3 edition of **Parallel computations** found in the catalog.

Parallel computations

- 115 Want to read
- 23 Currently reading

Published
**1996**
by International Thomson Computer Press in London
.

Written in English

**Edition Notes**

Statement | A. Zomaya. |

Series | Parallel & Distributed Computing Series |

Contributions | Zomaya, Albert Y. |

The Physical Object | |
---|---|

Pagination | (520)p. ; |

Number of Pages | 520 |

ID Numbers | |

Open Library | OL15030811M |

ISBN 10 | 0412599708 |

Prof. Matlo ’s book on the R programming language, The Art of R Programming, was published in His book, Parallel Computation for Data Science, came out in His current book project, From Linear Models to Machine Learning: Predictive Insights through R, will be published in File Size: 1MB. An understanding of the role of parallel algorithms and the technical knowledge for designing and analyzing them are essential to anyone entering the field of parallel computation. Familiarity with the models associated with the algorithms is also essential. Thus, focusing on "models and methods, " author Selim G. Alk presents the following areas of parallel computation: an overview of the.

Hongchin Lin, Yuan-Ching Sheu, in Parallel Computational Fluid Dynamics , 1 INTRODUTION. Parallel computation has drawn more and more attentions in computational physics. The commercial device simulators usually make use of the drift-diffusion method or the energy balance method, which has been implemented in various parallel computers [1, 2]. Purchase Parallel Computational Fluid Dynamics - 1st Edition. Print Book & E-Book. ISBN ,

Parallel computation of rising bubbles using the lattice Boltzmann method on workstation cluster Pages The three-dimensional two-phase flow simulation code based on the two-component two-phase lattice Boltzmann method, in which two distribution functions are used to represent two phases, is developed and parallelized using the MPI library. This book consists of three papers that collect, describe, or reference an extensive selection of important parallel algorithms for matrix computations. Algorithms for matrix computations are among the most widely used computational tools in science and engineering.

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This book organizes content around the twin themes of models of computation and methods of problem solving. It presents models that characterize and distinguish parallel computation — combinational circuits, interconnection networks, and shared memory machines, as well as models which use : $ Parallel computations book Computations focuses on parallel computation, with emphasis on algorithms used in a variety of numerical and physical applications and for many different types of parallel computers.

Topics covered range from vectorization of fast Fourier transforms (FFTs) and of the incomplete Cholesky conjugate Parallel computations book (ICCG) algorithm on the Cray Introduction to Parallel Computing, Second Edition.

Ananth Grama. Anshul Gupta. George Karypis. Vipin Kumar. Increasingly, parallel processing is being seen as the only cost-effective method for the fast solution of computationally large and data-intensive by: 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 by: Written by parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders, this book explains how to design and implement maintainable and efficient parallel algorithms using a composable, structured, scalable, and machine-independent approach to parallel by: The text contains many useful illustrations and various “graphical interpretations” of the computation process.

I always find those helpful in any discussion of parallel action (which is a real brain-twister for an average sequential thinker). Overall, this book was a pleasure to read. Parallel and Distributed Computation: Numerical Methods Dimitri P.

Bertsekas and John N. Tsitsiklis This book was originally published by Prentice-Hall inand republished by Athena Scientific in in paperback form, and in in hardcover. There are many books and there are many types of parallel computing. The book by Quinn "Parallel Programming in C with MPI and OpenMP" is a good tutorial, with lots of examples.

If you want to do MPI or OpenMP that is. I'll leave it to other people to recommend a CUDA book, or pThreads/Cilk et cetera. the PRAM (parallel random-access machine), the VLSI (very large-scale integrated) chip, and a variety of parallel machines.

vii. viii Preface Models of Computation The book covers the traditional topics of formal languages and automata and complexity classesbut alsogivesan introductionto themoremoderntopics ofspace-time tradeoffs, mem-File Size: 4MB. 1 Modeling parallel computations The designer of a sequential algorithm typically formulates the algorithm using an abstract model of computation called the random-access machine (RAM) [2, Chapter 1] model.

In this model, the machine consists of a single processor connected to a memory system. Each basic CPU operation,File Size: KB. Purchase Parallel Computations - 1st Edition.

Print Book & E-Book. ISBNBook Edition: 1. TOPICS IN PARALLEL COMPUTATION 25 Types of parallelism - two extremes 25 Data parallel 25 Task parallel 25 Programming Methodologies 26 Computation Domain Decomposition and Load Balancing 27 Domain Decomposition 27 Load Balancing 27File Size: KB.

Parallel Computing: In the simplest sense, parallel computing is the simultaneous use of multiple compute resources to solve a computational problem: A problem is broken into discrete parts that can be solved concurrently Each part is further broken down to a series of instructions.

Also wanted to know that from which reference book or papers are the concepts in the udacity course on Parallel Computing taught. The History of Parallel Computing goes back far in the past, where the current interest in GPU computing was not yet predictable.

Some important concepts date back to that time, with lots of theoretical activity between and "Parallel Evolutionary Computation" focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and parallel hardware implementations, as well as on their impact on several applications.

The book is divided into four : Hardcover. Recommended Books on Parallel Programming From time to time I get an email asking what books I recommend for people to learn more about parallel programming in general, or about a specific system. You need to ask no more, as this is my list of recommended books.

A clear illustration of how parallel computers can be successfully applied to large-scale scientific computations. This book demonstrates how a variety of applications in physics, biology, mathematics and other sciences were implemented on real parallel computers to produce new scientific results.

The approach used in the “socket” type cluster can also be extended to other parallel cluster management systems which unfortunately are outside the scope of this book. In general, using parallel computation can speed up “embarrassingly parallel” computations, typically with little additional effort.

This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms.

Access-restricted-item true Addeddate Associated-names Rodrigue, G Boxid IA Camera Sony Alpha-A (Control) Collection_setPages:. The Wolfram Language provides a uniquely integrated and automated environment for parallel computing. With zero configuration, full interactivity, and seamless local and network operation, the symbolic character of the Wolfram Language allows immediate support of a variety of existing and new parallel programming paradigms and data-sharing models.This book provides a comprehensive analysis of the most important topics in parallel computation.

It is written so that it may be used as a self-study guide to the field, and researchers in parallel computing will find it a useful reference for many years to come. The first half of the book consists of an introduction to many fundamental issues in parallel computing.Limits to Parallel Computation: P-Completeness Theory RAYMOND GREENLAW University of New Hampshire H.

JAMES HOOVER University of Alberta WALTER L. RUZZO Overview of This Book 17 2 Parallel Models of Computation 19 Introduction 19 The PRAM Model 21 The Boolean Circuit Model 26 Uniform Circuit Families