Interprocedural Analysis for Parallelization
Mary W. Hall,
Brian R. Murphy, Saman P. Amarasinghe,
Shih-Wei Liao, Monica S. Lam
This research was supported in part by DARPA contracts
N00039-91-C-0138 and DABT63-91-K-0003, the NASA HPCC program,
an NSF Young Investigator Award, an NSF CISE postdoctoral fellowship,
a fellowship from Intel Corporation, and a fellowship from
AT&T Bell Laboratories.
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 on programs from standard
benchmark suites demonstrate that an integrated combination of
interprocedural analyses can substantially advance the capability of
automatic parallelization technology.
Mon Oct 2 11:00:22 PDT 1995