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2010 IEEE 12th International Conference on High Performance Computing and Communications
Effortless and Efficient Distributed Data-Partitioning in Linear Algebra
Melbourne, Australia
September 01-September 03
ISBN: 978-0-7695-4214-0
| ASCII Text | x | ||
| Carlos de Blas Cartón, Arturo Gonzalez-Escribano, Diego R. Llanos, "Effortless and Efficient Distributed Data-Partitioning in Linear Algebra," High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on, pp. 89-97, 2010 IEEE 12th International Conference on High Performance Computing and Communications, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/HPCC.2010.37, author = {Carlos de Blas Cartón and Arturo Gonzalez-Escribano and Diego R. Llanos}, title = {Effortless and Efficient Distributed Data-Partitioning in Linear Algebra}, journal ={High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on}, volume = {0}, year = {2010}, isbn = {978-0-7695-4214-0}, pages = {89-97}, doi = {http://doi.ieeecomputersociety.org/10.1109/HPCC.2010.37}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on TI - Effortless and Efficient Distributed Data-Partitioning in Linear Algebra SN - 978-0-7695-4214-0 SP89 EP97 A1 - Carlos de Blas Cartón, A1 - Arturo Gonzalez-Escribano, A1 - Diego R. Llanos, PY - 2010 KW - Automatic data partition KW - layouts KW - distributed systems VL - 0 JA - High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HPCC.2010.37
This paper introduces a new technique to exploit compositions of different data-layout techniques with Hit map, a library for hierarchical-tiling and automatic mapping of arrays. We show how Hit map is used to implement block-cyclic layouts for a parallel LU decomposition algorithm. The paper compares the well-known ScaLAPACK implementation of LU, as well as other carefully optimized MPI versions, with a Hit map implementation. The comparison is made in terms of both performance and code length. Our results show that the Hit map version outperforms the ScaLAPACK implementation and is almost as efficient as our best manual MPI implementation. The insertion of this composition technique in the automatic data-layouts of Hit map allows the programmer to develop parallel programs with both a significant reduction of the development effort and a negligible loss of efficiency.
Index Terms:
Automatic data partition, layouts, distributed systems
Citation:
Carlos de Blas Cartón, Arturo Gonzalez-Escribano, Diego R. Llanos, "Effortless and Efficient Distributed Data-Partitioning in Linear Algebra," hpcc-icess, pp.89-97, 2010 IEEE 12th International Conference on High Performance Computing and Communications, 2010
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