ALGORITHMS FOR EFFICIENT VECTORIZATION OF REPEATED SPARSE POWER-SYSTEM NETWORK COMPUTATIONS

Date

1995-02-01

Author

AYKANAT, C
OZGU, O
Güven, Ali Nezih

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Standard sparsity-based algorithms used in power system applications need to be restructured for efficient vectorization due to the extremely short vectors processed, Further, intrinsic architectural features of vector computers such as chaining and sectioning should also be exploited for utmost performance, This paper presents novel data storage schemes and vectorization algorithms that resolve the recurrence problem, exploit chaining and minimize the number of indirect element selections in the repeated solution of sparse linear system of equations widely encountered in various power system problems, The proposed schemes are also applied and experimented for the vectorization of power mismatch calculations arising in the solution phase of FDLF which involves typical repeated sparse power network computations. The relative performances of the proposed and existing vectorization schemes are evaluated, both theoretically and experimentally on IBM 3090/VF.

Subject Keywords

Flow, Vector computers, Matrix, Factorization

URI

https://hdl.handle.net/11511/42160

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS

DOI

https://doi.org/10.1109/59.373970

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

C. AYKANAT, O. OZGU, and A. N. Güven, “ALGORITHMS FOR EFFICIENT VECTORIZATION OF REPEATED SPARSE POWER-SYSTEM NETWORK COMPUTATIONS,” IEEE TRANSACTIONS ON POWER SYSTEMS, pp. 448–456, 1995, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42160.