PARTIES: QoS-Aware Resource Partitioning for Multiple Interactive Services
PARTIES: QoS-Aware Resource Partitioning for Multiple Interactive Services
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DOI：
10.1145/3297858.3304005
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发表时间：
2019-04
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影响因子：
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通讯作者：
Shuang Chen;Christina Delimitrou;José F. Martínez
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作者：
Shuang Chen;Christina Delimitrou;José F. Martínez
现代数据中心中的多租户目前仅限于一个延迟关键的交互式服务，与一个或多个低优先级的尽力而为的作业一起运行。这限制了多租户的效率提升，特别是随着越来越多的云应用程序从批处理作业转移到具有严格延迟要求的服务。我们提出PARTIES，一个QoS感知的资源管理器，使任意数量的交互式，延迟关键的服务，共享一个物理节点没有QoS违规。PARTIES利用一组硬件和软件资源分区机制在运行时动态调整分配，以满足每个共同调度的工作负载的QoS要求，并最大化机器的吞吐量。我们在最先进的服务器平台上通过一系列不同的交互式服务对PARTIES进行评估。我们的研究结果表明，PARTIES平均提高了61%的QoS下的吞吐量，现有的资源管理器相比，和提高的速度增加的数量共同调度的应用程序每个物理主机。
Multi-tenancy in modern datacenters is currently limited to a single latency-critical, interactive service, running alongside one or more low-priority, best-effort jobs. This limits the efficiency gains from multi-tenancy, especially as an increasing number of cloud applications are shifting from batch jobs to services with strict latency requirements. We present PARTIES, a QoS-aware resource manager that enables an arbitrary number of interactive, latency-critical services to share a physical node without QoS violations. PARTIES leverages a set of hardware and software resource partitioning mechanisms to adjust allocations dynamically at runtime, in a way that meets the QoS requirements of each co-scheduled workload, and maximizes throughput for the machine. We evaluate PARTIES on state-of-the-art server platforms across a set of diverse interactive services. Our results show that PARTIES improves throughput under QoS by 61% on average, compared to existing resource managers, and that the rate of improvement increases with the number of co-scheduled applications per physical host.