesis of Embedded Systems. In Proceedings of the 34th annual Design Automation Conference (DAC'97).
  11. Chehida, K., B., Auguin, M., 2002. HW/SW Partitioning Approach for Reconfigurable System Design. In Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems, CASES 2002.
  12. Purnaprajna, M., Reformat, M., Pedrycz, W., 2007. Genetic algorithms for hardware-software partitioning and optimal resource allocation. In Journal of Systems Architecture, 53(7).
  13. Eles, P., Peng, Z., Kuchcinski, K., Doboli, A., 1997. System Level Hardware/Software Partitioning Based on Simulated Annealing and Tabu Search. In Design Automation for Embedded Systems, vol. 2, No 1.
  14. Deniziak, S., Górski, A., 2008. Hardware/Software CoSynthesis of Distributed Embedded Systems Using Genetic programming. In Proceedings of the 8th International Conference Evolvable Systems: From Biology to Hardware, ICES 2008. Lecture Notes in Computer Science, Vol. 5216. SPRINGER-VERLAG.
  15. Shankaran, N., Roy, N., Schmidt, D. C., Koutsoukos, X. D. C., Chen, Y., Lu, C., 2008. Design and performance evaluation of an adaptive resource management framework for distributed real-time and embedded systems. EURASIP Journal on Embedded Systems.
  16. Górski, A., Ogorzalek, M., 2014b. Adaptive GP-based algorithm for hardware-software co-design of distributed embedded systems. In Proceedings of the 4th International Conference on Pervasive and Embedded Computing and Communication Systems.
  17. Koza, J., R., Bennett III, F., H., Lohn, j., Dunlap, F., Keane, M., A., Andre, D., 1997. Automated synthesis of computational circuits using genetic programming. In Proceedings of the IEEE Conference on Evolutionary Computation. IEEE.
  18. Holland., J., H., 1992. An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. IN MIT Press, Cambridge, MA.
  19. Krawiec, G., 2002. Genetic programming-based construction of features for machine learning and knowledge discovery tasks. In Genetic Programming and Evolvable Machines, vol. 3, No. 4., pp. 329-343.
  20. Giacobini, M., Provero, P., Vanneschi L., Mauri, G. 2014. Towards the Use of Genetic Programming for the Prediction of Survival in Cancer. In Evolution, Complexity and Artificial Life, pp177-192.
  21. John R. Koza. 2010. Human-competitive results produced by genetic programming. In Genetic programming and evolvable machines, vol. 11, issue 3-4. SPRINGERVERLAG.
  22. Engelhardt, N., Dallou, T., Elhossini, A., Juurlink, B 2014. An Integrated Hardware-Software Approach to Task Graph Management. In Proceedings of the 16th IEEE International Conference on High Performance and Communications.
  23. Dick, R., P., Jha, N., K., 1998. MOGAC: a multiobjective Genetic algorithm for the Co-Synthesis of Hardware-Software Embedded Systems. In IEEE Trans. on Computer Aided Design of Integrated Circiuts and systems, vol. 17, No. 10.
  24. Ruxton., G., D., 2006. The unequal variance t-test is an underused alternative to Student's t-test and the Mann-Whitney U test. In Behavioral Ecology, 17(4). doi:http:// dx.doi.org/10.1093/beheco/ark016.
Download


Paper Citation


in Harvard Style

Górski A. and Ogorzalek M. (2015). GP-based Methodology for HW/SW Co-synthesis of Multiprocessor Embedded Systems with Increasing Number of Individuals Obtained by Mutation . In Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-758-084-0, pages 275-280. DOI: 10.5220/0005238702750280


in Bibtex Style

@conference{peccs15,
author={Adam Górski and Maciej Ogorzalek},
title={GP-based Methodology for HW/SW Co-synthesis of Multiprocessor Embedded Systems with Increasing Number of Individuals Obtained by Mutation},
booktitle={Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2015},
pages={275-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005238702750280},
isbn={978-989-758-084-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - GP-based Methodology for HW/SW Co-synthesis of Multiprocessor Embedded Systems with Increasing Number of Individuals Obtained by Mutation
SN - 978-989-758-084-0
AU - Górski A.
AU - Ogorzalek M.
PY - 2015
SP - 275
EP - 280
DO - 10.5220/0005238702750280