Detecting Coarse - Grain Parallelism Using an Interprocedural Parallelizing Compiler

This paper presents an extensive empirical evaluation of an interprocedural parallelizing compiler, developed as part of the Stanford SUIF compiler system. The system incorporates a comprehensive and integrated collection of analyses, including privatization and reduction recognition for both array and scalar variables, and symbolic analysis of array subscripts. The interprocedural analysis framework is designed to provide analysis results nearly as precise as full inlining but without its associated costs. Experimentation with this system shows that it is capable of detecting coarser granularity of parallelism than previously possible. Specically, it can parallelize loops that span numerous procedures and hundreds of lines of codes, frequently requiring modications to array data structures such as privatization and reduction transformations. Measurements from several standard benchmark suites demonstrate that an integrated combination of interprocedural analyses can substantially a...

• Type: Conference
• Year: 1995
• Where: SC
• Authors: Mary W. Hall, Saman P. Amarasinghe, Brian R. Murphy, Shih-Wei Liao, Monica S. Lam
• Keywords: Applied Computing, Extensive Empirical Evaluation, Interprocedural Parallelizing Compiler, SC 1995, Stanford SUIF Compiler