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Data-Parallel Programming on MIMD Computers (Scientific & Engineering Computation)

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Data-Parallel Programming on MIMD Computers (Scientific & Engineering Computation) Cover

 

Synopses & Reviews

Publisher Comments:

MIMD computers are notoriously difficult to program. Data-Parallel Programming demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be compiled and efficiently executed-on both shared-memory multiprocessors and distributed-memory multicomputers.The authors provide enough data so that the reader can decide the feasibility of architecture-independent programming in a data-parallel language. For each benchmark program they give the source code listing, absolute execution time on both a multiprocessor and a multicomputer, and a speedup relative to a sequential program. And they often present multiple solutions to the same problem, to better illustrate the strengths and weaknesses of these compilers.The language presented is Dataparallel C, a variant of the original C* language developed by Thinking Machines Corporation for its Connection Machine processor array. Separate chapters describe the compilation of Dataparallel C programs for execution on the Sequent multiprocessor and the Intel and nCUBE hypercubes, respectively. The authors document the performance of these compilers on a variety of benchmark programs and present several case studies.Philip J. Hatcher is Assistant Professor in the Department of Computer Science at the University of New Hampshire. Michael J. Quinn is Associate Professor of Computer Science at Oregon State University.Contents: Introduction. Dataparallel C Programming Language Description. Design of a Multicomputer Dataparallel C Compiler. Design of a Multiprocessor Dataparallel C Compiler. Writing Efficient Programs. Benchmarking the Compilers. Case Studies. Conclusions.

Book News Annotation:

Demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be compiled and efficiently executed on both shared-memory multiprocessors and distributed-memory multicomputers.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Data-Parallel Programming demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be compiled and efficiently executed-on both shared-memory multiprocessors and distributed-memory multicomputers.

Synopsis:

MIMD computers are notoriously difficult to program.

Description:

Includes bibliographical references (p. [209]-218) and index.

About the Author

Michael J. Quinn is Dean of the College of Science and Engineering atSeattle University.

Product Details

ISBN:
9780262082051
With:
Quinn, Michael J.
Author:
Quinn, Michael J.
Author:
Kowalik, Janusz S.
Author:
Hatcher, Philip J.
Publisher:
The MIT Press
Location:
Cambridge, Mass. :
Subject:
Computer Science
Subject:
Programming Languages - General
Subject:
C (computer program language)
Subject:
Programming - General
Subject:
Parallel programming (computer science)
Subject:
MIMD computers -- Programming.
Subject:
Language, literature and biography
Subject:
Parallel programming
Subject:
MIMD computers
Subject:
Software Engineering - Programming and Languages
Series:
Scientific and Engineering Computation Data-Parallel Programming on MIMD Computers
Series Volume:
9396
Publication Date:
19911230
Binding:
Hardback
Grade Level:
from 17
Language:
English
Illustrations:
Yes
Pages:
250
Dimensions:
9.1 x 7.1 x 0.8 in

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Data-Parallel Programming on MIMD Computers (Scientific & Engineering Computation) New Hardcover
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Product details 250 pages MIT Press - English 9780262082051 Reviews:
"Synopsis" by , Data-Parallel Programming demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be compiled and efficiently executed-on both shared-memory multiprocessors and distributed-memory multicomputers.
"Synopsis" by , MIMD computers are notoriously difficult to program.
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