Iterative Methods for Sparse Linear Systems by Yousef Saad
About this book :-
"Iterative Methods for Sparse Linear Systems" by Yousef Saad is a widely respected graduate-level textbook that focuses on "numerical methods for solving large, sparse systems of linear equations", which commonly arise in scientific and engineering applications. As problem sizes grow into the hundreds of thousands or millions of unknowns, traditional direct solvers become inefficient, making iterative methods essential.
The book provides a "comprehensive and practical treatment" of classical and modern iterative techniques. It covers foundational topics such as sparse matrix storage, discretization of partial differential equations, and basic iterative schemes like Jacobi, Gauss–Seidel, and SOR methods. A major strength of the text is its in-depth discussion of "Krylov subspace methods", including Conjugate Gradient, GMRES, and related algorithms, along with detailed analysis of convergence behavior.
A significant emphasis is placed on "preconditioning, parallel implementations, and multigrid methods", reflecting modern high-performance computing needs. Algorithms are presented clearly, often with pseudocode, and supported by numerous exercises. The book is suitable as a "graduate textbook and reference" for students, researchers, and practitioners in applied mathematics, computer science, engineering, and scientific computing.
Book Detail :-
Title:
Iterative Methods for Sparse Linear Systems by Yousef Saad
Publisher:
SIAMs
Year:
2003
Pages:
556
Type:
PDF
Language:
English
ISBN-10 #:
0898715342
ISBN-13 #:
978-0898715347
License:
External Educational Resource
Amazon:
Amazon
About Author :-
The author
Yousef Saad
is a well-known scholar in "numerical linear algebra" and "scientific computing", recognized for his research on large-scale matrix problems. He served as a Professor Emeritus at the University of Minnesota and has contributed extensively to the development of modern computational mathematics. His work focuses on "iterative methods", "sparse matrices", and "high-performance computing", with strong impact in engineering and scientific applications. Saad is widely respected for combining theory with practical algorithms, and his books are considered essential references for graduate students and researchers working in computational and applied mathematics.
Book Contents :-
1. Background in Linear Algebra
2. Discretization of PDEs
3. Sparse Matrices
4. Basic Iterative Methods
5. Projection Methods
6. Krylov Subspace Methods Part I
7. Krylov Subspace Methods Part II
8. Methods Related to the Normal Equations
9. Preconditioned Iterations
10. Preconditioning Techniques
11. Parallel Implementations
12. Parallel Preconditioners
13. Multigrid Methods
14. Domain Decomposition Methods
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