Parallel-Vector Equation Solvers for Finite Element Engineering Applications by Duc Thai Nguyen.

Despite the ample number of articles on parallel-vector computational algorithms published over the last 20 years, there is a lack of texts in the field customized for senior undergraduate and graduate engineering research. Parallel-Vector Equation Solvers for Finite Element Engineering Applications...

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Bibliographic Details
Main Author: Duc Thai Nguyen (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2002.
Edition:1st ed. 2002.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

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505 0 |a 1. Introduction -- 1.1 Parallel Computers -- 1.2 Measurements for Algorithms’ Performance -- 1.3 Vector Computers -- 1.4 Summary -- 1.5 Exercises -- 1.6 References -- 2. Storage Schemes for the Coefficient Stiffness Matrix -- 2.1 Introduction -- 2.2 Full Matrix -- 2.3 Symmetrical Matrix -- 2.4 Banded Matrix -- 2.5 Variable Banded Matrix -- 2.6 Skyline Matrix -- 2.7 Sparse Matrix -- 2.8 Detailed Procedures For Determining The Mapping Between 2-D Array and 1-D Array in Skyline Storage Scheme -- 2.9 Determination of the Column Height (ICOLH) of a Finite Element Model -- 2.10 Computer Implementation For Determining Column Heights -- 2.11 Summary -- 2.12 Exercises -- 2.13 References -- 3. Parallel Algorithms for Generation and Assembly of Finite Element Matrices -- 3.1 Introduction -- 3.2 Conventional Algorithm to Generate and Assemble Element Matrices -- 3.3 Node-by-Node Parallel Generation and Assembly Algorithms -- 3.4 Additional Comments on Baddourah-Nguyen’s (Node-by-Node) Parallel Generation and Assembly (G&A) Algorithm -- 3.5 Application of Baddourah-Nguyen’s Parallel G&A Algorithm -- 3.6 Qin-Nguyen’s G&A Algorithm -- 3.7 Applications of Qin-Nguyen’s Parallel G&A Algorithm -- 3.8 Summary -- 3.9 Exercises -- 3.10 References -- 4. Parallel-Vector Skyline Equation Solver on Shared Memory Computers -- 4.1 Introduction -- 4.2 Choleski-based Solution Strategies -- 4.3 Factorization -- 4.4 Solution of Triangular Systems -- 4.5 Force: A Portable, Parallel FORTRAN Language -- 4.6 Evaluation of Methods on Example Problems -- 4.7 Skyline Equation Solver Computer Program -- 4.8 Summary -- 4.9 Exercises -- 4.10 References -- 5. Parallel-Vector Variable Bandwidth Equation Solver on Shared Memory Computers -- 5.1 Introduction -- 5.2 Data Storage Schemes -- 5.3 Basic Sequential Variable Bandwidth Choleski Method -- 5.4 Vectorized Choleski Code with Loop Unrolling -- 5.5 More on Force: A Portable, Parallel FORTRAN Language -- 5.6 Parallel-Vector Choleski Factorization -- 5.7 Solution of Triangular Systems -- 5.8 Relations Amongst the Choleski, Gauss and LDLT Factorizations -- 5.9 Factorization Based Upon “Look Backward” Versus “Look Forward” Strategies -- 5.10 Evaluation of Methods For Structural Analyses -- 5.11 Descriptions of Parallel-Vector Subroutine PVS -- 5.12 Parallel-Vector Equation Solver Subroutine PVS -- 5.13 Summary -- 5.14 Exercises -- 5.15 References -- 6. Parallel-Vector Variable Bandwidth Out-of-Core Equation Solver -- 6.1 Introduction -- 6.2 Out-of-Core Parallel/Vector Equation Solver (version 1) -- 6.3 Out-of-Core Vector Equation Solver (version 2) -- 6.4 Out-of-Core Vector Equation Solver (version 3) -- 6.5 Application -- 6.6 Summary -- 6.7 Exercises -- 6.8 References -- 7. Parallel-Vector Skyline Equation Solver for Distributed Memory Computers -- 7.1 Introduction -- 7.2 Parallel-Vector Symmetrical Equation Solver -- 7.3 Numerical Results and Discussions -- 7.4 FORTRAN Call Statement to Subroutine Node -- 7.5 Summary -- 7.6 Exercises -- 7.7 References -- 8. Parallel-Vector Unsymmetrical Equation Solver -- 8.1 Introduction -- 8.2 Parallel-Vector Unsymmetrical Equation Solution Algorithms -- 8.3 Numerical Evaluations -- 8.4 A Few Remarks On Pivoting Strategies -- 8.5 A FORTRAN Call Statement to Subroutine UNSOLVER -- 8.6 Summary -- 8.7 Exercises -- 8.8 References -- 9. A Tridiagonal Solver for Massively Parallel Computers -- 9.1 Introduction -- 9.2 Basic Sequential Solution Procedures for Tridiagonal Equations -- 9.3 Cyclic Reduction Algorithm -- 9.4 Parallel Tridiagonal Solver by Using Divided and Conquered Strategies -- 9.5 Parallel Factorization Algorithm for Tridiagonal System of Equations Using Separators -- 9.6 Forward and Backward Solution Phases -- 9.7 Comparisons between Different Algorithms -- 9.8 Numerical Results -- 9.9 A FORTRAN Call Statement To Subroutine Tridiag -- 9.10 Summary -- 9.11 Exercises -- 9.12 References -- 10. Sparse Equation Solver with Unrolling Strategies -- 10.1 Introduction -- 10.2 Basic Equation Solution Algorithms -- 10.3 Storage Schemes for the Coefficient Stiffness Matrix -- 10.4 Reordering Algorithms -- 10.5 Sparse Symbolic Factorization -- 10.6 Sparse Numerical Factorization -- 10.7 Forward and Backward Solutions -- 10.8 Sparse Solver with Improved Strategies -- 11. Algorithms for Sparse-Symmetrical-Indefinite and Sparse-Unsymmetrical System of Equations -- 11.1 Introduction -- 11.2 Basic Formulation for Indefinite System of Linear Equations -- 11.3 Rotation Matrix [R] Strategies -- 11.4 Natural 2x2 Pivoting -- 11.5 Switching Row(s) and Column(s) During Factorization -- 11.6 Simultaneously Performing Symbolic and Numerical Factorization -- 11.7 Restart Memory Managements -- 11.8 Major Step-by-Step Procedures for Mixed Look Forward/ Backward, Sparse LDLT Factorization, Forward and Backward Solution With 2x2 Pivoting Strategies -- 11.9 Numerical Evaluations -- 11.10 Some Remarks on Unsymmetrical-Sparse System of Linear Equations -- 11.11 Summary -- 11.12 Exercises -- 11.13 References. 
520 |a Despite the ample number of articles on parallel-vector computational algorithms published over the last 20 years, there is a lack of texts in the field customized for senior undergraduate and graduate engineering research. Parallel-Vector Equation Solvers for Finite Element Engineering Applications aims to fill this gap, detailing both the theoretical development and important implementations of equation-solution algorithms. The mathematical background necessary to understand their inception balances well with descriptions of their practical uses. Illustrated with a number of state-of-the-art FORTRAN codes developed as examples for the book, Dr. Nguyen's text is a perfect choice for instructors and researchers alike. 
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