Redundancy elimination is a key optimization direction, and loop nests are the main optimization target in modern compilers. Previous work on redundancy elimination of array computations in loop nests lacks universality. These approaches either focus on specific computation patterns or fail to recognize redundancies with complex structures. This paper proposes RACE (Redundant Array Computation Elimination), a more general redundancy elimination technique. RACE utilizes a novel two-level scheme to identify the data reuse between array references and the computation redundancies between expressions. It traverses the expression trees in loop nests to detect redundancies hierarchically in linear time and generates efficient code with optimized auxiliary arrays that store redundant computation results. Furthermore, RACE supports the expression reassociation with various aggressive strategies to improve the redundancy opportunities. Experimental results demonstrate the effectiveness of RACE.
@article{arxiv.2506.21960,
title = {Redundant Array Computation Elimination},
author = {Zixuan Wang and Liang Yuan and Xianmeng Jiang and Kun Li and Junmin Xiao and Yunquan Zhang},
journal= {arXiv preprint arXiv:2506.21960},
year = {2025}
}