6 edition of **Algorithms and applications on vector and parallel computers** found in the catalog.

- 348 Want to read
- 3 Currently reading

Published
**1987**
by North-Holland, Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co. in Amsterdam, New York, New York, N.Y., U.S.A
.

Written in English

- Computer programming.,
- Computer algorithms.,
- Supercomputers.

**Edition Notes**

Statement | edited by H.J.J. te Riele, Th.J. Dekker, H.A. van der Vorst. |

Series | Special topics in supercomputing ;, v. 3 |

Contributions | Riele, H. J. J. te, 1947-, Dekker, T. J., Vorst, H. A. van der, 1944-, Colloquium on Numerical Aspects of Vector and Parallel Processors (1985-1986 : Amsterdam, Netherlands) |

Classifications | |
---|---|

LC Classifications | QA76.6 .A4585 1987 |

The Physical Object | |

Pagination | xi, 457 p. : |

Number of Pages | 457 |

ID Numbers | |

Open Library | OL2392752M |

ISBN 10 | 0444703225 |

LC Control Number | 87022244 |

Parallel-Vector Equation Solvers for Finite Element Engineering Applications aims to fill this gap, detailing both the theoretical development and important implementations of equation-solution algorithms. The mathematical background necessary to understand their inception balances well with descriptions of . Despite the ample number of articles on parallel-vector computational algorithms published over the last 20 years, there is a lack of texts in the field customized for senior undergraduate and graduate engineering research. Parallel-Vector Equation Solvers for Finite Element Engineering.

In this work we review the present status of numerical methods for partial differential equations on vector and parallel computers. A discussion of the relevant aspects of these computers and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. a rapid introduction to the world of vector and parallel processing for these linear algebra applications. , the Project Leader for.

In this work we review the present status of numerical methods for partial differential equations on vector and parallel computers. A discussion of the relevant aspects of these computers and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic Cited by: Yang D and Zenios S () A Scalable Parallel Interior Point Algorithm for Stochastic Linear Programmingand Robust Optimization, Computational Optimization and Applications, , (), Online publication date: 1-Jan

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ISBN: OCLC Number: Notes: Papers based on the lectures presented at the Colloquium on Numerical Aspects of Vector and Parallel Processors, held at the Centre for Mathematics and Computer Science, Amsterdam on each last Friday of the month in the period Sept.

June Parallel Algorithms and Applications (Parallel Algorithm Appl) Journal description. Parallel Algorithms and Applications aims to publish high quality scientific papers arising from original. Parallel Algorithms and Parallel Architectures 13 Relating Parallel Algorithm and Parallel Architecture 14 Implementation of Algorithms: A Two-Sided Problem 14 Measuring Beneﬁ ts of Parallel Computing 15 Amdahl’s Law for Multiprocessor Systems 19 Gustafson–Barsis’s Law 21 Applications of Parallel Computing 22File Size: 8MB.

The vector data have been stored in shared storage. This is summarized in the fiture 7 on each subdomain; the method applied is VECGIC-2D Algorithms and applications on vector and parallel computers book. VECTOR OR PARALLEL COMPUTERS The results are summarized in Table 3, for the processor usage consideration and in Figure 8 for the numerical properties of this version of the by: 3.

Book Review: Petascale Computing: Algorithms and Applications by John E. West, for HPCwirePetascale Computing: Algorithms and Applications, edited by David A. Bader (Chapman & Hall/CRC, ), is the first book in CRC's Computational Science Series, edited by Horst Simon at Lawrence Berkeley National Lab/5(2).

The Impact of Vector and Parallel Architectures on the Gaussian Elimination Algorithm an algorithm is restructured into parallel form and efficient implementation is required on this widely used class of parallel computers.

Finally, the book reviews software tools, performance models, and other theoretical issues which are necessary to Cited by: Parallel Computing: Architectures, Algorithms and Applications - Volume 15 Advances in Parallel Computing [C. Bischof, C. Bischof, M. Bucker, P. Gibbon, G. Joubert, T.

Lippert] on *FREE* shipping on qualifying offers. Parallel Computing: Architectures, Algorithms and Applications - Volume 15 Advances in Parallel ComputingAuthor: C. Bischof, M. Bucker, P. Gibbon, G. Joubert, T.

Lippert. Parallel 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 gradient (ICCG) algorithm on the Cray The LEGO BOOST Expert Book: Building and Programming Instructions for 6 additional models based on the Boost-Set Programming Quantum Computers: Essential Algorithms and Code Samples Eric R.

Johnston. out of 5 stars Paperback. $ # Combinatorial Methods with Computer Applications (Discrete Mathematics and Its Applications. 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. Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are presents many algorithms based on the model, ranging from graph algorithms to numerical algorithms, and argues that data-parallel models are not only practical and can be applied to a surprisingly Cited by: The computer exercises focus on several different strategies for optimizing parallel computing code, using a range of programming options and algorithms.

An autograder was created for each exercise. The autograders run the student's codes and provide a score based. Parallel algorithms designed around halo exchange frequently show up not just in mesh-based solvers, as seen in Sectionbut also in sparse linear algebra operations such as the sparse matrix vector multiplication used in the high performance conjugate gradients (HPCG) benchmark presented in.

In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as Random-access rly, many computer science researchers have used a so-called parallel random-access.

Applications of Parallel Processing A presentation by chinmay terse vivek ashokan rahul nair rahul agarwal 2. Numeric weather prediction NWP uses mathematical models of atmosphere and oceans Taking current observations of weather and processing these data with computer models to forecast the future state of weather.

Uses data assimilation to. Massively Parallel Processing Applications and Development Moreover, the multi block implementation of the AOI method is efficient on vector computers. For a real-life application in the Netherlands results will be presented.

Timing results on iPSC parallel computers are presented. A: Programming Tools. Buy Introduction to Parallel Computing: Design and Analysis of Algorithms 2nd edition () by Ananth Grama, Vipin Kumar, Anshul Gupta and George Karypis for up to 90% off at : Addison-Wesley Longman, Inc.

An efficient algorithm, the Simple Parallel Prefix (SPP) algorithm, was previously proposed for solving symmetric Toeplitz tridiagonal systems on SIMD and vector : Markus Hegland.

( views) Vector Models for Data-Parallel Computing by Guy Blelloch - The MIT Press, Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based.

It presents many algorithms based on the model. The subject of this chapter is the design and analysis of parallel algorithms. Most of today’s algorithms are sequential, that is, they specify a sequence of steps in which each step consists of a single operation.

These algorithms are well suited to today’s computers, which basically perform operations in a File Size: KB. Dongarra J.J. (). ‘ Redesigning linear algebra algorithms’, Proc. 1st International Coll. on Vector and Parallel Computing in Scientific Appl., Bulletin de la Direction des Etudes et Recherches, Serie C, pp.

Google ScholarAuthor: C. Lacor.Parallel Algorithms and Cluster Computing Implementations, Algorithms and Applications. Editors (view affiliations) Karl Heinz Hoffmann science problems to the mathematical algorithms and on to the effective implementation of these algorithms on massively parallel and cluster computers we present state-of-the-art methods and technology as.Parallel Algorithm Examples.

We conclude this chapter by presenting four examples of parallel algorithms. We do not concern ourselves here with the process by which these algorithms are derived or with their efficiency; these issues are discussed in Chapters 2 and 3, goal is simply to introduce parallel algorithms and their description in terms of tasks and channels.