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Dynamic Levelwise Scheduling for Sparse Matrix Factorization on Vector Computers by M. Montagna; G.P. Granelli; G.T. Vuong; R. Chahine is a Engineering article available to read on EtoBox.

What is Dynamic Levelwise Scheduling for Sparse Matrix Factorization on Vector Computers about?

In this paper the problem of the efficient implementation of sparse matrix factorization on vector computers is considered. A fine-grain dynamic levelwise scheduling algorithm (DLSA) is proposed. DLSA takes into account the dependences between update operations, thus avoiding the recurrence problem. A simplified version of the algorithm (S-DLSA) can be employed to produce a suboptimal scheduling of the factorization operations. DLSA and S-DLSA are also applicable to all sparse matrix operations resulting in the modification of one-dimensional arrays. The scheduling procedures and the resulting vectorization-oriented numerical factorization have been implemented on a CRAY X-MP2/216 and a CRAY Y-MP8/464 computer. Test cases refer to real-life power systems with up to 12 000 buses. The maximum speed-ups achieved (with respect to a code based on standard sparsity programming) are close to 7 for complex matrices and 13 for real matrices.

Who reads Dynamic Levelwise Scheduling for Sparse Matrix Factorization on Vector Computers?

Author

M. Montagna; G.P. Granelli; G.T. Vuong; R. Chahine

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0378-7796)

Published

1995

Language

EN

Field

Engineering (Physical Sciences)