E-Mapper: Energy-Efficient Resource Allocation for Traditional Operating Systems on Heterogeneous Processors

Till Smejkal, Robert Khasanov, Jeronimo Castrillon, Hermann Härtig
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Abstract

Energy efficiency has become a key concern in modern computing. Major processor vendors now offer heterogeneous architectures that combine powerful cores with energy-efficient ones, such as Intel P/E systems, Apple M1 chips, and Samsungs Exyno's CPUs. However, apart from simple cost-based thread allocation strategies, today's OS schedulers do not fully exploit these systems' potential for adaptive energy-efficient computing. This is, in part, due to missing application-level interfaces to pass information about task-level energy consumption and application-level elasticity. This paper presents E-Mapper, a novel resource management approach integrated into Linux for improved execution on heterogeneous processors. In E-Mapper, we base resource allocation decisions on high-level application descriptions that user can attach to programs or that the system can learn automatically at runtime. Our approach supports various programming models including OpenMP, Intel TBB, and TensorFlow. Crucially, E-Mapper leverages this information to extend beyond existing thread-to-core allocation strategies by actively managing application configurations through a novel uniform application-resource manager interface. By doing so, E-Mapper achieves substantial enhancements in both performance and energy efficiency, particularly in multi-application scenarios. On an Intel Raptor Lake and an Arm big.LITTLE system, E-Mapper reduces the application execution on average by 20 % with an average reduction in energy consumption of 34 %. We argue that our solution marks a crucial step toward creating a generic approach for sustainable and efficient computing across different processor architectures.
E-Mapper:在异构处理器上为传统操作系统分配高能效资源
能效已成为现代计算的关键问题。目前,主要的处理器供应商都提供了将功能强大的内核与高能效内核相结合的异构架构,如英特尔 P/E 系统、苹果 M1 芯片和三星 Exyno CPU。然而,除了简单的基于成本的线程分配策略外,当今的操作系统调度程序并没有充分利用这些系统在自适应节能计算方面的潜力。部分原因在于缺少应用级接口来传递任务级能耗和应用级弹性的信息。本文介绍的 E-Mapper 是一种集成到 Linux 中的新型资源管理方法,用于改进异构处理器上的执行。在 E-Mapper 中,我们将资源分配决策建立在高级应用描述的基础上,用户可以将高级应用描述附加到程序中,系统也可以在运行时自动学习高级应用描述。最重要的是,E-Mapper 利用这些信息,通过新颖的统一应用资源管理器接口主动管理应用程序配置,从而超越了现有的线程到内核分配策略。在英特尔Raptor Lake和Arm big.LITTLE系统上,E-Mapper平均减少了20%的应用执行量,平均减少了34%的能耗。我们认为,我们的解决方案标志着在不同处理器体系结构上创建可持续高效计算通用方法的关键一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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