Author: Justin R. Smith
Publisher: Oxford University Press on Demand
Release Date: 1993
This text for students and professionals in computer science provides a valuable overview of current knowledge concerning parallel algorithms. These computer operations have recently acquired increased importance due to their ability to enhance the power of computers by permitting multiple processors to work on different parts of a problem independently and simultaneously. This approach has led to solutions of difficult problems in a number of vital fields, including artificial intelligence, image processing, and differential equations. As the first up-to-date summary of the topic, this book will be sought after by researchers, computer science professionals, and advanced students involved in parallel computing and parallel algorithms.
Take advantage of the power of parallel computers with this comprehensive introduction to methods for the design, implementation, and analysis of parallel algorithms. You'll examine many important core topics, including sorting and graph algorithms, discrete optimization techniques, and scientific computing applications, as you consider parallel algorithms for realistic machine models. Features: presents parallel algorithms as a small set of basic data communication operations in order to simplify their design and increase understanding; emphasizes practical issues of performance, efficiency, and scalability; provides a self-contained discussion of the basic concepts of parallel computer architectures; covers algorithms for scientific computation, such as dense and sparse matrix computations, linear system solving, finite elements, and FFT; discusses algorithms for combinatorial optimization, including branch-and-bound, heuristic search, and dynamic programming; incorporates illustrative examples of parallel programs for commercially available computers; and contains extensive figures and examples that illustrate the workings of algorithms on different architectures.
Author: C. Xavier
Publisher: John Wiley & Sons
Release Date: 1998-08-05
Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.
This book covers wealth of important material on parallel algorithms in depth for the solution of problems in a variety of application areas highlighting the importance of parallel graph algorithms. It covers all existing material and research on parallel graph algorithms as well as other important topics relating to parallel algorithms such as: parallel matrix and boolean matrix multiplication algorithms. The book is written for application software designers working in parallel processing environments but will also form an invaluable reference work for researchers.
Author: Dr. DK Sukhani
Release Date: 2017-10-29
Genre: Study Aids
This book is useful for IGNOU MCA students. A perusal of past questions papers gives an idea of the type of questions asked, the paper pattern and so on, it is for this benefit, we provide these IGNOU MCS-031: Design and Analysis of Algorithm Notes. Students are advised to refer these solutions in conjunction with their reference books. It will help you to improve your exam preparations. This book covers Algorithm definition and specification – Design of Algorithms, and Complexity of Algorithms, Asymptotic Notations, Growth of function, Recurrences, Performance analysis – Elementary Data structures:- stacks and queues – trees – dictionaries – priority queues –sets and disjoint set union – graphs – basic traversal and search techniques. Divide – and – conquer:- General method – binary search – merge sort – Quick sort. The Greedy method:-General method – knapsack problem – minimum cost spanning tree – single source shortest path. Dynamic Programming – general method – multistage graphs – all pair shortest path – optimal binary search trees – 0/1 Knapsack – traveling salesman problem – flow shop scheduling. Backtracking:- general method – 8-Queens problem – sum of subsets – graph coloring – Hamiltonian cycles – knapsack problem – Branch and bound:- The Method – 0/1 Knapsack problem – traveling salesperson. Parallel models:-Basic concepts, performance Measures, Parallel Algorithms: Parallel complexity, Analysis of Parallel Addition, Parallel Multiplication and division, parallel. Evaluation of General Arithmetic Expressions, First-Order Linear recurrence. Published by MeetCoogle
Author: Bruno Codenotti
Publisher: World Scientific
Release Date: 1991
This book presents the most important parallel algorithms for the solution of linear systems. Despite the evolution and significance of the field of parallel solution of linear systems, no book is completely dedicated to the subject. People interested in the themes covered by this book belong to two different groups: numerical linear algebra and theoretical computer science, and this is the first effort to produce a useful tool for both. The book is organized as follows: after introducing the general features of parallel algorithms and the most important models of parallel computation, the authors analyze the complexity of solving linear systems in the circuit, PRAM, distributed, and VLSI models. The approach covers both the general case (i.e. dense linear systems without structure) and many important special cases (i.e. banded, sparse, Toeplitz, circulant linear systems).
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 extracts fundamental ideas and algorithmic principles from the mass of parallel algorithm expertise and practical implementations developed over the last few decades. In the first section of the text, the authors cover two classical theoretical models of parallel computation (PRAMs and sorting networks), describe network models for topology and performance, and define several classical communication primitives. The next part deals with parallel algorithms on ring and grid logical topologies as well as the issue of load balancing on heterogeneous computing platforms. The final section presents basic results and approaches for common scheduling problems that arise when developing parallel algorithms. It also discusses advanced scheduling topics, such as divisible load scheduling and steady-state scheduling. With numerous examples and exercises in each chapter, this text encompasses both the theoretical foundations of parallel algorithms and practical parallel algorithm design.
Author: Seyed H Roosta
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.
Author: Yuefan Deng
Publisher: World Scientific
Release Date: 2013
The book provides a practical guide to computational scientists and engineers to help advance their research by exploiting the superpower of supercomputers with many processors and complex networks. This book focuses on the design and analysis of basic parallel algorithms, the key components for composing larger packages for a wide range of applications.
Author: Timo Lepistö
Publisher: Springer Science & Business Media
Release Date: 1988-06-22
This volume contains the proceedings of ICALP 88, held at Tampere University of Technology, Finland, July 11-15, 1988. ICALP 88 is the 15th International Colloquium on Automata, Languages and Programming in a series of meetings sponsored by the European Association for Theoretical Computer Science (EATCS). It is a broadly based conference covering all aspects of theoretical computer science including topics such as computability, automata, formal languages, analysis of algorithms, computational complexity, data types and data structures, theory of data bases and knowledge bases, semantics of programming languages, program specification, transformation and verification, foundations of logic programming, theory of logical design and layout, parallel and distributed computation, theory of concurrency, symbolic and algebraic computation, term rewriting systems, cryptography, and theory of robotics.