Efficient compiler optimization by modeling passes dependence
Jianfeng Liu, Jianbin Fang, Ting Wang, Jing Xie, Chun Huang, Zheng Wang · CCF Transactions on High Performance Computing · 2024
Abstract Selecting the optimal combination of compiler passes is a significant challenge to enhance performance and reduce the code size of compiled binaries. While a well-selected sequence of compiler passes can yield considerable benefits, the large number of potential combinations and the scarcity of effective ones make this task prohibitively complex. To tackle this problem, we propose a novel approach to group compiler passes into a small set of sub-sequences. This approach translates the task of identifying the right compiler passes combination into determining the appropriate combination of these sub-sequences. We apply our approach to CBench and PolyBench, demonstrating remarkable performance improvements. Our approach enhances runtime performance by 22% compared to the default LLVM ‘O3’ option, and achieves a code size reduction of 24% compared to the ‘Oz’ option. Our approach also outperforms state-of-the-art across various optimization tasks and hardware platforms.