Performance Analysis of Instruction Priority Functions using a List Scheduling Simulator

Changhoon Chung, Soo-Mook Moon

http://doi.org/10.5626/JOK.2023.50.12.1048

Instruction scheduling is an important compiler optimization technique, for reducing the execution time of a program by parallel processing. However, existing scheduling techniques show limited performance, because they rely on heuristics. This study examines the effect of instruction priority functions on list scheduling, through simulation. As a result, using a priority function based on the overall structure of the dependency graph can reduce schedule length by up to 4%, compared to using a priority function based on the original instruction order. Furthermore, the result gives a direction on which input features should be used when implementing a reinforcement learning-based scheduling model.