Software for Parallel Computation (eBook, PDF)

Redaktion: Kowalik, Janusz S.; Grandinetti, Lucio

• Format: PDF

Produktbeschreibung

This book contains papers on the most critical issue of parallel computing-software. It focuses on parallel software, programming tools, and practical experience of using parallel computers for solving demanding problems. Several high performance tools are described here for the first time.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 366
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9783642580499
• Artikelnr.: 53156847

Inhaltsangabe

1 Introduction.- Software for Parallel Computing: Key Issues and Research Directions.- 2 Tools and Methods for Parallel Computing.- Learning From Our Successes.- Software Development for Parallel Processing.- Software Tools for Developing and Porting Parallel Programs.- Scalable Software Tools for Parallel Computations.- PVM and HeNCE: Tools for Heterogeneous Network Computing.- Distributed Shared Memory: Principles and Implementation.- FORGE 90 and High Performance Fortran (HPF).- The Bird-Meertens Formalism as a Parallel Model.- Software Issues for the PASM Parallel Processing System.- Data Migrations on the Hypercube.- Automatic Determination of Parallelism in Programs.- Are Object Oriented Programming Methods Suitable for Numerical Computing on Parallel Machines.- Parallel Relational Data Base Management System Design Aspects.- 3 Graphics.- MUDI3: a Tool for the Interactive Visual Analysis of Multidimensional Fields.- Graphical Support for Parallel Debugging.- 4 Algorithms and Applications.- Backpropagation on Distributed Memory Systems.- Mapping Algorithms on Hypercube.- Software Development for Finite Element Fluid Dynamic Applications.- Asynchronous Communication on Shared-Memory Parallel Computers.- Two Different Data-Parallel Implementations of the BLAS.- 5 Performance of Parallel Programs and Systems.- Examples of Scalable Performance.- Performance Prediction from Data Transport.- Dynamic Load Balancing in Adaptive Parallel Applications.- Performance Analysis of Dynamic Scheduling Techniques for Irregularly Structured Computation.