Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5422
Título: NoC contention analysis using a branch-and-prune algorithm
Autor: Dasari, Dakshina
Nikolic, Borislav
Nelis, Vincent
Petters, Stefan M.
Palavras-chave: Design
Many-core systems
Real-time systems
wormhole routing
Data: 2014
Editora: ACM
Relatório da Série N.º: ACM Transactions on Embedded Computing Systems (TECS);Vol. 13 Issue 3
Resumo: “Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.
Peer review: yes
URI: http://hdl.handle.net/10400.22/5422
DOI: 10.1145/2567937
Versão do Editor: http://dl.acm.org/citation.cfm?doid=2597868.2567937
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