Structured Parallel Programming: Patterns for Efficient Computation

by Michael McCool, James Reinders, Arch Robison

Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology.The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming modelsDevelops a composable, structured, scalable, and machine-independent approach to parallel computingIncludes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers

Genres: Computer Science, Programming, Technical

433 pages, Kindle Edition

First published June 27, 2012

Reviews

[Jörn Dinkla · Rating 4 out of 5]

Good if you program thread based on multi cores with shared memory with TBB or Cilk. Not much information if you use GPUs. Nothing on message based architectures. All-in-all it's good to read it. I learned from this book.

[Brian · Rating 4 out of 5]

If I was teach a parallel programming course, I might consider using this work (although I still have other, similar textbooks to review); however, were I to do so I would be confining my teaching to the first two parts and may even to just 1 parallel programming paradigm. Yes, I will admit that the last parallel programming course I took covered a diversity of paradigms (Cilk, vectorization, GPUs, OpenMP, MPI), yet I would have preferred to focus more on what one or two paradigms are capable of rather than just the taste of many. Parallel programming takes a lot of work to learn and this book is one piece in that effort.

Full review at: http://elegantc.blogspot.com/2015/04/...