Portable profiling and tracing for parallel, scientific applications using C++
Portable profiling and tracing for parallel, scientific applications using C++
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使用 C 的并行科学应用程序的便携式分析和跟踪
DOI：
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
K. Lindlan
中科院分区：
文献类型：
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作者：
S. Shende;A. Malony;J. Cuny;P. Beckman;S. Karmesin;K. Lindlan
1。平行，反对的（00）程序的抽象性能测量需要开发仪器和分析技术，而不是用于更传统的语言事件。 00语言摘要，汇编方法和运行时执行动力学的上下文。已经使用丰富的平行编程框架来进行高度性能，我们解决了基于班级的分析，模板的仪器，运行时函数识别和多态性（基于类型的）分析。软件包还为分析组和用户级计时器提供了支持。未来的方向包括有关运行时性能数据访问，动态仪器的工作以及将对象语义与性能执行行为相关联的高级性能数据分析和可视化。
1. Abstract Performance measurement of parallel, objectoriented (00) programs requires the development of instrumentation and analysis techniques beyond those used for more traditional languages. Performance events must be redefined for the conceptual 00 programming model, and those events must be instrumented and tracked in the context of 00 language abstractions, compilation methods, and runtime execution dynamics. In this paper, we focus on the profiling and tracing of C++ applications that have been written using a rich parallel programming framework for highperformance, scientific computing. We address issues of class-based profiling, instrumentation of templates, runtime function identification, and polymorphic (type-based) profiling. Our solutions are implemented in the TAU portable profiling package which also provides support for profiling groups and userlevel timers. We demonstrate TAU’s C++ profiling capabilities for real parallel applications, built from components of the ACTS toolkit. Future directions include work on runtime performance data access, dynamic instrumentation, and higher-level performance data analysis and visualization that relates object semantics with performance execution behavior.