Coarse Grain Scheduling in pakallel triangular Factorization and Solution of Power System Matrices

Kawah Lau; Daniel Tylavsky; Anjan Bose

doi:10.1109/59.76716

Coarse Grain Scheduling in pakallel triangular Factorization and Solution of Power System Matrices

Kawah Lau, Daniel Tylavsky, Anjan Bose

Electrical Engineering

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

Triangular (LU) factorization has long been a widely used method for solving sparse linear matrix equations arising from power system analysis problems in the industry. Recent interest has been shown in parallel processing in order to further improve the speed of solution of the linear matrix equation. Parallel triangular factorization scheduling using two fast coarse grain scheduling schemes is presented in this paper along with performance results obtained using the iPSC hypercube parallel processing computer. The study shows that the solution of the parallel LU factorization problem using different coarse grain scheduling schemes on a coarse grain parallel processing computer can have widely varying performance results.

Original language	English (US)
Pages (from-to)	708-714
Number of pages	7
Journal	IEEE Transactions on Power Systems
Volume	6
Issue number	2
DOIs	https://doi.org/10.1109/59.76716
State	Published - 1991

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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abstract = "Triangular (LU) factorization has long been a widely used method for solving sparse linear matrix equations arising from power system analysis problems in the industry. Recent interest has been shown in parallel processing in order to further improve the speed of solution of the linear matrix equation. Parallel triangular factorization scheduling using two fast coarse grain scheduling schemes is presented in this paper along with performance results obtained using the iPSC hypercube parallel processing computer. The study shows that the solution of the parallel LU factorization problem using different coarse grain scheduling schemes on a coarse grain parallel processing computer can have widely varying performance results.",

author = "Kawah Lau and Daniel Tylavsky and Anjan Bose",

note = "Funding Information: This material is based upon work supported by the National Science Foundation under Grant No. ECS-8715715.",

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AU - Bose, Anjan

N1 - Funding Information: This material is based upon work supported by the National Science Foundation under Grant No. ECS-8715715.

PY - 1991

Y1 - 1991

N2 - Triangular (LU) factorization has long been a widely used method for solving sparse linear matrix equations arising from power system analysis problems in the industry. Recent interest has been shown in parallel processing in order to further improve the speed of solution of the linear matrix equation. Parallel triangular factorization scheduling using two fast coarse grain scheduling schemes is presented in this paper along with performance results obtained using the iPSC hypercube parallel processing computer. The study shows that the solution of the parallel LU factorization problem using different coarse grain scheduling schemes on a coarse grain parallel processing computer can have widely varying performance results.

AB - Triangular (LU) factorization has long been a widely used method for solving sparse linear matrix equations arising from power system analysis problems in the industry. Recent interest has been shown in parallel processing in order to further improve the speed of solution of the linear matrix equation. Parallel triangular factorization scheduling using two fast coarse grain scheduling schemes is presented in this paper along with performance results obtained using the iPSC hypercube parallel processing computer. The study shows that the solution of the parallel LU factorization problem using different coarse grain scheduling schemes on a coarse grain parallel processing computer can have widely varying performance results.

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Coarse Grain Scheduling in pakallel triangular Factorization and Solution of Power System Matrices

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