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摘要

本文描述了一个案例研究,其中修改了业务应用程序的软件体系结构以提高运行时性能。只要应用程序用户遇到响应缓慢、维护周期长或处理量需求发生变化的已知区域,就应该执行此类修改。对于这个特殊的研究,设计了一个源代码插插框架,以提供便利性、数据粒度和改进的控制,以分析运行时间、操作系统事件和CPU计数器。该研究证实,正确选择算法和数据结构对于实现最佳性能至关重要。此外,对已知的优化方法进行总结后,可以作为确定热点后调优的路线图。完成后,该优化项目对典型数据集的加速系数为18。
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A case study in optimization
This paper describes a case study in which the software architecture of a business application was modified to improve runtime performance. Such modifications should be performed whenever application users encounter known areas of sluggish response, long periods of maintenance, or a change in processing volume requirements. For this particular study, a framework for source code instrumentation was designed to provide convenience, data granularity, and improved control for profiling of elapsed time, operating system events, and CPU counters. The study confirms that proper selection of algorithms and data structures is essential for peak performance. Furthermore, known optimization methods, when summarized, can be used as a roadmap for tuning once hotspots are identified. Upon completion, this optimization project resulted in a speed-up factor of 18 for a typical data set.
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