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Optimization of Duplication-Based Schedules on Network-on-Chip Based Multi-Processor System-on-Chips

机译:基于片上网络的多处理器片上系统中基于复制的计划的优化

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Many applications such as streaming applications are both computation and communication intensive. The Multi-Processor System-on-Chip (MPSoC) based on Network-on-Chip (NoC) outperforms the multiprocessors with bus-based networking architecture in communication bandwidth and scalability, making it a better choice for implementing systems running these applications. It's important to schedule both the computation and communication onto processors and the networking architecture so as to satisfy the stringent timing requirements. To reduce or avoid inter-processor communication, task duplication has been employed in scheduling. Most of the available techniques for the duplication-based scheduling problem use heuristics to solve the problem, and seldom has any work studied further improving the schedule performance, despite the fact that the heuristic cannot provide quality guarantee. To fill in this gap, this paper introduces a duplication and mapping constrained task-communication co-scheduling problem that assumes the duplication strategy and task-to-processor mapping are known a priory, and proposes two Integer Linear Programming (ILP) formulations, i.e., CF-ILP and CA-ILP, to solve two editions of this problem, i.e., the contention-free problem and the contention-aware problem. The proposed ILP formulations optimize the ordering and timing of the communication and computation, thus improving the performance. Both synthesized and real applications are tested on a set of platforms to evaluate the performance of the proposed methods. The experimental results demonstrate the effectiveness of the proposed methods.
机译:流应用程序之类的许多应用程序都需要大量计算和通信。基于片上网络(NoC)的多处理器片上系统(MPSoC)在通信带宽和可扩展性方面优于基于总线的网络体系结构的多处理器,使其成为实现运行这些应用程序的系统的更好选择。重要的是将计算和通信调度到处理器和网络体系结构上,以满足严格的时序要求。为了减少或避免处理器间的通信,在任务调度中采用了任务复制。用于基于重复的调度问题的大多数可用技术都使用启发式方法来解决该问题,尽管启发式方法无法提供质量保证,但很少进行任何研究来进一步改善调度性能。为了填补这一空白,本文介绍了一个复制和映射受限的任务通信协同调度问题,该问题假设复制策略和任务到处理器的映射是先验的,并提出了两种整数线性规划(ILP)公式,即CF-ILP和CA-ILP来解决此问题的两个版本,即无竞争问题和竞争意识问题。提出的ILP公式可优化通信和计算的顺序和时序,从而提高性能。在一组平台上测试了综合应用程序和实际应用程序,以评估所提出方法的性能。实验结果证明了所提方法的有效性。

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