Toward Compiler Support for Scalable Parallelism Using Multipartitioning

Authors:
Daniel G. Chavarría-Miranda;John M. Mellor-Crummey
Affiliations:
-;-
Venue:
LCR '00 Selected Papers from the 5th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computers
Year:
2000

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Abstract

Strategies for partitioning an application's data play a fundamental role in determining the range of possible parallelizations that can be performed and ultimately their potential efficiency. This paper describes extensions to the Rice dHPF compiler for High Performance Fortran which enable it to support data distributions based on multipartitioning. Using these distributions can help close the substantial gap between the efficiency and scalability of compiler-parallelized codes for multi-directional line sweep computations and their hand-coded counterparts. We describe our the design and implementation of compiler support for multipartitioning and show preliminary results for a benchmark compiled using these techniques.