Abstract
Multipartitioning is a skewed-cyclic block distribution that yields better parallel efficiency and scalability for line-sweep computations than traditional block partitionings. This paper describes extensions to the Rice dHPF compiler for High Performance Fortran that enable it to support multipartitioned data distributions and optimizations that enable dHPF to generate efficient multipartitioned code. We describe experiments applying these techniques to parallelize serial versions of the NAS SP and BT application benchmarks and show that the performance of the code generated by dHPF is approaching that of hand-coded parallelizations based on multipartitioning.
This work has been supported in part by NASA Grant NAG 2-1181, DARPA agreement number F30602-96-1-0159, and the Los Alamos National Laboratory Computer Science Institute (LACSI) through LANL contract number 03891-99-23, as part of the prime contract (W-7405-ENG-36) between the Department of Energy and the Regents of the University of California. The U.S. Government is authorized to reproduce and distribute reprints for Governmentalpurp oses notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as representing the official policies or endorsements, either expressed or implied of sponsoring agencies.
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ChavarrÃa-Miranda, D., Mellor-Crummey, J., Sarang, T. (2001). Data-Parallel Compiler Support for Multipartitioning. In: Sakellariou, R., Gurd, J., Freeman, L., Keane, J. (eds) Euro-Par 2001 Parallel Processing. Euro-Par 2001. Lecture Notes in Computer Science, vol 2150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44681-8_36
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DOI: https://doi.org/10.1007/3-540-44681-8_36
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