Run-time parallelization: A framework for parallel computation

The goal of parallelizing, or restructuring, compilers is to detect and exploit parallelism in sequential programs written in conventional languages. Current parallelizing compilers do a reasonable job of extracting parallelism from programs with regular, statically analyzable access patterns. However, if the memory access pattern of the program is input data dependent, then static data dependence analysis and consequently parallelization is impossible. Moreover, in this case the compiler cannot apply privatization and reduction parallelization, the transformations that have been proven to be the most effective in removing data dependences and increasing the amount of exploitable parallelism in the program. Typical examples of irregular, dynamic applications are complex simulations such as SPICE for circuit simulation, DYNA-3D for structural mechanics modeling, DMOL for quantum mechanical simulation of molecules, and CHARMM for molecular dynamics simulation of organic systems. Therefore, since irregular programs represent a large and important fraction of applications, an automatable framework for run-time parallelization is needed to complement existing and future static compiler techniques.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Rauchwerger, Lawrence

Contributors dc:contributor

• Padua, David A.

• Computer Science

Statement dc:rights

• Copyright 1995 Rauchwerger, Lawrence

Language dc:language

eng

Identifier

AAI9624468
(UMI)AAI9624468

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/23071