Software pipelining loops with conditional branches

Abstract

Software pipelining is an aggressive scheduling technique that generates efficient code for loops and is particularly effective for VLIW architectures. Few software pipelining algorithms, however, are able to efficiently schedule loops that contain conditional branches. We have developed an algorithm we call All Paths Pipelining (APP) that addresses this shortcoming of software pipelining. APP is designed to achieve optimal or near-optimal performance for any run of iterations while providing efficient code for transitioning between runs. A run is the execution of consecutive iterations that all execute the same path through a loop. APP accomplishes this by using techniques from modulo scheduling and kernel recognition algorithms, the two main approaches for software pipelining loops. We have implemented the APP algorithm in our research compiler and have evaluated its performance by executing its generated code on a VLIW instruction-set simulator. For a processor with five heterogeneous functional units, APP is able to add another 1% to 23% increase in performance over basic software pipelining by effectively pipelining loops with conditional branches.