KRYLOV SUBSPACE SOLVERS IN PARALLEL NUMERICAL COMPUTATIONS OF PARTIAL DIFFERENTIAL EQUATIONS MODELING HEAT TRANSFER APPLICATIONS

In this study, parallel numerical algorithms for Krylov methods such as GMRES(k), Bi-CGM, Bi-CGSTAB, etc., for handling large-scale linear systems resulting from finite-difference analysis (FDA) and finite-element analysis (FEA) of coupled nonlinear partial differential equations (PDEs) describing p...

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Vydáno v:Numerical heat transfer. Part A, Applications Ročník 45; číslo 5; s. 479 - 503
Hlavní autoři: Rathish Kumar, B. V., Kumar, Bipin, Shalini, Mehra, Mani, Chandra, Peeyush, Raghvendra, V., Singh, R. K., Mahindra, A. K.
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Taylor & Francis Group 19.03.2004
Taylor & Francis
Témata:
Analytical and numerical techniques
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Heat transfer
Physics
Finite element method
Partial differential equations
Digital simulation
Krylov subspace method
Natural convection
Modelling
Reaction diffusion equation
Parallel algorithms
Numerical convergence
Heat transfer
Finite difference method
ISSN:1040-7782, 1521-0634
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Abstract In this study, parallel numerical algorithms for Krylov methods such as GMRES(k), Bi-CGM, Bi-CGSTAB, etc., for handling large-scale linear systems resulting from finite-difference analysis (FDA) and finite-element analysis (FEA) of coupled nonlinear partial differential equations (PDEs) describing problems in heat transfer applications are discussed. Parallel code has been successfully implemented on an eight-noded cluster under ANULIB message-passing library environment. Bi-CGM and ILU-GMRES(k) are found to give good performance for linear systems resulting from FEA, whereas Bi-CGSTAB is seen to give good performance with linear systems resulting from FDA.
AbstractList In this study, parallel numerical algorithms for Krylov methods such as GMRES(k), Bi-CGM, Bi-CGSTAB, etc., for handling large-scale linear systems resulting from finite-difference analysis (FDA) and finite-element analysis (FEA) of coupled nonlinear partial differential equations (PDEs) describing problems in heat transfer applications are discussed. Parallel code has been successfully implemented on an eight-noded cluster under ANULIB message-passing library environment. Bi-CGM and ILU-GMRES(k) are found to give good performance for linear systems resulting from FEA, whereas Bi-CGSTAB is seen to give good performance with linear systems resulting from FDA.
In this study, parallel numerical algorithms for Krylov methods such as GMRES(k), Bi-CGM, Bi-CGSTAB, etc., for handling large-scale linear systems resulting from finite-difference analysis (FDA) and finite-element analysis (FEA) of coupled nonlinear partial differential equations (PDEs) describing problems in heat transfer applications are discussed. Parallel code has been successfully implemented on an eight-noded cluster under ANVLIB message-passing library environment. Bi-CGM and ILV-GMRES(k) are found to give good performance for linear systems resulting from FEA, whereas Bi-CGSTAB is seen to give good performance with linear systems resulting from FDA.
Author Raghvendra, V.
Shalini
Singh, R. K.
Rathish Kumar, B. V.
Kumar, Bipin
Mehra, Mani
Mahindra, A. K.
Chandra, Peeyush
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crossref_primary_10_1016_j_matcom_2003_12_001
crossref_primary_10_1016_j_amc_2004_06_071
crossref_primary_10_1080_10407790500511096
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Issue 5
Keywords Finite element method
Partial differential equations
Digital simulation
Krylov subspace method
Natural convection
Modelling
Reaction diffusion equation
Parallel algorithms
Numerical convergence
Heat transfer
Finite difference method
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SubjectTerms Analytical and numerical techniques
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Heat transfer
Physics
Title KRYLOV SUBSPACE SOLVERS IN PARALLEL NUMERICAL COMPUTATIONS OF PARTIAL DIFFERENTIAL EQUATIONS MODELING HEAT TRANSFER APPLICATIONS
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