使用PAPI的数据流应用程序的自动检测

D. Madroñal, Antoine Morvan, R. Lazcano, R. Salvador, K. Desnos, E. J. Martínez, C. Sanz
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引用次数: 10

摘要

从应用程序开发的角度来看,过去几年见证的复杂性与生产力差距的扩大正变得难以承受。新的设计方法试图将大多数设计师的任务自动化,以弥合这一差距。此外,新的基于数据流的计算模型(MoC)简化了应用程序内并行性的表达,从而提高了生产率。快速原型设计工具提供了对设计选择的可靠性的快速评估。创建应用程序原型的关键步骤是使用具有代表性的性能指标来评估设计选择的有效性。这些指标可以通过PAPI (Performance API)获取硬件信息。在这项工作中,PAPI和数据流MoC集成在一个y图设计流程中。该实现采用Preesm工具中专用的自动代码生成方案的形式。初步结果表明,根据应用程序的复杂性,由于监视而产生的计算时间开销从几乎可以忽略到超过50%不等。此外,除了提供准确的硬件性能指标外,还可以将提取的值组合起来估算功率或能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic instrumentation of dataflow applications using PAPI
The widening of the complexity-productivity gap witnessed in the last years is becoming unaffordable from the application development point of view. New design methods try to automate most designers tasks in order to bridge this gap. In addition, new Models of Computation (MoC), as those dataflow-based, ease the expression of parallelism within applications and lead to higher productivity. Rapid prototyping design tools offer fast estimations of the soundness of design choices. A key step when prototyping an application is to have representative performance indicators to estimate the validity of the design choices. Such indicators can be obtained using hardware information through the Performance API (PAPI). In this work, PAPI and a dataflow MoC are integrated within a Y-chart design flow. The implementation takes the form of a dedicated automatic code generation scheme within the Preesm tool. Preliminary results show that depending on the complexity of the application, the computation time overhead due to monitoring varies from being almost negligible to more than 50%. Also, on top of offering accurate hardware performance indicators, the extracted values can be combined to estimate power or energy consumption.
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