The Phase-Ordering Problem: An Intermediate Speedup Prediction Approach

Abstract

This chapter presents the first of two methods to tackle the phase-ordering problem of compiler optimizations. Here, we present an intermediate speedup prediction approach followed by a full-sequence prediction approach in the next chapter and we show pros and cons of each approach in detail. Today’s compilers offer a vast number of transformation options to choose among, and this choice can significantly impact on the performance of the code being optimized. Not only the selection of compiler options represents a hard problem to be solved, but also the ordering of the phases is adding further complexity, making it a long-standing problem in compilation research. This chapter presents an innovative approach to tackling the compiler phase-ordering problem by using predictive modeling. The proposed methodology enables (i) to efficiently explore compiler exploration space including optimization permutations and repetitions and (ii) to extract the application dynamic features to predict the next-best optimization to be applied to maximize the performance given the current status. Experimental results are done by assessing the proposed methodology with utilizing two different search heuristics on the compiler optimization space and it demonstrates the effectiveness of the methodology on the selected set of applications. Using the proposed methodology on average we observed up to 4% execution speedup with respect to LLVM standard baseline.