SC12 Home > SC12 Schedule > SC12 Presentation - Automatic Selection of Compiler Optimizations Using Program Characterization and Machine Learning

SCHEDULE: NOV 10-16, 2012

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Automatic Selection of Compiler Optimizations Using Program Characterization and Machine Learning

SESSION: Doctoral Showcase - Dissertation Research Showcase

EVENT TYPE: Doctoral Showcase

TIME: 1:30PM - 1:45PM


Presenter(s):Eunjung Park


Selecting suitable optimizations for a particular class of applications is difficult because of the complex interactions between the optimizations themselves and the involved hardware. It has been shown that machine-learning based driven optimizations often outperform bundled optimizations or human-constructed heuristics. In this dissertation, we propose to use different modeling techniques and characterizations to solve the current issues in machine-learning based selection of compiler optimizations. In the first part, we evaluate two different state-of-the-art predictive modeling techniques against a new modeling technique we invented, named the tournament predictor. We show that this novel technique can outperform the other two state-of-the-art techniques. In the second, we evaluate three different program characterization techniques including performance counters, reactions, and source code features. We also propose a novel technique using control flow graphs (CFG), which we named graph-based characterization. In the last part, we explored different graph-based IRs other than CFGs to characterize programs.

Chair/Presenter Details:

Yong Chen (Chair) - Texas Tech University

Eunjung Park - University of Delaware

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