Parallel Processing for Scientific ComputingParallel 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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Parallel Processing for Scientific Computing Michael A. Heroux,Padma Raghavan,Horst D. Simon Limited preview - 2006 |
Parallel Processing for Scientific Computing Michael A. Heroux,Padma Raghavan,Horst D. Simon No preview available - 2006 |
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adaptive mesh adaptive mesh refinement adjoint algebra analysis application approach benchmarks BG/L block cache chapter checkpointing cluster coarse grid coarsening communication complex component architecture component models Computer Science Conference on Parallel constraints developed Distributed Computing efficient environment equations example factorization fault tolerance finite element framework function genome global graph partitioning High Performance hypergraph IEEE implementation integration interface inverse iterative methods Journal on Scientific linear system load balancing Mathematics memory minimize modules multigrid methods multilevel multiple National Laboratory nonlinear number of processors objects OpenMP operations optimization problem parallel algorithms Parallel and Distributed parallel computing Parallel Processing parallel programming parameters partitioners Power4 preconditioner Proc require runtime SAMR scalability ScaLAPACK Scientific Computing SCIRun2 SIAM SIAM Conference SIAM Journal simulation solution solvers solving sparse matrix strategies subdomains subproblems Supercomputing Tech techniques unstructured vector virtual node mode