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Principles Of Parallel Programming Pearson International Edition
With the rise of multi-core architecture, parallel programming is an increasingly important topic for software engineers and computer system designers. Written by well-known researchers Larry Snyder and Calvin Lin, this highly anticipated first edition emphasizes the principles underlying parallel computation, explains the various phenomena, and clarifies
why these phenomena represent opportunities or barriers to successful parallel programming. Ideal for an advanced upper-level undergraduate course, Principles of Parallel Programming supplies enduring knowledge that will outlive the current hardware and software, aiming to inspire future researchers to build tomorrow's solutions. "...the first basic book on the subject that I've ever seen that seems to have the pulse on the true issues of parallelism that are relevant for students." -- Alan Edelman, MIT "Principles of Parallel Programming is a wonderful book and I plan to use it in our new parallel programming course..."-- Peiyi Tang, University of Arkansas, Little Rock "I like [Principles of Parallel Programming] very much for a few specific reasons: it's concise, covers the most relevant topics but does not take thousand pages to do it, it is hands on and it covers. ..recent developments with multi-core and GPGPU." -- Edin Hodzic, Santa Clara University
Contents:
Chapter 1 Introduction: Parallelism = Opportunities + Challenges The Power and Potential of Parallelism Examining Sequential and Parallel Programs A Paradigm Shift Parallelism Using Multiple Instruction Streams The Goals: Scalable Performance and Portability Summary Historical Context Exercises Chapter 2 Parallel Computers And Their Model Balancing Machine Specifics with Portability A Look at Five Parallel Computers The RAM: An Abstraction of a Sequential Computer The PRAM: A Parallel Computer Model The CTA: A Practical Parallel Computer Model Memory Reference Mechanisms A Closer Look at Communication Applying the CTA Model Summary Historical Perspective Exercises Chapter 3 Reasoning about Performance Introduction Motivation and Some Basic Concepts Sources of Performance Loss Parallel Structure Reasoning about Performance Performance Trade-Offs Measuring Performance What should we measure? Summary Historical Perspective Exercises Chapter 4 First Steps Towards Parallel Programming Task and Data Parallelism Peril-L Count 3s Example Conceptualizing Parallelism Alphabetizing Example Comparison of Three Solutions Summary Historical Perspective Exercises Chapter 5 Scalable Algorithmic Techniques The Inevitability of Trees Blocks of Independent Computation Schwartz' Algorithm Assigning Work To Processes Statically Assigning Work to Processes Dynamically The Reduce & Scan Abstractions Trees Summary Historical Context Exercises Chapter 6 Programming with Threads POSIX Threads Thread Creation and Destruction Mutual Exclusion Synchronization Safety Issues Performance Issues Open MP The Count 3s Example Semantic Limitations on Reduction Thread Behavior and Interaction Sections Summary of OpenMP Java Threads Summary Historical Perspectives Exercises Chapter 7 Local View Programming Languages MPI: The Message Passing Interface Getting Started Safety Issues Performance Issues Co-Array Fortran Unified Parallel C Titanium Summary Exercises Chapter 8 Global View Programming Languages The Z-level Programming Language Basic Concepts of ZPL Life, An Example Design Principles Manipulating Arrays Of Different Ranks Reordering Data With Remap Parallel Execution of ZPL Performance Model Summary NESL Historical Context Exercises Chapter 9 Assessing Our Knowledge Introduction Evaluating Existing Approaches Lessons for the Future Summary Historical Perspectives Exercises Chapter 10 Future Directions in Parallel Programming Attached Processors Grid Computing Transactional Memory Summary Exercises Chapter 11 Capstone Project: Designing a Parallel Program Introduction Motivation Getting Started Summary Historical Perspective Exercises Appendix 1 More Advanced Concepts
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