1.3 Organization and Contents of the Text
This book provides a comprehensive and self-contained exposition of problem solving using parallel computers. Algorithms and metrics focus on practical and portable models of parallel machines. Principles of algorithm design focus on desirable attributes of parallel algorithms and techniques for achieving these in the contest of a large class of applications and architectures. Programming techniques cover standard paradigms such as MPI and POSIX threads that are available across a range of parallel platforms.
Chapters in this book can be grouped into four main parts as illustrated in Figure 1.1. These parts are as follows:
Fundamentals This section spans Chapters 2 through 4 of the book. Chapter 2, Parallel Programming Platforms, discusses the physical organization of parallel platforms. It establishes cost metrics that can be used for algorithm design. The objective of this chapter is not to provide an exhaustive treatment of parallel architectures; rather, it aims to provide sufficient detail required to use these machines efficiently. Chapter 3, Principles of Parallel Algorithm Design, addresses key factors that contribute to efficient parallel algorithms and presents a suite of techniques that can be applied across a wide range of applications. Chapter 4, Basic Communication Operations, presents a core set of operations that are used throughout the book for facilitating efficient data transfer in parallel algorithms. Finally, Chapter 5, Analytical Modeling of Parallel Programs, deals with metrics for quantifying the performance of a parallel algorithm.
Parallel Programming This section includes Chapters 6 and 7 of the book. Chapter 6, Programming Using the Message-Passing Paradigm, focuses on the Message Passing Interface (MPI) for programming message passing platforms, including clusters. Chapter 7, Programming Shared Address Space Platforms, deals with programming paradigms such as threads and directive based approaches. Using paradigms such as POSIX threads and OpenMP, it describes various features necessary for programming shared-address-space parallel machines. Both of these chapters illustrate various programming concepts using a variety of examples of parallel programs.
Non-numerical Algorithms Chapters 9-12 present parallel non-numerical algorithms. Chapter 9 addresses sorting algorithms such as bitonic sort, bubble sort and its variants, quicksort, sample sort, and shellsort. Chapter 10 describes algorithms for various graph theory problems such as minimum spanning tree, shortest paths, and connected components. Algorithms for sparse graphs are also discussed. Chapter 11 addresses search-based methods such as branch-and-bound and heuristic search for combinatorial problems. Chapter 12 classifies and presents parallel formulations for a variety of dynamic programming algorithms.
Numerical Algorithms Chapters 8 and 13 present parallel numerical algorithms. Chapter 8 covers basic operations on dense matrices such as matrix multiplication, matrix-vector multiplication, and Gaussian elimination. This chapter is included before non-numerical algorithms, as the techniques for partitioning and assigning matrices to processors are common to many non-numerical algorithms. Furthermore, matrix-vector and matrix-matrix multiplication algorithms form the kernels of many graph algorithms. Chapter 13 describes algorithms for computing Fast Fourier Transforms.