面向多面体模型的非规则程序SIMD投机优化技术

多面体模型具有规范化、健壮性、灵活性等特点，被认为是最有前途的编译优化技术之一，SIMD优化是重要应用领域之一。由于静态编译技术的限制，大量非规则循环无法建立多面体模型，例如复杂依赖关系，导致无法利用该模型实现SIMD循环优化与代码生成。文章通过分析、利用SIMD优化所需的程序运行剖面信息，将静态编译未知情况转化为已知情况，为多面体模型建立创造条件。SPEC2000和PolyBench的测试结果显示，通过本文提出的方法，可将适用多面体模型的非规则循环个数提高2．3倍，经过SIMD优化后，平均加速比提高了1．53倍。

SIMD Speculative Optimization for Irregular Program Based on Polyhedral Framework

Polyhedral models have characteristics of normalization, robustness and flexibility, but the limitations of static compilation technology make most of irregular loops fail to model polyhedral framework because of aliasing, non-affine expressions, etc. To eliminate these limitations this paper applies the knowledge of the running profile information which is needed by SIMD Optimization . Evaluation on the SPEC2000 and PolyBench shows that the method is able to effectively increase the number of irregular loop which is amenable to polyhedral model by 2.3-fold, and average speed-up by 1.53-fold.