Parallel Processing for Scientific Computing

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Michael A. Heroux, Padma Raghavan, Horst D. Simon
SIAM, Jan 1, 2006 - Computers - 397 pages
2 Reviews
Parallel Processing for Scientific Computing is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, scientists, and computer scientists focus on to make parallel processing effective for scientific problems. It is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth looks at applications that require parallel computing for scaling to solve larger and more realistic models that can advance science and engineering. In sum, this is an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for students interested in computational modeling and simulation.
  

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Contents

San Diego Supercomputer Center Mathematics and Computer
1
Bruce Curtis Troy NY 12180 USA omarices texas
9
Rochester MN 55901
31
Approaches to ArchitectureAware Parallel Scientific Computation
33
Rob Armstrong gyanus ibm com California Institute of Technology
45
Travis Desell Laboratory
49
Michael A Heroux Salt Lake City UT 84112 USA School of Computer Science
52
Albuquerque NM 87185 USA Ian Foster Yorktown Heights NY 10598
55
Lawrence Livermore National
147
Parallel Sparse Solvers Preconditioners and Their Applications
163
A Survey of Parallelization Techniques for Multigrid Solvers
179
Fault Tolerance in LargeScale Scientific Computing
203
A Survey
223
Parallel Linear Algebra Software
233
HighPerformance Component Software Systems
249
Integrating ComponentBased Scientific Computing Software
271

Achieving High Performance on the BlueGeneL Supercomputer
59
P O Box 808 L561
75
Performance Evaluation and Modeling of UltraScale Systems
77
Lawrence Berkeley National
78
Partitioning and Load Balancing for Emerging Parallel Applications
99
Combinatorial Parallel and Scientific Computing
127
Parallel Adaptive Mesh Refinement
143
Parallel Algorithms for PDEConstrained Optimization
291
Algorithms and Applica
323
Parallel Methods and Software for Multicomponent Simulations
341
Parallel Computational Biology
357
Opportunities and Challenges for Parallel Computing in Science
379
Index
391
Copyright

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About the author (2006)

Michael A. Heroux is the Solvers Project Leader at Sandia National Laboratory; his work focuses on new algorithm development and robust parallel implementation of solver components. He leads development of the Trilinos Project, an effort to provide solution methods in a state-of-the-art software framework. He also maintains an active interest in the interaction between scientific/engineering applications and high-performance computer architectures. Padma Raghavan is a Professor in the Department of Computer Science and Engineering at Pennsylvania State University. Her research interests include parallel and distributed computing, sparse matrix graph techniques and their applications, and software environments and component architectures for large-scale computational materials science.Horst D. Simon is Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory. His recursive spectral bisection algorithm is regarded as a breakthrough in parallel algorithms for unstructured computations, and he was honored for his algorithm research efforts with the 1988 Gordon Bell Prize for parallel processing research.

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