CDAC / The introduction of languages like High Performance Fortran (HPF) which allow the programmer to indicate how the arrays used in the
program have to be distributed across the local memories of a multi-computer has not completely unburdened the parallel programmer from the intricacies of these architectures. In order to tap the full potential of these architectures, the compiler has to perform this crucial task of data partitioning automatically. This would not only
unburden the programmer but would make the programs more efficient since the compiler can be made more intelligent to take care of the
architectural nuances.
The topic of this thesis namely the automatic data partitioning deals with finding the best data partition for the various arrays used in
the entire program in such a way that the cost of execution of the entire program is minimized. The compiler could resort to runtime redistribution of the arrays at various points in the program if found profitable. Several aspects of this problem have been proven to be NP-complete. Other researchers have suggested heuristic solutions to solve this problem. In this thesis we propose a genetic algorithm namely the Hierarchical Genetic Search algorithm to solve this problem.
| Identifer | oai:union.ndltd.org:IISc/oai:etd.ncsi.iisc.ernet.in:2005/172 |
| Date | 09 1900 |
| Creators | Shenoy, U Nagaraj |
| Contributors | Srikant, Y N |
| Publisher | Indian Institute of Science |
| Source Sets | India Institute of Science |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis and Dissertation |
| Format | 1091751 bytes, application/postscript |
| Rights | I grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. |
Page generated in 0.0052 seconds