为HPC应用程序设计操作系统:调度

R. Gioiosa, S. Mckee, M. Valero
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引用次数: 24

摘要

操作系统历来被实现为硬件和应用程序之间的独立层。用户程序通过一组定义良好的系统调用与操作系统通信,并且不能直接访问硬件。反过来,操作系统通过控制寄存器与底层体系结构通信。除了这些接口之外,这三层实际上是相互忽略的。虽然这种结构提高了可移植性和透明性,但它可能无法提供最佳性能。对于高性能计算(HPC)系统尤其如此,其中现代并行应用程序和多核架构在性能、功耗和系统利用率方面提出了新的挑战。硬件、操作系统和应用程序不能再保持隔离,而应该相互协作,以最小的功耗提供高性能。在本文中,我们介绍了我们设计和实现高性能Linux (HPL)的经验,HPL是一种旨在优化运行在最先进的计算集群上的高性能pc应用程序的性能的操作系统。我们将展示如何通过硬件和软件性能计数器来描述并行应用程序的特征,从而驱动操作系统的设计,以及如何包含有关体系结构的知识来提高性能和效率。我们在一台双插槽IBM POWER6机器上进行了实验,显示了NAS(一种广泛使用的并行基准套件)的性能改进和稳定性(性能变化平均为2.11%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing OS for HPC Applications: Scheduling
Operating systems have historically been implemented as independent layers between hardware and applications. User programs communicate with the OS through a set of well defined system calls, and do not have direct access to the hardware. The OS, in turn, communicates with the underlying architecture via control registers. Except for these interfaces, the three layers are practically oblivious to each other. While this structure improves portability and transparency, it may not deliver optimal performance. This is especially true for High Performance Computing (HPC) systems, where modern parallel applications and multi-core architectures pose new challenges in terms of performance, power consumption, and system utilization. The hardware, the OS, and the applications can no longer remain isolated, and instead should cooperate to deliver high performance with minimal power consumption. In this paper we present our experience with the design and implementation of High Performance Linux (HPL), an operating system designed to optimize the performance of HPC applications running on a state-of-the-art compute cluster. We show how characterizing parallel applications through hardware and software performance counters drives the design of the OS and how including knowledge about the architecture improves performance and efficiency. We perform experiments on a dual-socket IBM POWER6 machine, showing performance improvements and stability (performance variation of 2.11% on average) for NAS, a widely used parallel benchmark suite.
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