About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Paper
Parallelizing Nonnumerical Code with Selective Scheduling and Software Pipelining
Abstract
Instruction-level parallelism (ILP) in nonnumerical code is regarded as scarce and hard to exploit due to its irregularity. In this article, we introduce a new code-scheduling technique for irregular ILP called "selective scheduling" which can be used as a component for superscalar and VLIW compilers. Selective scheduling can compute a wide set of independent operations across all execution paths based on renaming and forward-substitution and can compute available operations across loop iterations if combined with software pipelining. This scheduling approach has better heuristics for determining the usefulness of moving one operation versus moving another and can successfully find useful code motions without resorting to branch profiling. The compile-time overhead of selective scheduling is low due to its incremental computation technique and its controlled code duplication. We parallelized the SPEC integer benchmarks and five AIX utilities without using branch probabilities. The experiments indicate that a fivefold speedup is achievable on realistic resources with a reasonable overhead in compilation time and code expansion and that a solid speedup increase is also obtainable on machines with fewer resources. These results improve previously known characteristics of irregular ILP.