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Hermes: Improving Server Utilization by Colocation-Aware Runtime Systems

机译:Hermes:通过托管托管运行时系统提高服务器利用率

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Improving server utilization is increasingly important to service providers. Latency-critical services have strict tail latency service-level objects and safe colocation of the latencycritical service with other workloads on the same machine is difficult. This would underutilize server resources. We present Hermes, a user-level resource management layer to address this dilemma. We implement two kinds of runtime systems in Hermes, one for latency-critical workloads (LC runtime) and one for besteffort workloads (BE runtime). LC runtime implements userlevel thread management and controls the dedicated computing resources occupied by latency-critical workload through a feedback-based controller. BE runtimes schedule threads of besteffort workloads to take advantage of simultaneous multithreading technology. Runtime systems are aware of their colocation and work in a cooperative approach to improve server utlization without violating the tail latency service-level objects of the latency-critical workload. Hermes is implemented entirely at user-level on Linux. We evaluate Hermes using memcached and several sythetic micro-benchmarks, the result shows that Hermes could achieve both safe colocation and improvement of core utilization.
机译:对于服务提供商而言,提高服务器利用率越来越重要。延迟关键服务具有严格的尾部延迟服务级别对象,并且很难将延迟关键服务与同一台机器上的其他工作负载安全地托管在一起。这将利用不足服务器资源。我们提出了爱马仕(Hermes),它是一个用户级资源管理层,用于解决这一难题。我们在Hermes中实现了两种运行时系统,一种用于时延关键型工作负载(LC运行时),另一种用于尽力而为的工作负载(BE运行时)。 LC运行时实现了用户级线程管理,并通过基于反馈的控制器来控制延迟关键型工作负载所占用的专用计算资源。 BE运行时调度尽力而为工作负载的线程,以利用同步多线程技术的优势。运行时系统意识到它们的共置关系,并以协作的方式工作以改善服务器的实用性,而又不会违反对延迟至关重要的工作负载的尾部延迟服务级别对象。 Hermes完全在Linux上的用户级别上实现。我们使用memcached和几个合成的微基准评估了Hermes,结果表明Hermes可以实现安全的主机代管和核心利用率的提高。

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