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Scheduling Policies for Processor Coallocation in Multicluster Systems

机译：多集群系统中处理器合并的调度策略

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摘要

Building multicluster systems out of multiple, geographically distributed clusters interconnected by high-speed wide-area networks can provide access to a larger computational power and to a wider range of resources. Jobs running on multiclusters and, more generally, in grids, may require (processor) coallocation, i.e., the simultaneous allocation of resources (processors) in different clusters or subsystems of a grid. In this paper, we propose four scheduling policies for processor coallocation in multiclusters, and we assess with simulations their performance under a wide variety of parameter settings. In particular, in our simulations we use synthetic workloads and workloads derived from the logs of actual systems and from runtime measurements. We conclude that although coallocation makes scheduling more difficult and the wide-area communication critically impacts the performance, there is a wide range of realistic applications that may benefit from coallocation. However, unrestricted coallocation is not recommended: Limiting the total job size or the number or the sizes of their components improves performance.
机译：在通过高速广域网互连的多个地理分布的集群中构建多集群系统可以提供对更大计算能力和更广泛资源的访问。在多集群上（通常在网格中）运行的作业可能需要（处理器）合并，即在网格的不同集群或子系统中同时分配资源（处理器）。在本文中，我们为多集群中的处理器合并提出了四种调度策略，并通过仿真评估了它们在各种参数设置下的性能。特别地，在我们的仿真中，我们使用合成工作负载以及从实际系统的日志和运行时测量得出的工作负载。我们得出的结论是，尽管合并使调度变得更加困难，并且广域通信严重影响性能，但仍有许多实际的应用可能会受益于合并。但是，不建议进行无限制的合并：限制总作业大小或组件的数量或大小可以提高性能。

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