Reduction of network load by mapping the application in the network on a chip using the discrete Harris hawk algorithm
Subject Areas :Elham Hajebi 1 , Vahid Sattari-Naeini 2
1 - Department of Computer Engineering
2 -
Keywords: Network-on-chip, Core-mapping, Latency, Utilization of link, HHO,
Abstract :
Reducing load and power consumption in on-chip network systems is very important and one of the most important issues to increase the efficiency of on-chip network is the issue of mapping an application on the chip network. Solving the application mapping problem to find the best mapping is a complex and time consuming issue and has a huge impact on network latency and power consumption. In this paper, using the Harris hawk algorithm, we have been able to provide a method for mapping processing cores to the network on chip to reduce the load on the network and thus congestion in the links and improve network performance. The simulation results show that this algorithm performs better than the basic algorithms.
]1] A. V. Bhaskar and T. Venkatesh, "Performance analysis of network-on-chip in many-core processors," Journal of Parallel and Distributed Computing, vol. 147, pp. 196-208, 2021.
[2] اسدی بهاره، رشادی میدیا، خادم زاده احمد، کرباسی مصطفی،"مدل های چرخشی تطابقی و الگوهای ترافیکی جهت کاهش اتلاف نوری در شبکه های روی تراشه ی نوری"، فصلنامه فناوری اطلاعات و ارتباطات ایران، 10(36 و 35) ، 26-15، 1397.
]3] W. Amin et al., "Performance evaluation of application mapping approaches for Network-on-Chip designs," IEEE Access, vol. 8, pp. 63607-63631, 2020.
]4] A. K. Singh, W. Jigang, A. Kumar, and T. Srikanthan, "Run-time mapping of multiple communicating tasks on MPSoC platforms," Procedia Computer Science, vol. 1, no. 1, pp. 1019-1026, 2010.
]5] S. Kaushik, A. K. Singh, and T. Srikanthan, "Computation and communication aware run-time mapping for NoC-based MPSoC platforms," in 2011 IEEE International SOC Conference, 2011, pp. 185-190: IEEE.
]6] M. Obaidullah and G. N. Khan, "Application mapping to mesh NoCs using a Tabu-search based swarm optimization," Microprocessors and Microsystems, vol. 55, pp. 13-25, 2017.
]7] B. Xie, T. Chen, W. Hu, X. Tang, and D. Wang, "An energy-aware online task mapping algorithm in NoC-based system," The Journal of Supercomputing, vol. 64, no. 3, pp. 1021-1037, 2013
]8] C. Wang, Y. Zhu, J. Jiang, X. Liu, and X. Han, "A dynamic contention-aware application allocation algorithm for many-core processor," in 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, 2015, pp. 308-315: IEEE.
]9] T. Maqsood et al., "Energy and communication aware task mapping for MPSoCs," Journal of parallel and distributed computing, vol. 121, pp. 71-89, 2018.
]10] A. A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, and H. Chen, "Harris hawks optimization: Algorithm and applications," Future Generation Computer Systems, vol. 97, pp. 849-872, 2019 .
]11] R. Abbassi, A. Abbassi, A. A. Heidari, and S. Mirjalili, "An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models," Energy conversion and management, vol. 179, pp. 362-372, 2019.
]12] H. Faris et al., "An intelligent system for spam detection and identification of the most relevant features based on evolutionary random weight networks," Information Fusion, vol. 48, pp. 67-83, 2019.
]13] G. Wu, "Across neighborhood search for numerical optimization," Information Sciences, vol. 329, pp. 597-618, 2016.
]14] J. Dréo, A. Pétrowski, P. Siarry, and E. Taillard, Metaheuristics for hard optimization: methods and case studies. Springer Science & Business Media, 2006.
]15] E.-G. Talbi, Metaheuristics: from design to implementation. John Wiley & Sons, 2009.
]16] S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, "others. 1983," Optimization by simulated annealing. science, vol. 220, no. 4598, pp. 671-680, 1983.
]17] H. John, "Holland. genetic algorithms," Scientific american, vol. 267, no. 1, pp. 44-50, 1992.
]18] J. Luo, H. Chen, Y. Xu, H. Huang, and X. Zhao, "An improved grasshopper optimization algorithm with application to financial stress prediction," Applied Mathematical Modelling, vol. 64, pp. 654-668, 2018 .
]19] Q. Zhang, H. Chen, J. Luo, Y. Xu, C. Wu, and C. Li, "Chaos enhanced bacterial foraging optimization for global optimization," IEEE Access, vol. 6, pp. 64905-64919, 2018.
]20] M. Mafarja et al., "Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems," Knowledge-Based Systems, vol. 145, pp. 25-45, 2018.
]21] I. Aljarah, M. Mafarja, A. A. Heidari, H. Faris, Y. Zhang, and S. Mirjalili, "Asynchronous accelerating multi-leader salp chains for feature selection," Applied Soft Computing, vol. 71, pp. 964-979, 2018.
]22] S. Salcedo-Sanz, "Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures," Physics Reports, vol. 655, pp. 1-70, 2016.
]23] L. F. Bittencourt, E. R. Madeira, and N. L. Da Fonseca, "Scheduling in hybrid clouds," IEEE Communications Magazine, vol. 50, no. 9, pp. 42-47, 2012.
]24] Q. Le, G. Yang, W. N. Hung, X. Song, and X. Zhang, "Pareto optimal mapping for tile-based network-on-chip under reliability constraints," International Journal of Computer Mathematics, vol. 92, no. 1, pp. 41-58, 2015.
]25] Y. Ben-Itzhak, E. Zahavi, I. Cidon, and A. Kolodny, "HNOCS: modular open-source simulator for heterogeneous NoCs," in 2012 international conference on embedded computer systems (SAMOS), 2012, pp. 51-57: IEEE.
]26] J. Huang, C. Buckl, A. Raabe, and A. Knoll, "Energy-aware task allocation for network-on-chip based heterogeneous multiprocessor systems," in 2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing, 2011, pp. 447-454: IEEE.
]27] G. Juve, A. Chervenak, E. Deelman, S. Bharathi, G. Mehta, and K. Vahi, "Characterizing and profiling scientific workflows," Future Generation Computer Systems, vol. 29, no. 3, pp. 682-692, 2013.