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SynFull: Synthetic Traffic Models Capturing Cache Coherent Behaviour

Abstract: Modern and future many-core systems represent complex architectures. The communication fabrics of these large systems heavily influence their performance and power consumption. Current simulation methodologies for evaluating networks-on-chip (NoCs) are not keeping pace with the increased complexity of our systems; architects often want to explore many different design knobs quickly. Methodologies that capture workload trends with faster simulation times are highly beneficial at early stages of architectural exploration. We propose SynFull, a synthetic traffic generation methodology that captures both application and cache coherence behaviour to rapidly evaluate NoCs. SynFull allows designers to quickly indulge in detailed performance simulations without the cost of long-running full-system simulation. By capturing a full range of application and coherence behaviour, architects can avoid the over or underdesign of the network as may occur when using traditional synthetic traffic patterns such as uniform random. SynFull has errors as low as 0.3% and provides 50x speedup on average over full-system simulation.

If you use our SynFull traffic models in your research, please cite our ISCA 2014 paper:

Mario Badr and Natalie Enright Jerger. "SynFull: Synthetic Traffic Models Capturing Cache Coherent Behaviour." In Proceedings of the 41st International Symposium on Computer Architecture (ISCA). June 2014.

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For support or questions, please contact mario dot badr at mail dot utoronto dot ca