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Parallel and Distributed Scientific and Engineering Computing

Author: Yi Pan

Publisher: Nova Publishers

Published: 2004

Total Pages: 240

ISBN-13: 9781590339565

In the not too distant future, every researcher and professional in science and engineering fields will have to understand parallel and distributed computing. With hyperthreading in Intel processors, hypertransport links in AMD processors, multi-core silicon in today's high-end microprocessors from IBM and emerging cluster and grid computing, parallel and distributed computers have moved into the mainstream of computing. To fully exploit these advances in computer architectures, researchers and professionals must start to design parallel or distributed software, systems and algorithms for their scientific and engineering applications. Parallel and distributed scientific and engineering computing has become a key technology which will play an important part in determining, or at least shaping, future research and development activities in many academic and industrial branches. This book reports on the recent important advances in the area of parallel and distributed computing for science and engineering applications. Included in the book are selected papers from prestigious workshops such as PACT-SHPSEC, IPDPS-PDSECA and ICPP-HPSECA together with some invited papers from prominent researchers around the world. The book is basically divided into five main sections. These chapters not only provide novel ideas, new experimental results and handful experience in this field, but also stimulate the future research activities in the area of parallel and distributed computing for science and engineering applications.

Programming Models for Parallel Computing

Author: Pavan Balaji

Publisher: MIT Press

Published: 2015-11-06

Total Pages: 488

ISBN-13: 0262528819

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An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. 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. Contributors Timothy 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

High Performance Scientific and Engineering Computing

Author: Laurence Tianruo Yang

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 315

ISBN-13: 1475754027

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High Performance Scientific And Engineering Computing: Hardware/Software Support contains selected chapters on hardware/software support for high performance scientific and engineering computing from prestigious workshops in the fields such as PACT-SHPSEC, IPDPS-PDSECA and ICPP-HPSECA. This edited volume is basically divided into six main sections which include invited material from prominent researchers around the world. We believe all of these contributed chapters and topics not only provide novel ideas, new results and state-of-the-art techniques in this field, but also stimulate the future research activities in the area of high performance computing for science and engineering applications. High Performance Scientific And Engineering Computing: Hardware/Software Support is designed for a professional audience, composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.

Parallel Processing for Scientific Computing

Author: Michael A. Heroux

Publisher: SIAM

Published: 2006-01-01

Total Pages: 407

ISBN-13: 0898716195

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Scientific computing has often been called the third approach to scientific discovery, emerging as a peer to experimentation and theory. Historically, the synergy between experimentation and theory has been well understood: experiments give insight into possible theories, theories inspire experiments, experiments reinforce or invalidate theories, and so on. As scientific computing has evolved to produce results that meet or exceed the quality of experimental and theoretical results, it has become indispensable.Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering. This edited volume serves as an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for graduate and senior-level undergraduate students interested in computational modeling and simulation and related computer science and applied mathematics aspects.Contents List of Figures; List of Tables; Preface; Chapter 1: Frontiers of Scientific Computing: An Overview; Part I: Performance Modeling, Analysis and Optimization. Chapter 2: Performance Analysis: From Art to Science; Chapter 3: Approaches to Architecture-Aware Parallel Scientific Computation; Chapter 4: Achieving High Performance on the BlueGene/L Supercomputer; Chapter 5: Performance Evaluation and Modeling of Ultra-Scale Systems; Part II: Parallel Algorithms and Enabling Technologies. Chapter 6: Partitioning and Load Balancing; Chapter 7: Combinatorial Parallel and Scientific Computing; Chapter 8: Parallel Adaptive Mesh Refinement; Chapter 9: Parallel Sparse Solvers, Preconditioners, and Their Applications; Chapter 10: A Survey of Parallelization Techniques for Multigrid Solvers; Chapter 11: Fault Tolerance in Large-Scale Scientific Computing; Part III: Tools and Frameworks for Parallel Applications. Chapter 12: Parallel Tools and Environments: A Survey; Chapter 13: Parallel Linear Algebra Software; Chapter 14: High-Performance Component Software Systems; Chapter 15: Integrating Component-Based Scientific Computing Software; Part IV: Applications of Parallel Computing. Chapter 16: Parallel Algorithms for PDE-Constrained Optimization; Chapter 17: Massively Parallel Mixed-Integer Programming; Chapter 18: Parallel Methods and Software for Multicomponent Simulations; Chapter 19: Parallel Computational Biology; Chapter 20: Opportunities and Challenges for Parallel Computing in Science and Engineering; Index.

Topics in Parallel and Distributed Computing

Author: Sushil K Prasad

Publisher: Morgan Kaufmann

Published: 2015-09-16

Total Pages: 359

ISBN-13: 0128039388

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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. Contributed and developed by the leading minds in parallel computing research and instruction Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline Succinctly addresses a range of parallel and distributed computing topics Pedagogically designed to ensure understanding by experienced engineers and newcomers 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

Advances in Parallel & Distributed Processing, and Applications

Author: Hamid R. Arabnia

Publisher: Springer Nature

Published: 2021-10-18

Total Pages: 1201

ISBN-13: 3030699846

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The book presents the proceedings of four conferences: The 26th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'20), The 18th International Conference on Scientific Computing (CSC'20); The 17th International Conference on Modeling, Simulation and Visualization Methods (MSV'20); and The 16th International Conference on Grid, Cloud, and Cluster Computing (GCC'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students. Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the research tracks Parallel and Distributed Processing, Scientific Computing, Modeling, Simulation and Visualization, and Grid, Cloud, and Cluster Computing; Features papers from PDPTA’20, CSC’20, MSV’20, and GCC’20.

Applied Parallel and Distributed Computing

Author: Yi Pan

Publisher: Nova Science Pub Incorporated

Published: 2005

Total Pages: 187

ISBN-13: 9781594541742

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In the not too distant future, every researcher and professional in science and engineering fields will have to understand parallel and distributed computing. With hyperthreading in Intel processors, hypertransport links in AMD processors, multi-core silicon in today's high-end microprocessors from IBM and emerging cluster and grid computing, parallel and distributed computers have moved into the mainstream of computing. To fully exploit these advances in computer architectures, researchers and professionals must start to design parallel or distributed software, systems and algorithms for their scientific and engineering applications. Parallel and distributed scientific and engineering computing has become a key technology which will play an important part in determining, or at least shaping, future research and development activities in many academic and industrial branches. This book reports on the recent important advances in the area of parallel and distributed computing for science and engineering applications. Included in the book are selected papers from prestigious workshops such as PACT-SHPSEC, IPDPS-PDSECA and ICPP-HPSECA together with some invited papers from prominent researchers around the world. The book is divided into five main sections. These chapters not only provide novel ideas, new experimental results and handful experience in this field, but also stimulate the future research activities in the area of parallel and distributed computing for science and engineering applications.

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

Author: Roger Lee

Publisher: Springer

Published: 2014-09-02

Total Pages: 199

ISBN-13: 331910389X

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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. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.

Scientific Parallel Computing

Author: L. Ridgway Scott

Publisher: Princeton University Press

Published: 2021-03-09

Total Pages: 392

ISBN-13: 0691227659

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What does Google's management of billions of Web pages have in common with analysis of a genome with billions of nucleotides? Both apply methods that coordinate many processors to accomplish a single task. From mining genomes to the World Wide Web, from modeling financial markets to global weather patterns, parallel computing enables computations that would otherwise be impractical if not impossible with sequential approaches alone. Its fundamental role as an enabler of simulations and data analysis continues an advance in a wide range of application areas. Scientific Parallel Computing is the first textbook to integrate all the fundamentals of parallel computing in a single volume while also providing a basis for a deeper understanding of the subject. Designed for graduate and advanced undergraduate courses in the sciences and in engineering, computer science, and mathematics, it focuses on the three key areas of algorithms, architecture, languages, and their crucial synthesis in performance. The book's computational examples, whose math prerequisites are not beyond the level of advanced calculus, derive from a breadth of topics in scientific and engineering simulation and data analysis. The programming exercises presented early in the book are designed to bring students up to speed quickly, while the book later develops projects challenging enough to guide students toward research questions in the field. The new paradigm of cluster computing is fully addressed. A supporting web site provides access to all the codes and software mentioned in the book, and offers topical information on popular parallel computing systems. Integrates all the fundamentals of parallel computing essential for today's high-performance requirements Ideal for graduate and advanced undergraduate students in the sciences and in engineering, computer science, and mathematics Extensive programming and theoretical exercises enable students to write parallel codes quickly More challenging projects later in the book introduce research questions New paradigm of cluster computing fully addressed Supporting web site provides access to all the codes and software mentioned in the book

Assignment Problems in Parallel and Distributed Computing

Author: Shahid H. Bokhari

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 167

ISBN-13: 1461320038

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This book has been written for practitioners, researchers and stu dents in the fields of parallel and distributed computing. Its objective is to provide detailed coverage of the applications of graph theoretic tech niques to the problems of matching resources and requirements in multi ple computer systems. There has been considerable research in this area over the last decade and intense work continues even as this is being written. For the practitioner, this book serves as a rich source of solution techniques for problems that are routinely encountered in the real world. Algorithms are presented in sufficient detail to permit easy implementa tion; background material and fundamental concepts are covered in full. The researcher will find a clear exposition of graph theoretic tech niques applied to parallel and distributed computing. Research results are covered and many hitherto unpublished spanning the last decade results by the author are included. There are many unsolved problems in this field-it is hoped that this book will stimulate further research.