Download or read book Vector and parallel processors in computational science Proceedings of the international conference Vector and parallel processors in computational science Proceedings of the International Conference on Vector and Parallel Processors in Computational Science 3 written by and published by . This book was released on 1987 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vector and Parallel Processors in Computational Science written by and published by . This book was released on 1982 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Parallel and Vector Solution of Linear Systems written by James M. Ortega and published by Springer Science & Business Media. This book was released on 1988-04-30 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the origins of parallel computing go back to the last century, it was only in the 1970s that parallel and vector computers became available to the scientific community. The first of these machines-the 64 processor llliac IV and the vector computers built by Texas Instruments, Control Data Corporation, and then CRA Y Research Corporation-had a somewhat limited impact. They were few in number and available mostly to workers in a few government laboratories. By now, however, the trickle has become a flood. There are over 200 large-scale vector computers now installed, not only in government laboratories but also in universities and in an increasing diversity of industries. Moreover, the National Science Foundation's Super computing Centers have made large vector computers widely available to the academic community. In addition, smaller, very cost-effective vector computers are being manufactured by a number of companies. Parallelism in computers has also progressed rapidly. The largest super computers now consist of several vector processors working in parallel. Although the number of processors in such machines is still relatively small (up to 8), it is expected that an increasing number of processors will be added in the near future (to a total of 16 or 32). Moreover, there are a myriad of research projects to build machines with hundreds, thousands, or even more processors. Indeed, several companies are now selling parallel machines, some with as many as hundreds, or even tens of thousands, of processors.
Download or read book Vector and Parallel Processors in Computational Science written by Leonard Michael Delves and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vector and Parallel Processors in Computational Science III written by L. M. Delves and published by . This book was released on 1988 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vector and Parallel Processors in Computational Science written by and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the International Conference on Vector and Parallel Processors in Computational Science III written by Leonard M. Delves and published by . This book was released on 1988 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the International Conference on Vector and Parallel Processors in Computational Science III written by and published by . This book was released on 1988 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parallel Processing for Scientific Computing written by Michael A. Heroux and published by SIAM. This book was released on 2006-01-01 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Vector and Parallel Processors in Computational Science II written by and published by . This book was released on 1984 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parallel Processing for Scientific Computing written by Michael A. Heroux and published by SIAM. This book was released on 2006-01-01 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Vector and Parallel Processors in Computational Science written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vector and Parallel Processors in Computational Science written by Iain S. Duff and published by North Holland. This book was released on 1985 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vector and Parallel Processors in Computational Science written by P. G. Burke and published by . This book was released on 1982 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Introduction to Parallel and Vector Solution of Linear Systems written by James M. Ortega and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the origins of parallel computing go back to the last century, it was only in the 1970s that parallel and vector computers became available to the scientific community. The first of these machines-the 64 processor llliac IV and the vector computers built by Texas Instruments, Control Data Corporation, and then CRA Y Research Corporation-had a somewhat limited impact. They were few in number and available mostly to workers in a few government laboratories. By now, however, the trickle has become a flood. There are over 200 large-scale vector computers now installed, not only in government laboratories but also in universities and in an increasing diversity of industries. Moreover, the National Science Foundation's Super computing Centers have made large vector computers widely available to the academic community. In addition, smaller, very cost-effective vector computers are being manufactured by a number of companies. Parallelism in computers has also progressed rapidly. The largest super computers now consist of several vector processors working in parallel. Although the number of processors in such machines is still relatively small (up to 8), it is expected that an increasing number of processors will be added in the near future (to a total of 16 or 32). Moreover, there are a myriad of research projects to build machines with hundreds, thousands, or even more processors. Indeed, several companies are now selling parallel machines, some with as many as hundreds, or even tens of thousands, of processors.
Download or read book The Art of High Performance Computing for Computational Science Vol 1 written by Masaaki Geshi and published by Springer. This book was released on 2019-05-14 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides basic and practical techniques of parallel computing and related methods of numerical analysis for researchers who conduct numerical calculation and simulation. Although the techniques provided in this book are field-independent, these methods can be used in fields such as physics, chemistry, biology, earth sciences, space science, meteorology, disaster prevention, and manufacturing. In particular, those who develop software code in these areas will find this book useful. The contents are suitable for graduate students and researchers in computational science rather than novices at programming or informed experts in computer science. Starting with an introduction to the recent trends in computer architecture and parallel processing, Chapter 1 explains the basic knowledge of speedup programs with simple examples of numerical computing. Chapters 2 – 4 detail the basics of parallel programming, the message passing interface (MPI), and OpenMP and discuss hybrid parallelization techniques. Showing an actual example of adaptation, Chapter 5 gives an overview of performance tuning and communication optimizations. To deal with dense matrix calculations, Chapter 6 details the basics and practice of linear algebra calculation libraries BLAS and LAPACK, including some examples that can be easily reproduced by readers using free software. Focusing on sparse matrix calculations, Chapter 7 explains high performance algorithms for numerical linear algebra. Chapter 8 introduces the fast Fourier transform in large-scale systems from the basics. Chapter 9 explains optimization and related topics such as debug methods and version control systems. Chapter 10 discusses techniques for increasing computation accuracy as an essential topic in numerical calculation. This is the first of the two volumes that grew out of a series of lectures in the K computer project in Japan. The second volume will focus on advanced techniques and examples of applications in materials science.
