Exponentially Expanding the Phase-Ordering Search Space via Dormant Information
Ruobing Han, Hyesoon Kim · 2024
Applying compilation transformations in optimal sequences can significantly improve program speed and reduce code size. However, finding these optimal sequences—a problem known as the phase-ordering problem—remains a long-standing challenge. Specifically, modern compilers offer hundreds of available transformations, making the search space too large to explore efficiently within a reasonable timeframe. Existing solutions address this problem by grouping transformations into short sequences based on prior knowledge from human experts, and then searching for optimal orders among these sequences. Such pruning methods are aggressive, potentially excluding optimal solutions from the search space. Additionally, they rely on prior knowledge and lack scalability when applied to new transformations.