扩展运行时资源管理框架以支持OpenCL和异构系统

G. Massari, Chiara Caffarri, P. Bellasi, W. Fornaciari
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引用次数: 9

摘要

从移动到高性能计算(HPC)系统,性能和能源效率的要求越来越具有挑战性。在这方面,由通用处理器和一个或多个硬件加速器组成的异构系统正在成为负担得起的解决方案。然而,有效地利用这些平台需要特定的编程语言(例如OpenCL)和合适的运行时软件层。这项工作说明了运行时资源管理(RTRM)框架的扩展,以支持在具有多核CPU和多gpu的系统上执行OpenCL应用程序。早期的结果显示了该解决方案如何为应用程序(就性能而言)和系统(就资源利用而言)带来好处,即计算设备上的负载平衡和热均衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending a Run-time Resource Management framework to support OpenCL and Heterogeneous Systems
From Mobile to High-Performance Computing (HPC) systems, performance and energy efficiency are becoming always more challenging requirements. In this regard, heterogeneous systems, made by a general-purpose processor and one or more hardware accelerators, are emerging as affordable solutions. However, the effective exploitation of such platforms requires specific programming languages, like for instance OpenCL, and suitable run-time software layers. This work illustrates the extension of a run-time resource management (RTRM) framework, to support the execution of OpenCL applications on systems featuring a multi-core CPU and multiple GPUs. Early results show how this solution leads to benefits both for the applications, in terms of performance, and for the system, in terms of resource utilization, i.e. load balancing and thermal leveling over the computing devices.
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