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Book by Hatcher Philip J Quinn Michael J
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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. 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. 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
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MIMD computers are notoriously difficult to program. Data-Parallel Programming on MIMD Computers 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.
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- VerlagMIT Press
- Erscheinungsdatum1991
- ISBN 10 0262082055
- ISBN 13 9780262082051
- EinbandTapa dura
- SpracheEnglisch
- Anzahl der Seiten250
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Data-Parallel Programming on MIMD Computers (Scientific and Engineering Computation)
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Hardcover. Zustand: As New. No Jacket. 1st Edition. Bestandsnummer des Verkäufers 36156
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Data-Parallel Programming on MIMD Computers.
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Zustand: as new. Cambridge, MA: The MIT Press, 1991. Hardcover. Dustjacket. 231 pp.(Scientific and Engineering Computation). - 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. English text. Condition : as new. Condition : as new copy. ISBN 9780262082051. Keywords : , Bestandsnummer des Verkäufers 263635
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Data-Parallel Programming on MIMD Computers Scientific and Engineering Computation
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Hardcover-Großformat. Zustand: Gut. 231 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 660. Bestandsnummer des Verkäufers 2138655
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Data-Parallel Programming on MIMD Computers (Scientific & Engineering Computation)
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Zustand: Sehr gut. Auflage: New. 250 Seiten ex Library Book / aus einer wissenschafltichen Bibliothek / Sprache: Englisch Gewicht in Gramm: 969 23,7 x 18,5 x 2,0 cm, Gebundene Ausgabe. Bestandsnummer des Verkäufers 367816
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Zustand: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. | Seiten: 250 | Sprache: Englisch | Produktart: Bücher. Bestandsnummer des Verkäufers 2391787/202
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