
The SIAM series on Software, Environments, and Tools focuses on the practical implementation of
computational methods and the high performance aspects of scientific computation by emphasizing
in-demand software, computing environments, and tools for computing. Software technology development
issues such as current status, applications and algorithms, mathematical software, software tools, languages
and compilers, computing environments, and visualization are presented.
Editor-in-Chief
Jack J. Dongarra
University of Tennessee and Oak Ridge National Laboratory
Series Editors
Timothy A. Davis
Texas A&M University
James W. Demmel
University of California,
Berkeley
Laura Grigori
INRIA
Michael A. Heroux
Sandia National Laboratories
Padma Raghavan
Pennsylvania State University
Yves Robert
ENS Lyon
Software, Environments, and Tools
Ed Bueler, PETSc for Partial Differential Equations: Numerical Solutions in C and Python
D. L. Chopp, Introduction to High Performance Scientific Computing
Thomas Huckle and Tobias Neckel, Bits and Bugs: A Scientific and Historical Review of Software Failures in
Computational Science
Thomas F. Coleman and Wei Xu, Automatic Differentiation in MATLAB Using ADMAT with Applications
Walter Gautschi, Orthogonal Polynomials in MATLAB: Exercises and Solutions
Daniel J. Bates, Jonathan D. Hauenstein, Andrew J. Sommese, and Charles W. Wampler, Numerically Solving
Polynomial Systems with Bertini
Uwe Naumann, The Art of Differentiating Computer Programs: An Introduction to Algorithmic Differentiation
C. T. Kelley, Implicit Filtering
Jeremy Kepner and John Gilbert, editors, Graph Algorithms in the Language of Linear Algebra
Jeremy Kepner, Parallel MATLAB for Multicore and Multinode Computers
Michael A. Heroux, Padma Raghavan, and Horst D. Simon, editors, Parallel Processing for Scientific Computing
Gérard Meurant, The Lanczos and Conjugate Gradient Algorithms: From Theory to Finite Precision Computations
Bo Einarsson, editor, Accuracy and Reliability in Scientific Computing
Michael W. Berry and Murray Browne, Understanding Search Engines: Mathematical Modeling and Text
Retrieval, Second Edition
Craig C. Douglas, Gundolf Haase, and Ulrich Langer, A Tutorial on Elliptic PDE Solvers and Their Parallelization
Louis Komzsik, The Lanczos Method: Evolution and Application
Bard Ermentrout, Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers
and Students
V. A. Barker, L. S. Blackford, J. Dongarra, J. Du Croz, S. Hammarling, M. Marinova, J. Wasniewski, and
P. Yalamov, LAPACK95 Users’ Guide
Stefan Goedecker and Adolfy Hoisie, Performance Optimization of Numerically Intensive Codes
Zhaojun Bai, James Demmel, Jack Dongarra, Axel Ruhe, and Henk van der Vorst, Templates for the Solution
of Algebraic Eigenvalue Problems: A Practical Guide
Lloyd N. Trefethen, Spectral Methods in MATLAB
E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling,
A. McKenney, and D. Sorensen, LAPACK Users’ Guide, Third Edition
Michael W. Berry and Murray Browne, Understanding Search Engines: Mathematical Modeling and Text Retrieval
Jack J. Dongarra, Iain S. Duff, Danny C. Sorensen, and Henk A. van der Vorst, Numerical Linear Algebra
for High-Performance Computers
R. B. Lehoucq, D. C. Sorensen, and C. Yang, ARPACK Users’ Guide: Solution of Large-Scale Eigenvalue Problems
with Implicitly Restarted Arnoldi Methods
Randolph E. Bank, PLTMG: A Software Package for Solving Elliptic Partial Differential Equations, Users’ Guide 8.0
L. S. Blackford, J. Choi, A. Cleary, E. D’Azevedo, J. Demmel, I. Dhillon, J. Dongarra, S. Hammarling,
G. Henry, A. Petitet, K. Stanley, D. Walker, and R. C. Whaley, ScaLAPACK Users’ Guide
Greg Astfalk, editor, Applications on Advanced Architecture Computers
Roger W. Hockney, The Science of Computer Benchmarking
Françoise Chaitin-Chatelin and Valérie Frayssé, Lectures on Finite Precision Computations
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