Series: Scientific and Engineering Computation. Num Pages: 336 pages, 114 b&w illus. BIC Classification: UYFP. Category: (P) Professional & Vocational. Dimension: 230 x 205 x 19. Weight in Grams: 630. . 2014. third edition. Paperback. . . . .

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Bibliographic Details

Title: Using MPI: Portable Parallel Programming with the Message-Passing Interface (Scientific and Engineering Computation)
Publisher: The MIT Press
Publication Date: 2014
Language: English
ISBN 10: 0262527391
ISBN 13: 9780262527392
Binding: Soft cover
Edition: 3rd Edition
Condition: New

About this title

Synopsis

The thoroughly updated edition of a guide to parallel programming with MPI, reflecting the latest specifications, with many detailed examples.

This book offers a thoroughly updated guide to the MPI (Message-Passing Interface) standard library for writing programs for parallel computers. Since the publication of the previous edition of Using MPI, parallel computing has become mainstream. Today, applications run on computers with millions of processors; multiple processors sharing memory and multicore processors with multiple hardware threads per core are common. The MPI-3 Forum recently brought the MPI standard up to date with respect to developments in hardware capabilities, core language evolution, the needs of applications, and experience gained over the years by vendors, implementers, and users. This third edition of Using MPI reflects these changes in both text and example code.

The book takes an informal, tutorial approach, introducing each concept through easy-to-understand examples, including actual code in C and Fortran. Topics include using MPI in simple programs, virtual topologies, MPI datatypes, parallel libraries, and a comparison of MPI with sockets. For the third edition, example code has been brought up to date; applications have been updated; and references reflect the recent attention MPI has received in the literature. A companion volume, Using Advanced MPI, covers more advanced topics, including hybrid programming and coping with large data.

About the Author

William Gropp is Director of the Parallel Computing Institute and Thomas M. Siebel Chair in Computer Science at the University of Illinois Urbana-Champaign.

Ewing Lusk is Argonne Distinguished Fellow Emeritus at Argonne National Laboratory.

Anthony Skjellum is Professor of Software Engineering at Auburn University.

"About this title" may belong to another edition of this title.

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