Data-parallel Programming on MIMD Computers
Data-parallel Programming on MIMD Computers

Author: Philip J. Hatcher

Publisher:

Published: 1991

Total Pages: 231

ISBN-13: 9780262288484

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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.ContentsIntroduction 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

Parallel Supercomputing in MIMD Architectures
Parallel Supercomputing in MIMD Architectures

Author: R.Michael Hord

Publisher: CRC Press

Published: 2018-02-01

Total Pages: 483

ISBN-13: 1351092235

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Parallel Supercomputing in MIMD Architectures is devoted to supercomputing on a wide variety of Multiple-Instruction-Multiple-Data (MIMD)-class parallel machines. This book describes architectural concepts, commercial and research hardware implementations, major programming concepts, algorithmic methods, representative applications, and benefits and drawbacks. Commercial machines described include Connection Machine 5, NCUBE, Butterfly, Meiko, Intel iPSC, iPSC/2 and iWarp, DSP3, Multimax, Sequent, and Teradata. Research machines covered include the J-Machine, PAX, Concert, and ASP. Operating systems, languages, translating sequential programs to parallel, and semiautomatic parallelizing are aspects of MIMD software addressed in Parallel Supercomputing in MIMD Architectures. MIMD issues such as scalability, partitioning, processor utilization, and heterogenous networks are discussed as well.This book is packed with important information and richly illustrated with diagrams and tables, Parallel Supercomputing in MIMD Architectures is an essential reference for computer professionals, program managers, applications system designers, scientists, engineers, and students in the computer sciences.

Foundations of Parallel Programming
Foundations of Parallel Programming

Author: D. B. Skillicorn

Publisher: Cambridge University Press

Published: 1994-12

Total Pages: 214

ISBN-13: 9780521455114

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This is the first comprehensive account of this new approach to the fundamentals of parallel programming.

Parallel Processing and Parallel Algorithms
Parallel Processing and Parallel Algorithms

Author: Seyed H Roosta

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 579

ISBN-13: 1461212200

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Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.

Introduction to Parallel Computing
Introduction to Parallel Computing

Author: Ananth Grama

Publisher: Pearson Education

Published: 2003

Total Pages: 664

ISBN-13: 9780201648652

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A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.

Parallel Programming
Parallel Programming

Author: Thomas Bräunl

Publisher:

Published: 1993

Total Pages: 294

ISBN-13:

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This introduction to parallel programming explores the fundamentals of parallelism, parallel system architecture (MIMD and SIMD), and parallel programming languages, and presents methods for designing parallel algorithms, for writing efficient parallel programs, and for computing performance data and judging it.

An Introduction to Parallel Programming
An Introduction to Parallel Programming

Author: Peter Pacheco

Publisher: Morgan Kaufmann

Published: 2021-08-27

Total Pages: 498

ISBN-13: 012804618X

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An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs. Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models A robust package of online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition: New chapters on GPU programming and heterogeneous programming New examples and exercises related to parallel algorithms