Characterizing Dominant Program Behavior Using the Execution-Time Variance of the Call Structure

Traditional profiling techniques typically identify performance hot-spots. Other specialized techniques such as WCET analysis cater to safety critical real-time systems with hard constraints and thus make conservative assumptions. However, several domains motivate the need to systematically characterize and represent differential timing properties such as the variance in execution time of application artifacts such as the functions. Such domains include, vulnerability analysis of applications with regard to differential timing attacks, and the optimization of soft-real-time applications to reduce frame-rate fluctuations. In this paper, we motivate the need for execution variance as a performance measure and propose a variance-based analysis scheme. We introduce a new program representation called Variance Characterization Graph (VCG) that is used both as the intermediate representation for the variance-based analysis, and as the final representation that provides concise actionable information to programmers and optimization frameworks. We develop a methodology based on statistical pattern matching to summarize the dominant patterns of application behavior into a very compact VCG representation useful for tuning application behavior such as the soft-real-time properties.