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On Self-Tuning Networks-on-Chip for Dynamic Network-Flow Dominance Adaptation

Xiaohang Wang, Mei Yang, Yingtao Jiang, Terrence Mak, Masoud Daneshtalab, Maurizio Palesi, On Self-Tuning Networks-on-Chip for Dynamic Network-Flow Dominance Adaptation. ACM Transactions on Embedded Computing Systems 13(2), 73–94, 2014.

Abstract:

Modern network-on-chip (NoC) systems are required to handle complex runtime traffic patterns and un-
precedented applications. Data traffics of these applications are difficult to fully comprehend at design time
so as to optimize the network design. However, it has been discovered that the majority of dataflows in a
network are dominated by less than 10% of the specific pathways. In this article, we introduce a method
that is capable of identifying critical pathways in a network at runtime and can then dynamically reconfig-
ure the network to optimize for network performance subject to the identified dominated flows. An online
learning and analysis scheme is employed to quickly discover the emerging dominated traffic flows and
provides a statistical traffic prediction using regression analysis. The architecture of a self-tuning network
is also discussed which can be reconfigured by setting up the identified point-to-point paths for the domi-
nance dataflows in large traffic volumes. The merits of this new approach are experimentally demonstrated
using comprehensive NoC simulations. Compared to the conventional network architectures over a range
of realistic applications, the proposed self-tuning network approach can effectively reduce the latency and
power consumption by as much as 25% and 24%, respectively. We also evaluated the configuration time and
additional hardware cost. This new approach demonstrates the capability of an adaptive NoC to handle more
complex and dynamic applications.

BibTeX entry:

@ARTICLE{jWaYaJiMaDaPa14a,
  title = {On Self-Tuning Networks-on-Chip for Dynamic Network-Flow Dominance Adaptation},
  author = {Wang, Xiaohang and Yang, Mei and Jiang, Yingtao and Mak, Terrence and Daneshtalab, Masoud and Palesi, Maurizio},
  journal = {ACM Transactions on Embedded Computing Systems},
  volume = {13},
  number = {2},
  publisher = {ACM},
  pages = {73–94},
  year = {2014},
  keywords = {Networks-on-chip, self tuning, regression, reconfigurable},
}

Belongs to TUCS Research Unit(s): Embedded Computer and Electronic Systems (ECES)

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