Load-store optimization for software pipelining

Abstract

Software pipelining can generate efficient schedules for loop by overlapping the execution of operations from different iterations in order to exploit maximum Instruction Level Parallelism (ILP). Code optimization can decrease total number of calculations and memory related operations. As a result, instruction schedules can use freed resources to construct shorter schedules. Particularly, when the data is not presented in cache, the performance will be significantly degraded by memory references. Therefore, elimination of redundant load-store operations is most important for improving overall performance. This paper introduces a method for integrating software pipelining and load-store elimination techniques. Moreover, we demonstrate that integrated algorithm is more effective than other methods.