An accurate performance model for network-on-chip and multicomputer interconnection networks
Journal of Parallel and Distributed Computing
A traffic-aware adaptive routing algorithm on a highly reconfigurable network-on-chip architecture
Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Mathematical formalisms for performance evaluation of networks-on-chip
ACM Computing Surveys (CSUR)
On bottleneck analysis in stochastic stream processing
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Dynamic power management for multidomain system-on-chip platforms: An optimal control approach
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special Section on Networks on Chip: Architecture, Tools, and Methodologies
Online learning of timeout policies for dynamic power management
ACM Transactions on Embedded Computing Systems (TECS)
Analytical performance modeling of shuffle-exchange inspired mesh-based Network-on-Chips
Performance Evaluation
Proceedings of the International Conference on Computer-Aided Design
Journal of Systems Architecture: the EUROMICRO Journal
Systolic traffic modelling in network on chip
International Journal of Wireless and Mobile Computing
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Networks-on-chip (NoCs) have been proposed as a viable solution to solving the communication problem in multicore systems. In this new setup, mapping multiple applications on available computational resources leads to interaction and contention at various network resources. Consequently, taking into account the traffic characteristics becomes of crucial importance for performance analysis and optimization of the communication infrastructure, as well as proper resource management. Although queuing-based approaches have been traditionally used for performance analysis purposes, they cannot properly account for many of the traffic characteristics (e.g., non-stationarity, self-similarity) that are crucial for multicore platform design. To overcome these limitations, we propose a statistical physics inspired approach to capture the traffic dynamics in multicore systems. As shown later in this paper, this is of fundamental significance for re-thinking the very basis of multicore systems design; it also opens up new research directions into NoC optimization which require accurate models of time-dependent and space-dependent traffic behavior.