Integrating Performance Analysis in Parallel Software Engineering
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Modern computational software is increasingly large in terms of lines of code, number of developers, intended longevity, and complexity of intended architectures. While tools exist to mitigate the problems this type of software causes for the development of functional software, no solutions exist to deal with the problems it causes for performance. This thesis introduces a design called the Software Development Performance Analysis System, or SDPAS. SDPAS observes the performance of software tests as software is developed, tracking builds, tests, and developers in order to provide data with which to analyze a software development process. SDPAS integrates with the CMake build and test suite to obtain data about builds and provide consistent tests, with git to obtain data about how software is changing. SDPAS also integrates with TAU to obtain performance data and store it along with the data obtained from other tools. The utility of SDPAS is observed on two pieces of production software.