基于Intel SCC多核平台的作业到达感知分布式运行时资源管理

Vasileios Tsoutsouras, S. Xydis, D. Soudris
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引用次数: 4

摘要

现代计算系统正在处理各种复杂的动态工作负载,这些工作负载存在不同的工作到达率。这种多样性增加了开发复杂的运行时机制的需求,这些机制可以有效地管理系统资源。此外,在向千核处理器体系结构发展的过程中,集中式资源管理方法很可能会形成严重的性能瓶颈,因此对分布式运行时资源管理(DRTRM)方案的研究现在得到了很多关注。在本文中,我们为具有延展性特征的应用程序提出了一个工作到达感知DRTRM框架,该框架在英特尔单芯片云计算机(SCC)多核平台上实现。我们发现资源分配不仅受到系统内部决策机制的高度影响,还受到系统上传入应用程序间隔率的高度影响。基于这一观察,我们提出了一种有效的准入控制策略,利用DRTRM部分的电压和频率缩放(VFS),最终保留分布式决策,从而提高系统性能,并显著提高其消耗的能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Job-Arrival Aware Distributed Run-Time Resource Management on Intel SCC Manycore Platform
Modern computing systems are dealing with a diverse set of complex and dynamic workloads in the presence of varying job arrival rates. This diversity is raising the need for the development of sophisticated run-time mechanisms that efficiently manage system's resources. In addition, moving towards kilo-core processor architectures, centralized resource management approaches will most probably form a severe performance bottleneck, thus the study of Distributed Run-Time Resource Management (DRTRM) schemes is now gaining a lot of attention. In this paper, we propose a job-arrival aware DRTRM framework for applications with malleable characteristics, implemented on top of the Intel Single-Chip Cloud Computer (SCC) many-core platform. We show that resource allocation is highly affected not only by the internal decision mechanisms but also from the incoming application interval rate on the system. Based on this observation, we propose an effective admission control strategy utilizing Voltage and Frequency Scaling (VFS) of parts of the DRTRM which eventually retains the distributed decision making thus improving system performance in combination with significant gains in its consumed energy.
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