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Author ORCID Identifier
Open Access Dissertation
Doctor of Philosophy (PhD)
Year Degree Awarded
Month Degree Awarded
Programming Languages and Compilers
It is well-known that programs tend to have multiple phases in their execution. Because phases have impact on micro-architectural features such as caches and branch predictors, they are relevant to program performance (Xian et al., 2007; Roh et al., 2009; Gu and Verbrugge, 2008) and energy consumption. They are also relevant to detecting whether a program is executing as expected or is encountering unusual or exceptional conditions, a software engineering and program monitoring concern (Peleg and Mendelson, 2007; Singer and Kirkham, 2008; Pirzadeh et al., 2011; Benomar et al., 2014).
We present methods for real-time phase change detection and phase prediction in Java, C, (etc.,) and Python programs. After applying a training protocol to a program of interest, our methods can detect and predict phase at run time for that program with good precision and recall (compared with a “ground truth” definition of phases) and with small performance impact. Furthermore, for concrete applications, we explore run-time energy-efficient clock frequency adjustment for statically compiled executables.
Chiu, Meng-Chieh, "RUN-TIME PROGRAM PHASE DETECTION AND PREDICTION" (2018). Doctoral Dissertations. 1332.