Mathematics of Computing -- Parallelism.

Mathematics of Computing -- Parallelism.

Mathematics of Computing -- Parallelism.

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and essential notions of scheduling. The book extract

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 programming: 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 models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers

The matching problem is central to graph theory and the theory of algorithms. This book provides a comprehensive and straightforward introduction to the basic methods for designing efficient parallel algorithms for graph matching problems. Written for students at the beginning graduate level, the exposition is largely self-contained and example-driven; prerequisites have been kept to a minimum by including relevant background material. The book contains full details of several new techniques and will be of interest to researchers in computer science, operations research, discrete mathematics, and electrical engineering. The main theoretical tools are presented in three independent chapters, devoted to combinatorial tools, probabilistic tools, and algebraic tools. One of the goals of the book is to show how these three approaches can be combined to develop efficient parallel algorithms. The book represents a meeting point of interesting algorithmic techniques and opens up new algebraic and geometric areas.