A new solution based on multi-objective algorithm for multi-application mappings for Many-Core systems

Authors

Keywords:

many-core, network-on-chip, task mapping, metrics.

Abstract

In the current context of intelligent systems and big data, specifically concerning high-performance and efficient data processing for streams applications, single-core systems can no longer meet this demand. Increasing their operating frequencies would result in higher energy consumption for the chip as a whole. Thus, in this scenario, multicore and manycore chips appear to be a viable solution. However, distributing mono8 application or multi-application tasks on these devices is not trivial in practice. It is necessary to consider heat dissipation effects throughout the system while simultaneously ensuring fault tolerance and good load balancing. Although there is not yet a considerable number of works in the literature addressing the allocation of multi-applications in NoCs, there are many works focusing on mapping mono-applications. Therefore, this article proposes a multi-objective mapping model that focuses on performance metrics and heat distribution for multi-applications in manycores with NoCs, aiming to contribute in this direction. The results found are compared with the state-of-the-art algorithm in this scenario, showing promise for the field, with improvements of more than 30% in latency and 38% in fault tolerance when all applications are taken into account.

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Author Biographies

Manoel de Almeida, USFCAR

Manoel Aranda de Almeida is a PhD student at the Department of Computer Science, Federal University of São Carlos, Brazil. He holds a degree in Information Systems from Faculdade João XXIII and a master's degree in Computer Science from UFSCar. His research focuses on image and video processing, machine learning, remote sensing, manycore architectures, and hardware development using FPGAs.

E.C.Pedrino, UFSCAR

Emerson Carlos Pedrino is an Associate Professor in the Department of Computing at the Federal University of São Carlos, Brazil, with degrees in Electrical Engineering and Computational Physics from USP, where he graduated first in his class. He holds a Master’s and Ph.D. in Electrical Engineering from USP, as well as a Postdoctoral fellowship at the University of York, UK, funded by FAPESP. His work focuses on real-time image and video processing using FPGAs, machine learning, remote sensing, and manycore architectures. He also serves as an editorial board member for scientific journals and as a project reviewer for FAPESP.

Igor Felipe Gallon, UFSCAR

Igor Felipe Gallon  is a PhD student at the Department of Computer Science, Federal University of Sao Carlos, Brazil, with B.S.E. in Computer Engineering from the Federal University of São Carlos in 2018. He is currently pursuing a Master's degree in Computer Science at the same institution. His research interests encompass Reconfigurable Architectures, Many-Core Architectures, and Big Data.

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Published

2025-03-07

How to Cite

de Almeida, M., Pedrino, E., & Gallon, I. (2025). A new solution based on multi-objective algorithm for multi-application mappings for Many-Core systems. IEEE Latin America Transactions, 23(4), 323–328. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/9346