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Recent Progress in Computational Sciences and Engineering (Hardcover)
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Recent Progress in Computational Sciences and Engineering (Hardcover)
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Designed for introductory parallel computing courses at the
advanced undergraduate or beginning graduate level, Elements of
Parallel Computing presents the fundamental concepts of parallel
computing not from the point of view of hardware, but from a more
abstract view of algorithmic and implementation patterns. The aim
is to facilitate the teaching of parallel programming by surveying
some key algorithmic structures and programming models, together
with an abstract representation of the underlying hardware. The
presentation is friendly and informal. The content of the book is
language neutral, using pseudocode that represents common
programming language models. The first five chapters' present core
concepts in parallel computing. SIMD, shared memory, and
distributed memory machine models are covered, along with a brief
discussion of what their execution models look like. The book also
discusses decomposition as a fundamental activity in parallel
algorithmic design, starting with a naive example, and continuing
with a discussion of some key algorithmic structures. Important
programming models are presented in depth, as well as important
concepts of performance analysis, including work-depth analysis of
task graphs, communication analysis of distributed memory
algorithms, key performance metrics, and a discussion of barriers
to obtaining good performance. The second part of the book presents
three case studies that reinforce the concepts of the earlier
chapters. One feature of these chapters is to contrast different
solutions to the same problem, using select problems that aren't
discussed frequently in parallel computing textbooks. They include
the Single Source Shortest Path Problem, the Eikonal equation, and
a classical computational geometry problem: computation of the
two-dimensional convex hull. After presenting the problem and
sequential algorithms, each chapter first discusses the sources of
parallelism then
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