The purpose of the 12th Conference Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2011) held on July 6-8, 2011 in Sydney, Australia was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of computer and information sciences, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.
The conference organizers selected 14 outstanding papers from SNPD 2011, all of which you will find in this volume of Springer s Studies in Computational Intelligence. "
Описание: This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 - July 2, 2014 in Las Vegas Nevada, USA.
Автор: Prasad Sushil Название: Topics in Parallel and Distributed Computing ISBN: 0128038993 ISBN-13(EAN): 9780128038994 Издательство: Elsevier Science Рейтинг: Цена: 9264.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline.
The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology.
However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists.
This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula.
This book aims to provide a deep look into Italian actions taken in some fields of science and high performance computing (HPC), and the Italian effort to bridge the HPC gap with respect to Europe. The Italian PON ReCaS Project is written for graduate readers and professionals in the field of high performance computing. It presents and discusses innovative and important technological solutions, and describes interesting results in various fields of application.
ReCaS stands for "Rete di Calcolo per SuperB e altre applicazioni" and is a computing network infrastructure in Southern Italy devoted to scientific and non-scientific applications within the vision of a common European infrastructure for computing, storage and network. The ReCaS project is part of the 2007-2013 European Union strategy, and was funded by the Italian Ministry of Research and Education (MIUR) for the development and enhancement of a distributed computing infrastructure of the Grid/Cloud type over the four EU 'Convergence' regions in Southern Italy: Campania, Puglia and Sicily and Calabria.
The network will be open and accessible to all researchers, public and private, and will be characterized by unprecedented computing power and storage capacity. Posted in the European Grid Infrastructure EGI, ReCaS is also an opportunity to the countries of the Mediterranean area and extends the potential of the current network.
Автор: Magoules Frdric Название: Parallel Scientific Computing ISBN: 1848215819 ISBN-13(EAN): 9781848215818 Издательство: Wiley Рейтинг: Цена: 22010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Parallel Computing presents scientific computing techniques applied to parallel computing for the numerical simulation of large-scale problems, which result from systems modeled by partial differential equations.
Описание: Addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks With concerns about global energy consumption at an all-time high, improving computer networks energy efficiency is becoming an increasingly important topic.
Автор: Aubanel Название: Elements of Parallel Computing ISBN: 1498727891 ISBN-13(EAN): 9781498727891 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns. The aim is to facilitate the teaching of parallel programming by surveying some key algorithmic structures and programming models, together with an abstract representation of the underlying hardware. The presentation is friendly and informal. The content of the book is language neutral, using pseudocode that represents common programming language models.
The first five chapters present core concepts in parallel computing. SIMD, shared memory, and distributed memory machine models are covered, along with a brief discussion of what their execution models look like. The book also discusses decomposition as a fundamental activity in parallel algorithmic design, starting with a naive example, and continuing with a discussion of some key algorithmic structures. Important programming models are presented in depth, as well as important concepts of performance analysis, including work-depth analysis of task graphs, communication analysis of distributed memory algorithms, key performance metrics, and a discussion of barriers to obtaining good performance.
The second part of the book presents three case studies that reinforce the concepts of the earlier chapters. One feature of these chapters is to contrast different solutions to the same problem, using select problems that aren't discussed frequently in parallel computing textbooks. They include the Single Source Shortest Path Problem, the Eikonal equation, and a classical computational geometry problem: computation of the two-dimensional convex hull. After presenting the problem and sequential algorithms, each chapter first discusses the sources of parallelism then surveys parallel algorithms.
Описание: . GPU-based Parallel Implementation of Swarm Intelligence Algorithms combines and covers two emerging areas attracting increased attention and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform. GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone. . This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research.
Автор: Balaji Pavan Название: Programming Models for Parallel Computing ISBN: 0262528819 ISBN-13(EAN): 9780262528818 Издательство: MIT Press Рейтинг: Цена: 10157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today.
The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations.
ContributorsTimothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng
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