Compile and Run-Time Support for the Parallelization of Sparse Matrix Updating Algorithms
The Journal of Supercomputing
A Compressed Diagonals Remapping Technique for Dynamic Data Redistribution on Banded Sparse Matrix
The Journal of Supercomputing
Sparse Matrix Block-Cyclic Realignment on Distributed Memory Machines
The Journal of Supercomputing
Scheduling contention-free irregular redistributions in parallelizing compilers
The Journal of Supercomputing
A compressed diagonals remapping technique for dynamic data redistribution on banded sparse matrix
ISPA'03 Proceedings of the 2003 international conference on Parallel and distributed processing and applications
Optimizing scheduling stability for runtime data alignment
EUC'06 Proceedings of the 2006 international conference on Emerging Directions in Embedded and Ubiquitous Computing
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
Irregular redistribution scheduling by partitioning messages
ACSAC'05 Proceedings of the 10th Asia-Pacific conference on Advances in Computer Systems Architecture
On the complexity of the max-edge-coloring problem with its variants
ESCAPE'07 Proceedings of the First international conference on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies
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Run-time support for the CYCLIC(k) redistribution on the SPMD computation model is presently very relevant for the scientific community. This work is focused to the characterization of the sparse matrix redistribution and its associate problematic due to the use of compressed representations. Two main improvements about the buffering and the coordinates calculation modify the original algorithm.Our solutions contain a Collecting, a Communication and Mixing stage with different influence in the execution time depending on the sparsity of the matrix and the number of processors. Experimental results have been carried out on a Cray T3E for real matrices and different redistribution parameters.