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M. Haghbayan, A. Kanduri, A. Rahmani, P. Liljeberg, A. Jantsch, H. Tenhunen:
"MapPro: Proactive Runtime Mapping for Dynamic Workloads by Quantifying Ripple Effect of Applications on Networks-on-Chip";
Talk: International Symposium on Networks on Chip, Vancouver, Canada; 2015-09-28 - 2015-09-30; in: "Proceedings of the International Symposium on Networks on Chip", (2015), ISBN: 978-1-4503-3396-2; 8 pages.

Increasing dynamic workloads running on NoC-based many-core
systems necessitates efficient runtime mapping strategies. With an
unpredictable nature of application profiles, selecting a rational re-
gion to map an incoming application is an NP-hard problem in view
of minimizing congestion and maximizing performance. In this pa-
per, we propose a proactive region selection strategy which prior-
itizes nodes that offer lower congestion and dispersion. Our pro-
posed strategy, MapPro, quantitatively represents the propagated
impact of spatial availability and dispersion on the network with
every new mapped application. This allows us to identify a suit-
able region to accommodate an incoming application that results
in minimal congestion and dispersion. We cluster the network into
squares of different radii to suit applications of different sizes and
proactively select a suitable square for a new application, eliminat-
ing the overhead caused with typical reactive mapping approaches.
We evaluated our proposed strategy over different traffic patterns
and observed gains of up to 41% in energy efficiency, 28% in con-
gestion and 21% dispersion when compared to the state-of-the-art
region selection methods.

On-chip many-core systems, Application mapping, Task allocation, Proactive Runtime Mapping

http://dx.doi.org/10.1145/2786572.2786589