Abstract
Kahn process networks (KPNs) is a distributed model of computation used for describing systems where streams of data are transformed by processes executing in sequence or parallel. Autonomous processes communicate through unbounded FIFO channels in absence of a global scheduler. In this work, we propose a task-aware middleware concept that allows adaptivity in KPN implemented over a Network on Chip (NoC). We also list our ideas on the development of a simulation platform as an initial step towards creating fault tolerance strategies for KPNs applications running on NoCs. In doing that, we extend our SACRE (Self-Adaptive Component Run Time Environment) framework by integrating it with an open source NoC simulator, Noxim. We evaluate the overhead that the middleware brings to the the total execution time and to the total amount of data transferred in the NoC. With this work, we also provide a methodology that can help in identifying the requirements and implementing fault tolerance and adaptivity support on real platforms.
Highlights
Past decade has witnessed a change in the design of powerful processors
This led to the design of multicore chips, usually consisting of multiprocessor symmetric Systems on Chip (MPSoCs), with limited numbers of CPU-L1 cache nodes interconnected by simple bus connections and capable in turn of becoming nodes in larger multiprocessors
Being our work a first attempt to evaluate the cost of using a middleware layer for supporting the adaptivity of the application, we cannot directly compare our results with those obtained in previous work adopting the Kahn process networks (KPNs) model of computation
Summary
Past decade has witnessed a change in the design of powerful processors. It has been realized that running processors at higher and higher frequencies is not sustainable due to unproportional increases in power consumption. The distributed run-time environment can manage the adaptation of the application for high-level goals such as fault-tolerance, high performance, and lowpower consumption by migrating the application components between the available resources and/or increasing the parallelism of the application by instantiating multiple copies of the same component on different resources [3, 4]. Such a selfadaptive RTE constitutes a fundamental part in order to enable systemwide self-adaptivity and continuity of service support [5].
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