Parallel Computing: Accelerating Computational Science and Engineering (CSE)

Parallel Computing: Accelerating Computational Science and Engineering (CSE)
Author :
Publisher : IOS Press
Total Pages : 868
Release :
ISBN-10 : 9781614993810
ISBN-13 : 1614993815
Rating : 4/5 (10 Downloads)

Book Synopsis Parallel Computing: Accelerating Computational Science and Engineering (CSE) by : M. Bader

Download or read book Parallel Computing: Accelerating Computational Science and Engineering (CSE) written by M. Bader and published by IOS Press. This book was released on 2014-03-31 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel computing has been the enabling technology of high-end machines for many years. Now, it has finally become the ubiquitous key to the efficient use of any kind of multi-processor computer architecture, from smart phones, tablets, embedded systems and cloud computing up to exascale computers. _x000D_ This book presents the proceedings of ParCo2013 – the latest edition of the biennial International Conference on Parallel Computing – held from 10 to 13 September 2013, in Garching, Germany. The conference focused on several key parallel computing areas. Themes included parallel programming models for multi- and manycore CPUs, GPUs, FPGAs and heterogeneous platforms, the performance engineering processes that must be adapted to efficiently use these new and innovative platforms, novel numerical algorithms and approaches to large-scale simulations of problems in science and engineering._x000D_ The conference programme also included twelve mini-symposia (including an industry session and a special PhD Symposium), which comprehensively represented and intensified the discussion of current hot topics in high performance and parallel computing. These special sessions covered large-scale supercomputing, novel challenges arising from parallel architectures (multi-/manycore, heterogeneous platforms, FPGAs), multi-level algorithms as well as multi-scale, multi-physics and multi-dimensional problems._x000D_ It is clear that parallel computing – including the processing of large data sets (“Big Data”) – will remain a persistent driver of research in all fields of innovative computing, which makes this book relevant to all those with an interest in this field.


Parallel Computing: Accelerating Computational Science and Engineering (CSE) Related Books

Parallel Computing: Accelerating Computational Science and Engineering (CSE)
Language: en
Pages: 868
Authors: M. Bader
Categories: Computers
Type: BOOK - Published: 2014-03-31 - Publisher: IOS Press

DOWNLOAD EBOOK

Parallel computing has been the enabling technology of high-end machines for many years. Now, it has finally become the ubiquitous key to the efficient use of a
Parallel Computing: On the Road to Exascale
Language: en
Pages: 872
Authors: G.R. Joubert
Categories: Computers
Type: BOOK - Published: 2016-04-28 - Publisher: IOS Press

DOWNLOAD EBOOK

As predicted by Gordon E. Moore in 1965, the performance of computer processors increased at an exponential rate. Nevertheless, the increases in computing speed
Software for Exascale Computing - SPPEXA 2013-2015
Language: en
Pages: 557
Authors: Hans-Joachim Bungartz
Categories: Computers
Type: BOOK - Published: 2016-09-14 - Publisher: Springer

DOWNLOAD EBOOK

The research and its outcomes presented in this collection focus on various aspects of high-performance computing (HPC) software and its development which is co
Parallel Computing is Everywhere
Language: en
Pages: 852
Authors: S. Bassini
Categories: Computers
Type: BOOK - Published: 2018-03-07 - Publisher: IOS Press

DOWNLOAD EBOOK

The most powerful computers work by harnessing the combined computational power of millions of processors, and exploiting the full potential of such large-scale
Parallel Computing: Technology Trends
Language: en
Pages: 806
Authors: I. Foster
Categories: Computers
Type: BOOK - Published: 2020-03-25 - Publisher: IOS Press

DOWNLOAD EBOOK

The year 2019 marked four decades of cluster computing, a history that began in 1979 when the first cluster systems using Components Off The Shelf (COTS) became