Distributed stable states for process networks: algorithm, analysis, and experiments on intel SCC

  • Authors:
  • Devendra Rai;Lars Schor;Nikolay Stoimenov;Lothar Thiele

  • Affiliations:
  • Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland;Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland;Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland;Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland

  • Venue:
  • Proceedings of the 50th Annual Design Automation Conference
  • Year:
  • 2013

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Abstract

Technology scaling is a common trend in current embedded systems. It has promoted the use of multi-core, multi-processor, and distributed platforms. Such systems usually require run-time migration of distributed applications between the different nodes of the platform in order to balance the workload or to tolerate faults. Before an application can be migrated, it needs to be brought to a stable state such that restarting the application after migration does not violate its functional correctness. An application in a stable state does not change its context any further, and therefore, stabilization is a prerequisite for any application migration. Process networks are a common model of computation for specifying distributed applications. However, most results on the migration of process networks do not provide an algorithm to put a general process network into a stable state, suitable for migration. This paper proposes a technique which efficiently and correctly brings a process network executing on a distributed system to a known stable state. The correctness of the technique is independent of the temporal characteristics of the system and the topology of the process network. The required modifications of a process network are lightweight and preserve its original functionality. A model characterizing the timing properties of the technique is provided. The feasibility and efficiency of the proposed approach and the respective model are validated with experimental results on Intel's SCC platform.