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Parallel Processing for Computer Graphics

Parallel Processing for Computer Graphics PDF Author: Stuart Green
Publisher: Mit Press
ISBN: 9780262570879
Category : Computer graphics.
Languages : en
Pages : 233

Book Description
Green provides background information on both computer graphics and parallel computers and then goes on to describe how a distributed memory multiprocessor can be used to effectively implement the ray tracing algorithm.

Parallel Processing for Computer Graphics

Parallel Processing for Computer Graphics PDF Author: Stuart Green
Publisher: Mit Press
ISBN: 9780262570879
Category : Computer graphics.
Languages : en
Pages : 233

Book Description
Green provides background information on both computer graphics and parallel computers and then goes on to describe how a distributed memory multiprocessor can be used to effectively implement the ray tracing algorithm.

Practical Parallel Rendering

Practical Parallel Rendering PDF Author: Alan Chalmers
Publisher: CRC Press
ISBN: 1439863806
Category : Computers
Languages : en
Pages : 392

Book Description
Meeting the growing demands for speed and quality in rendering computer graphics images requires new techniques. Practical parallel rendering provides one of the most practical solutions. This book addresses the basic issues of rendering within a parallel or distributed computing environment, and considers the strengths and weaknesses of multiprocessor machines and networked render farms for graphics rendering. Case studies of working applications demonstrate, in detail, practical ways of dealing with complex issues involved in parallel processing.

Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF Author: David B. Kirk
Publisher: Newnes
ISBN: 0123914183
Category : Computers
Languages : en
Pages : 519

Book Description
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

High Performance Computing for Computer Graphics and Visualisation

High Performance Computing for Computer Graphics and Visualisation PDF Author: Min Chen
Publisher: Springer Science & Business Media
ISBN: 1447110110
Category : Computers
Languages : en
Pages : 292

Book Description
This book contains mainly a selection of papers that were presented at the International Workshop on High Performance Computing/or Computer Graphics and Visualisation, held in Swansea, United Kingdom on 3-4 July 1995. The workshop was sponsored by the HEFCWI Initiative on ·Parallel Computing - Foundations and Applications·, and it has provided the international computer graphics community with a platform for: • assessing and reviewing the impact of the development of high performance computing on the progress of computer graphics and visualisation; • presenting the current use of high performance computing architecture and software tools in computer graphics and visualisation, and the development of parallel graphics algorithms; • identifying potential high performance computing applications in computer graphics and visualisation, and encouraging members of the graphics community to think about their problems from the perspective of parallelism. The book is divided into six sections. The first section, which acts as the introduction of the book, gives an overview of the current state of the art It contains a comprehensive survey, by Whitman, of parallel algorithms for computer graphics and visualisation; and a discussion, by Hansen, on the past, present and future high performance computing applications in computer graphics and visualisation. The second section is focused on the design and implementation of high performance architecture, software tools and algorithms for surface rendering.

Introduction to Parallel Processing

Introduction to Parallel Processing PDF Author: Behrooz Parhami
Publisher: Springer Science & Business Media
ISBN: 0306469642
Category : Business & Economics
Languages : en
Pages : 512

Book Description
THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of computer technology. At the same time, better understanding of various forms of concurrency, from standard pipelining to massive parallelism, and invention of architectural structures to support a reasonably efficient and user-friendly programming model for such systems, has allowed hardware performance to continue its exponential growth. This trend is expected to continue in the near future. This explosive growth, linked with the expectation that performance will continue its exponential rise with each new generation of hardware and that (in stark contrast to software) computer hardware will function correctly as soon as it comes off the assembly line, has its down side. It has led to unprecedented hardware complexity and almost intolerable dev- opment costs. The challenge facing current and future computer designers is to institute simplicity where we now have complexity; to use fundamental theories being developed in this area to gain performance and ease-of-use benefits from simpler circuits; to understand the interplay between technological capabilities and limitations, on the one hand, and design decisions based on user and application requirements on the other.

Programming Models for Parallel Computing

Programming Models for Parallel Computing PDF Author: Pavan Balaji
Publisher: MIT Press
ISBN: 0262528819
Category : Computers
Languages : en
Pages : 488

Book Description
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

Algorithms and Parallel Computing

Algorithms and Parallel Computing PDF Author: Fayez Gebali
Publisher: John Wiley & Sons
ISBN: 0470934638
Category : Computers
Languages : en
Pages : 372

Book Description
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

Introduction to Parallel Computing

Introduction to Parallel Computing PDF Author: Roman Trobec
Publisher: Springer
ISBN: 3319988336
Category : Computers
Languages : en
Pages : 263

Book Description
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition.

Parallel and Distributed Computer Graphics

Parallel and Distributed Computer Graphics PDF Author: Xavier Pueyo
Publisher: Nova Publishers
ISBN: 9781590331767
Category : Computers
Languages : en
Pages : 188

Book Description
Parallel & Distributed Computer Graphics

Parallel Computing for Data Science

Parallel Computing for Data Science PDF Author: Norman Matloff
Publisher: CRC Press
ISBN: 1466587032
Category : Computers
Languages : en
Pages : 340

Book Description
This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science. The book prepares readers to write effective parallel code in various languages and learn more about different R packages and other tools. It covers the classic n observations, p variables matrix format and common data structures. Many examples illustrate the range of issues encountered in parallel programming.