模调度中的数据猜测方法

软件流水是一种重要的指令调度技术，通过重叠地执行不同的循环体来提高指令级并行性。模调度是一类重要的软件流水调度算法，保守的相关性分析可能会引入较多的模糊相关，这阻碍了模调度生成高效的调度结果。数据猜测能克服保守的相关性分析带来的调度限制，开发潜在的并行性。本文提出了模调度中的一种数据猜测方法，在开放源代码编译器ORC上实现了该方法，并用SPEC2000基准程序进行了测试，实验结果表明，该方法收到了较好的效果。

A DATA SPECULATION APPROACH IN MODULO SCHEDULING

Software pipelining is an important scheduling technique which exploits instruction level parallelism by overlapping several consecutive iterations. Modulo scheduling is a state-of-art scheme in the literature of software pipelining. Conservative alias analysis may introduce many non-definite dependencies, which prevents modulo scheduling from finding a more efficient scheduling result. Data speculation can be applied to ignore those constraints and exploit potential parallelism. This paper proposes a data speculation approach in modulo scheduling. We implement the approach in ORC and test it on SPEC2000 benchmarks. Experimental results show that the approach boosts performance effectively.