数据并行程序的集成编译和性能分析环境

Vikram S. Adve, J. Mellor-Crummey, Mark Anderson, K. Kennedy, Jhy-Chun Wang, D. Reed
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引用次数: 136

摘要

支持用数据并行语言编写的程序的源代码级性能分析需要编译器和性能分析工具之间的独特集成程度。诸如高性能Fortran等语言的编译器从数据分布指令中推断并行性和通信,因此,如果没有大量编译器的支持,性能工具无法将执行性能的这些关键方面的测量与源代码级结构有意义地联系起来。本文介绍了一个基于Rice Fortran 77D编译器和Illinois Pablo性能分析工具包的数据并行程序性能分析集成系统。在代码生成过程中,Fortran D编译器记录映射信息和描述性能检测与原始源程序之间关系的语义分析结果。基于Pablo工具包的集成性能分析系统使用这些信息将程序的动态行为与数据并行源代码关联起来。集成系统通过一对图形界面向程序员提供详细的源代码级性能反馈。我们的策略可以作为数据并行编译器和性能工具集成的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Integrated Compilation and Performance Analysis Environment for Data Parallel Programs
Supporting source-level performance analysis of programs written in data-parallel languages requires a unique degree of integration between compilers and performance analysis tools. Compilers for languages such as High Performance Fortran infer parallelism and communication from data distribution directives, thus, performance tools cannot meaningfully relate measurements about these key aspects of execution performance to source-level constructs without substantial compiler support. This paper describes an integrated system for performance analysis of data-parallel programs based on the Rice Fortran 77D compiler and the Illinois Pablo performance analysis toolkit. During code generation, the Fortran D compiler records mapping information and semantic analysis results describing the relationship between performance instrumentation and the original source program. An integrated performance analysis system based on the Pablo toolkit uses this information to correlate the program's dynamic behavior with the data parallel source code. The integrated system provides detailed source-level performance feedback to programmers via a pair of graphical interfaces. Our strategy serves as a model for integration of data-parallel compilers and performance tools.
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