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Ensemble-level Power Management for Dense Blade Servers

机译:密集刀片服务器的集成级电源管理

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One of the key challenges for high-density servers (e.g., blades) is the increased costs in addressing the power and heat density associated with compaction. Prior approaches have mainly focused on reducing the heat generated at the level of an individual server. In contrast, this work proposes power efficiencies at a larger scale by leveraging statistical properties of concurrent resource usage across a collection of systems ("ensemble"). Specifically, we discuss an implementation of this approach at the blade enclosure level to monitor and manage the power across the individual blades in a chassis. Our approach requires low-cost hardware modifications and relatively simple software support. We evaluate our architecture through both prototyping and simulation. For workloads representing 132 servers from nine different enterprise deployments, we show significant power budget reductions at performances comparable to conventional systems.
机译:高密度服务器(例如刀片)的主要挑战之一是解决与压实相关的功率和热密度的成本增加。先前的方法主要集中在减少单个服务器级别产生的热量。相反,这项工作通过利用整个系统集合中“并发资源使用情况”的统计属性,提出了更大的功率效率(“合奏”)。具体来说,我们在刀片服务器机箱级别讨论此方法的实现,以监视和管理机箱中各个刀片服务器的电源。我们的方法需要低成本的硬件修改和相对简单的软件支持。我们通过原型设计和仿真来评估我们的架构。对于代表来自9个不同企业部署的132台服务器的工作负载,我们显示出与传统系统相比性能显着降低的功率预算。

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