论文标题
擦除:节能任务映射和用于窃取运行时间的资源管理
ERASE: Energy Efficient Task Mapping and Resource Management for Work Stealing Runtimes
论文作者
论文摘要
并行应用程序通常依赖于窃取工作调度程序,并结合细粒度的任务来实现高性能和可扩展性。但是,在窃取工作时减少总能源消耗仍然具有挑战性,尤其是在使用具有不同类型的CPU内核的不对称体系结构时。节能的一种常见方法涉及动态电压和频率缩放(DVF),其中基于任务并行性,窃取关系和任务关键性等因素进行节流。本文对以下观察进行了以下观察:(i)在使用细粒度的任务和群集/芯片级DVF的环境中,以每任务为基础的DVF是不切实际的; (ii)任务可模拟性,其中一个任务可以通过工作共享在多个线程/核心执行,可以帮助减少能耗; (iii)任务和分配的资源(即核心类型和核心数)之间的不匹配会对能源消耗产生不利影响。在本文中,我们提出了Erase(能源意识调度程序),这是一种在工作窃取运行时的内部应用任务调度程序,旨在减少并行应用的总能源消耗。它通过基于各种资源配置的每项任务消耗预测来指导计划决策来节省能源。此外,ERASE能够适应给定的静态频率设置和外部控制的DVF。总体而言,与最先进的DVFS调度程序相比,ERASE可实现高达31%的能源节省,平均可提高性能44%。
Parallel applications often rely on work stealing schedulers in combination with fine-grained tasking to achieve high performance and scalability. However, reducing the total energy consumption in the context of work stealing runtimes is still challenging, particularly when using asymmetric architectures with different types of CPU cores. A common approach for energy savings involves dynamic voltage and frequency scaling (DVFS) wherein throttling is carried out based on factors like task parallelism, stealing relations and task criticality. This paper makes the following observations: (i) leveraging DVFS on a per-task basis is impractical when using fine-grained tasking and in environments with cluster/chip-level DVFS; (ii) task moldability, wherein a single task can execute on multiple threads/cores via work-sharing, can help to reduce energy consumption; and (iii) mismatch between tasks and assigned resources (i.e.~core type and number of cores) can detrimentally impact energy consumption. In this paper, we propose ERASE (EneRgy Aware SchedulEr), an intra-application task scheduler on top of work stealing runtimes that aims to reduce the total energy consumption of parallel applications. It achieves energy savings by guiding scheduling decisions based on per-task energy consumption predictions of different resource configurations. In addition, ERASE is capable of adapting to both given static frequency settings and externally controlled DVFS. Overall, ERASE achieves up to 31% energy savings and improves performance by 44% on average, compared to the state-of-the-art DVFS-based schedulers.