An evaluation of different modeling techniques for iterative compilation
Eunjung Park, Sameer G. Kulkarni, John Cavazos · 2011
Iterative compilation techniques, which involve iterating over different sets of optimizations, have proven useful in helping compilers choose the right set of optimizations for a given program. However, compilers typically have a large number of optimizations to choose from, making it impossible to iterate over a significant fraction of the entire optimization search space. Recent research has proposed to "intelligently" iterate over the optimization search space using predictive methods. In particular, state-the-art methods in iterative compilation use characteristics of the code being optimized to predict good optimization sequences to evaluate. Thus, an important step in developing predictive methods for compilation is deciding how to model the problem of choosing the right optimizations.