PEPPHER组合工具:基于gpu系统的应用程序的性能感知动态组合

Usman Dastgeer, Lu Li, C. Kessler
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引用次数: 20

摘要

PEPPHER组件模型为同质和异构多核和多核系统(包括GPU和基于多GPU的系统)定义了一个注释本地基于C/ c++的组件的环境。对于作为组件捕获的相同计算功能,可能会提供使用各种类型的执行单元的不同顺序和显式并行实现变体,以及显式公开的可调参数等元数据。目标是由组件和变体组成应用程序,以便根据运行时上下文自动为每个调用选择最合适的实现变体。我们描述和评估PEPPHER组合工具,它探索应用程序的组件及其实现变体,生成与运行时系统交互的必要的低级代码,并协调各种代码单元的本地编译和链接,以组成整个应用程序代码。通过几个应用程序,我们演示了组合工具如何提供高级编程前端,同时有效地利用底层基于任务的PEPPHER运行时系统(StarPU)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The PEPPHER Composition Tool: Performance-Aware Dynamic Composition of Applications for GPU-Based Systems
The PEPPHER component model defines an environment for annotation of native C/C++ based components for homogeneous and heterogeneous multicore and manycore systems, including GPU and multi-GPU based systems. For the same computational functionality, captured as a component, different sequential and explicitly parallel implementation variants using various types of execution units might be provided, together with metadata such as explicitly exposed tunable parameters. The goal is to compose an application from its components and variants such that, depending on the run-time context, the most suitable implementation variant will be chosen automatically for each invocation. We describe and evaluate the PEPPHER composition tool, which explores the application's components and their implementation variants, generates the necessary low-level code that interacts with the runtime system, and coordinates the native compilation and linking of the various code units to compose the overall application code. With several applications, we demonstrate how the composition tool provides a high-level programming front-end while effectively utilizing the task-based PEPPHER runtime system (StarPU) underneath.
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