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Automatic performance debugging of parallel applications includes two main steps: locating performance bottlenecks and uncovering their root causes for performance optimization. Previous work fails to resolve this challenging issue in two ways: first, several previous efforts automate locating bottlenecks, but present results in a confined way that only identifies performance problems with apriori knowledge; second, several tools take exploratory or confirmatory data analysis to automatically discover relevant performance data relationships, but these efforts do not focus on locating performance bottlenecks or uncovering their root causes. The Simple Program and Multiple Data (SPMD) programming model is widely used for both high performance computing and Cloud computing.
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