Author : Guy E. Blelloch
Publisher : MIT Press (MA)
Page : 288 pages
File Size : 49,26 MB
Release : 1990
Category : Computers
ISBN :
Mathematics of Computing -- Parallelism.
Author : Guy-Rene Perrin
Publisher : Springer Science & Business Media
Page : 316 pages
File Size : 14,8 MB
Release : 1996-09-11
Category : Computers
ISBN : 9783540617365
This monograph-like book assembles the thorougly revised and cross-reviewed lectures given at the School on Data Parallelism, held in Les Menuires, France, in May 1996. The book is a unique survey on the current status and future perspectives of the currently very promising and popular data parallel programming model. Much attention is paid to the style of writing and complementary coverage of the relevant issues throughout the 12 chapters. Thus these lecture notes are ideally suited for advanced courses or self-instruction on data parallel programming. Furthermore, the book is indispensable reading for anybody doing research in data parallel programming and related areas.
Author : I. Foster
Publisher : IOS Press
Page : 806 pages
File Size : 50,86 MB
Release : 2020-03-25
Category : Computers
ISBN : 1643680714
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 operational. This achievement resulted in a rapidly growing interest in affordable parallel computing for solving compute intensive and large scale problems. It also directly lead to the founding of the Parco conference series. Starting in 1983, the International Conference on Parallel Computing, ParCo, has long been a leading venue for discussions of important developments, applications, and future trends in cluster computing, parallel computing, and high-performance computing. ParCo2019, held in Prague, Czech Republic, from 10 – 13 September 2019, was no exception. Its papers, invited talks, and specialized mini-symposia addressed cutting-edge topics in computer architectures, programming methods for specialized devices such as field programmable gate arrays (FPGAs) and graphical processing units (GPUs), innovative applications of parallel computers, approaches to reproducibility in parallel computations, and other relevant areas. This book presents the proceedings of ParCo2019, with the goal of making the many fascinating topics discussed at the meeting accessible to a broader audience. The proceedings contains 57 contributions in total, all of which have been peer-reviewed after their presentation. These papers give a wide ranging overview of the current status of research, developments, and applications in parallel computing.
Author : David B. Kirk
Publisher : Newnes
Page : 519 pages
File Size : 27,66 MB
Release : 2012-12-31
Category : Computers
ISBN : 0123914183
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Author : Philip J. Hatcher
Publisher : MIT Press
Page : 262 pages
File Size : 21,27 MB
Release : 1991
Category : Computers
ISBN : 9780262082051
Mathematics of Computing -- Parallelism.
Author : Ananth Grama
Publisher : Pearson Education
Page : 664 pages
File Size : 37,14 MB
Release : 2003
Category : Computers
ISBN : 9780201648652
A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.
Author : Foster
Publisher :
Page : 381 pages
File Size : 19,24 MB
Release : 2002
Category : Computer programming
ISBN : 9787115103475
国外著名高等院校信息科学与技术优秀教材
Author : Guy E. Blelloch
Publisher : American Mathematical Soc.
Page : 413 pages
File Size : 17,90 MB
Release : 1994
Category : Computers
ISBN : 0821802534
This volume contains papers presented at the DIMACS workshop on Specification of Parallel Algorithms, held in May 1994 at Princeton University. The goal of the workshop was to bring together some of the best researchers in parallel languages, algorithms, and systems to present and discuss recent developments in their areas of expertise. Among the topics discussed were new specification techniques for concurrent and distributed systems, behavioral and operational specification techniques, new parallel language and system abstractions, novel concurrent architectures and systems, large-scale parallel systems, specification tools and environments, and proof techniques for concurrent systems.
Author : Roger D. Peng
Publisher :
Page : 0 pages
File Size : 27,89 MB
Release : 2012-04-19
Category : R (Computer program language)
ISBN : 9781365056826
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.
Author : Alan Gibbons
Publisher : Cambridge University Press
Page : 452 pages
File Size : 27,74 MB
Release : 1993-03-18
Category : Computers
ISBN : 9780521415569
The foundations of parallel computation, especially the efficiency of computation, are the concern of this book. Distinguished international researchers have contributed fifteen chapters which together form a coherent stream taking the reader who has little prior knowledge of the field to a position of being familiar with leading edge issues. The book may also function as a source of teaching material and reference for researchers. The first part is devoted to the Parallel Random Access Machine (P-RAM) model of parallel computation. The initial chapters justify and define the model, which is then used for the development of algorithm design in a variety of application areas such as deterministic algorithms, randomisation and algorithm resilience. The second part deals with distributed memory models of computation. The question of efficiently implementing P-RAM algorithms within these models is addressed as are the immensely interesting prospects for general purpose parallel computation.
