HomeresearchPeopleGeneral InfoSeminarsResources
Abstract

Hao Yu, Lawrence Rauchwerger, "Run-time Parallelization Optimization Techniques," In Wkshp. on Lang. and Comp. for Par. Comp. (LCPC), San Diego, CA, Aug 1999.
Proceedings(ps, pdf, abstract)

In this paper we first present several compiler techniques to reduce the overhead of run-time parallelization. We show how to use static control flow information to reduce the number of memory references that need to be traced at run-time. Then we introduce several methods designed specifically for the parallelization of sparse applications. We detail some heuristics on how to speculate on the type and data structures used by the original code and thus reduce the memory requirements for tracing the sparse access patterns without performing any additional work. Optimization techniques for the sparse reduction paralleization and speculative loop distribution conclude the paper.