MapPro: Proactive Runtime Mapping for Dynamic Workloads by Quantifying Ripple Effect of Applications on Networks-on-Chip
2015 (English)In: NOCS '15 Proceedings of the 9th International Symposium on Networks-on-Chip, ACM Digital Library, 2015Conference paper (Refereed)
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 region to map an incoming application is an NP-hard problem in view of minimizing congestion and maximizing performance. In this paper, we propose a proactive region selection strategy which prioritizes nodes that offer lower congestion and dispersion. Our proposed 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 suitable 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, eliminating 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 congestion and 21% dispersion when compared to the state-of-the-art region selection methods.
Place, publisher, year, edition, pages
ACM Digital Library, 2015.
Computer Systems Embedded Systems
IdentifiersURN: urn:nbn:se:kth:diva-169509OAI: oai:DiVA.org:kth-169509DiVA: diva2:821731
IEEE/ACM International Symposium on Networks-on-Chip (NOCS),September 28-30 2015, Vancouver, Canada
QC 201602122015-06-152015-06-152016-02-12Bibliographically approved