CSR: Small: Cross-layer HW/SW solutions towards Energy-Efficient Datacenters

促进工作负载整合和提高服务器利用率对于降低成本和提高现代数据中心的能源效率至关重要。提高利用率的一个主要挑战是在不影响服务质量 (QoS) 的情况下实现这一目标。在现代服务器上，各种协同定位的作业可能共享关键资源，包括1）微架构资源，例如末级缓存、内存带宽和功能单元等，以及2）能源资源，包括电网电源和分布式电池，尤其是在高负载期间提供额外的电源。多个共处一地的作业可能会争夺共享这些资源，从而造成干扰，威胁应用程序 QoS，甚至触发断路器，从而导致代价高昂的停机时间和严重的 QoS 违规。该项目通过设计一个跨层系统来解决这些挑战，该系统可有效管理工作负载整合、服务质量 (QoS) 和各种能源，以优化节能计算。我们的系统跨越多个层，包括分析器、静态编译器、在线轻量级监控和预测、运行时执行管理、硬件电源状态控制和能源控制。编译技术可识别低优先级应用程序中的争议代码区域，以及需要 QoS 保护的高优先级应用程序中的关键区域，并将标记插入其中。轻量级运行时利用编译器提示，监控QoS、功耗等，并自适应调整应用程序对共享缓存和内存带宽等共享资源产生的压力，管理电池（dis）充电和硬件电源状态，以保证QoS并实现高效的功耗。

Facilitating workload consolidation and improving server utilization are critical for reducing cost and improving energy-efficiency of modern datacenters. One major challenge for improving utilization is to do so without affecting the quality of service (QoS). On modern servers, various co-located jobs may share critical resources including 1) micro-architectural resources such as last level cache, memory bandwidth, and functional units, etc., and 2) energy resources including grid power and distributed batteries that provide an additional power source especially during high load period. Multiple co-located jobs may contend for shared these resources, causing interference, threatening application QoS or even triggering the circuit breaker and resulting in costly downtime and severe QoS violations.This project addresses these challenges by designing a cross-layer system that effectively manages workload consolidation, quality of service (QoS) and various energy sources to optimize for energy efficient computing. Our system spans several layers, including profiler, static compiler, online lightweight monitoring and prediction, runtime execution management, hardware power state control and energy sources control. The compilation technique identifies and inserts markers in contentious code regions in low-priority applications, as well as critical regions in high-priority applications that require QoS protection. The lightweight runtime utilizes the compiler hints, monitors the QoS, power consumption, etc., and adaptively adjusts the pressure applications generate to the shared resources such as shared cache and memory bandwidth, manages battery (dis) charges and hardware power states to guarantee QoS and achieve efficient power shaving.