Reducing the energy expended to carry out a computational task is important. In this work, we explore the prospects of meeting Quality-of-Service requirements of tasks on a multi-core system while adjusting resources to expend a minimum of energy. This paper considers, for the first time, a QoS-driven coordinated resource management algorithm (RMA) that dynamically adjusts the size of the per-core last-level cache partitions and the per-core voltage–frequency settings to save energy while respecting QoS requirements of every application in multi-programmed workloads run on multi-core systems. It does so by doing configuration-space exploration across the spectrum of LLC partition sizes and Dynamic Voltage–Frequency Scaling (DVFS) settings at runtime at negligible overhead. We show that the energy of 4-core and 8-core systems can be reduced by up to 18% and 14%, respectively, compared to a baseline with even distribution of cache resources and a fixed mid-range core voltage–frequency setting. The energy savings can potentially reach 29% if the QoS targets are relaxed to 40% longer execution time.

减少用于执行计算任务的能量很重要。在这项工作中，我们将探索在多核系统上满足任务的服务质量要求，同时调整资源以消耗最少能量的前景。本文首次考虑了QoS驱动的协调资源管理算法（RMA）可动态调整每个核的最后一级缓存分区的大小和每个核的电压频率设置，以节省能源，同时在多核运行的多程序工作负载中遵守每个应用程序的QoS要求系统。它通过在运行时以可忽略的开销跨LLC分区大小和动态电压频率缩放（DVFS）设置范围进行配置空间探索来实现。我们显示，与具有均匀分布的缓存资源和固定的中端核心电压频率设置的基准相比，与基准相比，四核和八核系统的能源最多可降低18％和14％。如果将QoS目标放宽到40％的执行时间，则节能量可能达到29％。