Towards self-adaptive MPSoC systems with adaptivity throttling

W. Quan, A. Pimentel
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引用次数: 3

Abstract

Today's multi-processor system-on-chip (MPSoC) systems increasingly have to deal with dynamically changing application workload scenarios. To cope with such dynamic application behavior, these systems could dynamically adapt the mapping of application tasks onto the underlying system resources to improve the system's performance. However, such performance improvement comes at the cost of a system reconfiguration in which application tasks may have to be migrated between processors. This trade-off implies that reconfiguring the system is only beneficial when the performance gains outweight the re-configuration overhead. To address this problem for MPSoCs, this paper presents a scenario-based run-time resource management framework with the ability of adaptivity throttling that uses the history of application scenario execution behavior to predict the actual benefit of a system reconfiguration to allow for explicitly deciding (at runtime) whether or not to reconfigure. Experimental results reveal that our proposed approach substantially improves the system's efficiency as compared to MPSoCs that do not provide such intelligent reconfiguration control.
基于自适应节流的自适应MPSoC系统研究
当今的多处理器片上系统(MPSoC)系统越来越需要处理动态变化的应用工作负载场景。为了处理这种动态应用程序行为,这些系统可以动态地调整应用程序任务到底层系统资源的映射,以提高系统的性能。然而,这种性能改进是以系统重新配置为代价的,其中应用程序任务可能必须在处理器之间迁移。这种权衡意味着,只有当性能增益超过重新配置开销时,重新配置系统才有好处。为了解决mpsoc的这个问题,本文提出了一个基于场景的运行时资源管理框架,该框架具有自适应调节的能力,它使用应用程序场景执行行为的历史来预测系统重新配置的实际好处,从而允许(在运行时)明确地决定是否重新配置。实验结果表明,与不提供这种智能重新配置控制的mpsoc相比,我们提出的方法大大提高了系统的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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