Computer Science

For senior-level/graduate courses in Parallel Computing and Processing in departments of Engineering, Computer Science and Mathematics.

This carefully class tested text provides comprehensive coverage of the fundamentals of parallel processing with integration of parallel architectures, algorithms, and languages. Its unique presentation integrates the three topics and explains their performance implications, providing students with the depth of knowledge and expertise needed to design and develop successful parallel applications.

• Focus on fundamental concepts with consistent integration of algorithms, languages, and architectures throughout.

  • Teaches students performance implications of these three parallel system components.

• Numerous real-world examples and illustrations throughout.

  • Provides concepts that are carefully presented, helping students comprehend the more difficult ones.

• Carefully class tested for over three years.

  • Provides a presentation that students find accessible and usable.

• Examples in real parallel languages.

  • Clarifies any ambiguities regarding the transition from an algorithm to a real working program.

• Examples on real machines with real data.

  • Demonstrate and test performance models.

• Chapter-opening questions.

  • Stimulates students' thought processes, and motivates them to learn the material to be covered.

• Comprehensive set of thought provoking chapter-end problems.

  • Enables students to gain a deeper understanding of the subject and expand their knowledge of crucial issues.

• Extensive set of figures.

  • Presents complex concepts with clarity.

• Pseudo code.

  • Conveys to students the key concepts without interference from code syntax.

 1. Parallel Machines and Computations.


 2. Potential for Parallel Computations.


 3. Vector Algorithms and Architectures.


 4. MIMD Computers and Multiprocessors.


 5. Distributed Memory Multiprocessors.


 6. Interconnection Networks.


 7. Data Dependence and Parallelism.


 8. Implementing Synchronization and Data Sharing.


 9. Parallel Processor Performance.


10. Temporal Behavior of Parallel Programs.


11. Parallel I/O.


Appendix A. Routines of the MPI Message Passing Library.


Appendix B. Synchronization Mechanisms.


Bibliography.


Index.

Parallel Programming / Concurrent Programming (Computer Science)
Parallel Algorithms (Computer Science)
Parallel Computing (Computer Science)
Parallel Processing (Electrical and Computing Engineering)

Harry F. Jordan received the Ph.D. from the University of Illinois. He has been with the University of Colorado at Boulder since 1966 and is now a professor in the Departments of Electrical and Computer Engineering and Computer Science. Professor Jordan's interests in computer systems center on the interface between hardware and software, including supercomputers, multi-processor architecture, and optical computing.

Gita Alaghband received the Ph.D. in Electrical Engineering (1986) from the University of Colorado at Boulder. Currently, she is a professor in the Department of Computer Science and Engineering at the University of Colorado at Denver. Dr. Alaghband's research interests in parallel processing include computer architecture, performance evaluation, simulation, application programs, and algorithm designs.

This unique book provides comprehensive coverage of the crucial fundamental concepts of parallel processing. The authors also introduce the integration of parallel architecture, algorithms, and language to provide insight into designing and implementing parallel applications. This book is suitable for advanced courses on the principles of parallel processing and is also a superb professional reference.

• Presents subjects by integrating algorithms, languages, and architectures.
• Clearly explains performance analysis and implications resulting from influences of the three components.
• Guides readers with thought-provoking questions at the beginning of each chapter.
• A Offers numerous examples to clarify difficult concepts.
• Helps students implement their learning with 141 end-of-chapter problems.
• A Conveys performance implications of each new topic with consistent integration of algorithms, languages, and architectures throughout the text.

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Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students, contact your Pearson Higher Education representative for pricing and ordering information.

Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students contact your Pearson Higher Education representative.