Widely used compilers like GCC usually have hundreds of optimizations controlled by optimization flags, which can be enabled or disabled during compilation to improve the runtime performance of a compiled program. Due to the large number of optimization flags and their combination, it is difficult for compiler users to tune compiler optimization flags manually. In the literature, many auto-tuning techniques have been proposed, which find a desired setting on all optimization flags (i.e., an optimization sequence) by designing different search strategies in the entire optimization space. Due to the huge search space, these techniques suffer from the widely-recognized efficiency problem. To reduce the search space, in this paper, we propose a critical-flag selection based approach CFSCA which first finds flags potentially relevant to the target program by analyzing program structure and compiler documentation, and then identifies critical flags through statistical analysis on the program's predicted runtime performance with various optimization sequences. With the reduced search space, CFSCA selects a desired optimization sequence. To evaluate the performance of the proposed approach CFSCA, we conduct an extensive experimental study on the latest version of the compiler GCC with a widely used benchmark cBench. The experimental results show that CFSCA significantly outperforms the four compared techniques, including the state-of-art technique BOCA.

@inproceedings{ZhuH23,
  title = {Compiler Auto-Tuning via Critical Flag Selection},
  author = {Mingxuan Zhu and Dan Hao},
  booktitle = {ASE},
  year = {2023},
  doi = {10.1109/ase56229.2023.00209}
}