Parallel implementation of an efficient preconditioned linear solver for grid-based applications in chemical physics. III: Improved parallel scalability for sparse matrix–vector products

The linear solve problems arising in chemical physics and many other fields involve large sparse matrices with a certain block structure, for which special block Jacobi preconditioners are found to be very efficient. In two previous papers [W. Chen, B. Poirier, Parallel implementation of efficient p...

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Veröffentlicht in:	Journal of parallel and distributed computing Jg. 70; H. 7; S. 779 - 782
Hauptverfasser:	Chen, Wenwu, Poirier, Bill
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Inc 01.07.2010 Elsevier
Schlagworte:	Algorithms Applied sciences Block Jacobi Blocking Chemical physics Chemistry Computer networks Computer science; control theory; systems Computer systems and distributed systems. User interface Construction Distributed processing Eigensolver Exact sciences and technology General and physical chemistry Linear solver Matrix–vector product Parallel computing Preconditioning Software Solvers Sparse matrices Sparse matrix Theory of reactions, general kinetics Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry Parallel computing Eigensolver Block Jacobi Matrix–vector product Linear solver Sparse matrix Chemical physics Preconditioning Matrix diagonalization High performance Parallel algorithm Scalability Physical chemistry Grid Matrix product Jacobi matrix Distributed computing Lanczos method Parallel processing Matrix-vector product Block matrix
ISSN:	0743-7315, 1096-0848
Online-Zugang:	Volltext
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