Download Full eBooks in PDF
The Opencl Programming Book Parallel Programming For Multicore Cpu And Gpu Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of The Opencl Programming Book Parallel Programming For Multicore Cpu And Gpu book. This book definitely worth reading, it is an incredibly well-written.
Author : Anonim
Publisher : Fixstars
Page : 246 pages
File Size : 49,9 Mb
Release : 2024-06-29
Category : Electronic
ISBN : 8210379456XXX
Author : Gerassimos Barlas
Publisher : Morgan Kaufmann
Page : 1026 pages
File Size : 43,6 Mb
Release : 2022-02-09
Category : Computers
ISBN : 9780128141212
Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing tools, essential for multi-core CPU programming and many-core "massively parallel" computing. Using threads, OpenMP, MPI, CUDA and other state-of-the-art tools, the book teaches the design and development of software capable of taking advantage of modern computing platforms that incorporate CPUs, GPUs and other accelerators. Presenting material refined over more than two decades of teaching parallel computing, author Gerassimos Barlas minimizes the challenge of transitioning from sequential programming to mastering parallel platforms with multiple examples, extensive case studies, and full source code. By using this book, readers will better understand how to develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting parallel machines. Includes comprehensive coverage of all major multi-core and many-core programming tools and platforms, including threads, OpenMP, MPI, CUDA, OpenCL and Thrust Covers the most recent versions of the above at the time of publication Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance Updates in the second edition include the use of the C++17 standard for all sample code, a new chapter on concurrent data structures, a new chapter on OpenCL, and the latest research on load balancing Includes downloadable source code, examples and instructor support materials on the book’s companion website
Author : Ravishekhar Banger,Koushik Bhattacharyya
Publisher : Packt Publishing Ltd
Page : 437 pages
File Size : 41,6 Mb
Release : 2013-12-23
Category : Computers
ISBN : 9781849692359
This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming. If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.
Author : Aaftab Munshi,Benedict Gaster,Timothy G. Mattson,Dan Ginsburg
Publisher : Pearson Education
Page : 649 pages
File Size : 53,5 Mb
Release : 2011-07-07
Category : Computers
ISBN : 9780132594554
Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes Understanding OpenCL’s architecture, concepts, terminology, goals, and rationale Programming with OpenCL C and the runtime API Using buffers, sub-buffers, images, samplers, and events Sharing and synchronizing data with OpenGL and Microsoft’s Direct3D Simplifying development with the C++ Wrapper API Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more Source code for this book is available at https://code.google.com/p/opencl-book-samples/
Author : Janusz Kowalik
Publisher : IOS Press
Page : 312 pages
File Size : 40,6 Mb
Release : 2012
Category : Computers
ISBN : 9781614990291
Author : Benedict Gaster,Lee Howes,David R. Kaeli,Perhaad Mistry,Dana Schaa
Publisher : Newnes
Page : 309 pages
File Size : 55,6 Mb
Release : 2012-11-13
Category : Computers
ISBN : 9780124058941
Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7 This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students. Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications. Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more. Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms
Author : David R. Kaeli,Perhaad Mistry,Dana Schaa,Dong Ping Zhang
Publisher : Morgan Kaufmann
Page : 330 pages
File Size : 48,8 Mb
Release : 2015-06-18
Category : Computers
ISBN : 9780128016497
Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: • Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources • Dynamic parallelism which reduces processor load and avoids bottlenecks • Improved imaging support and integration with OpenGL Designed to work on multiple platforms, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book explores memory spaces, optimization techniques, extensions, debugging and profiling. Multiple case studies and examples illustrate high-performance algorithms, distributing work across heterogeneous systems, embedded domain-specific languages, and will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. Updated content to cover the latest developments in OpenCL 2.0, including improvements in memory handling, parallelism, and imaging support Explanations of principles and strategies to learn parallel programming with OpenCL, from understanding the abstraction models to thoroughly testing and debugging complete applications Example code covering image analytics, web plugins, particle simulations, video editing, performance optimization, and more
Author : Gerassimos Barlas
Publisher : Elsevier
Page : 698 pages
File Size : 54,5 Mb
Release : 2014-12-16
Category : Computers
ISBN : 9780124171404
Multicore and GPU Programming offers broad coverage of the key parallel computing skillsets: multicore CPU programming and manycore "massively parallel" computing. Using threads, OpenMP, MPI, and CUDA, it teaches the design and development of software capable of taking advantage of today’s computing platforms incorporating CPU and GPU hardware and explains how to transition from sequential programming to a parallel computing paradigm. Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge with multiple examples, extensive case studies, and full source code. Using this book, you can develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting multicore machines. Comprehensive coverage of all major multicore programming tools, including threads, OpenMP, MPI, and CUDA Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance Particular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systems Download source code, examples, and instructor support materials on the book's companion website
Author : Benedict Gaster,Lee Howes,David R. Kaeli,Perhaad Mistry,Dana Schaa
Publisher : Elsevier
Page : 296 pages
File Size : 50,5 Mb
Release : 2011-09-30
Category : Computers
ISBN : 9780123877673
Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Intended to support a parallel programming course, Heterogeneous Computing with OpenCL includes detailed examples throughout, plus additional online exercises and other supporting materials. Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications. Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more. Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms
Author : Thomas Rauber,Gudula Rünger
Publisher : Springer Science & Business Media
Page : 523 pages
File Size : 41,7 Mb
Release : 2013-06-13
Category : Computers
ISBN : 9783642378010
Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years.
Author : Shane Cook
Publisher : Newnes
Page : 600 pages
File Size : 46,9 Mb
Release : 2012-12-28
Category : Computers
ISBN : 9780124159884
If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both Detailed instructions help readers optimize the CUDA software development kit Practical techniques illustrate working with memory, threads, algorithms, resources, and more Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets Each chapter includes exercises to test reader knowledge
Author : Tolga Soyata
Publisher : CRC Press
Page : 477 pages
File Size : 42,7 Mb
Release : 2018-01-19
Category : Mathematics
ISBN : 9781498750769
Provides a comprehensive, class-tested introduction to CUDA and GPU programming Covers CPU programming, parallellism, multi-threading, and other key concepts as a basis for understanding GPU programming Uses Nvidia's new platform based on Amazon EC2 and WebGPU Introduces GPU multi-threading and Global Memory, and the use of atomics and libraries on GPUs Includes example applications
Author : Rainer Keller,David Kramer,Jan-Philipp Weiss
Publisher : Springer Science & Business Media
Page : 164 pages
File Size : 43,7 Mb
Release : 2010-10-06
Category : Computers
ISBN : 9783642162329
This state-of-the-art survey features topics related to the impact of multicore and coprocessor technologies in science and for large-scale applications in an interdisciplinary environment. The papers cover all issues of current research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, compilers, hardware-aware computing, heterogeneous platforms, emerging architectures, tools, performance tuning, and requirements for large-scale applications. The contributions presented in this volume offer a survey on the state of the art, the concepts and perspectives for future developments. They are an outcome of an inspiring conference conceived and organized by the editors within the junior scientist program of Heidelberg Academy for Sciences and Humanities titled "Facing the Multicore-Challenge", held at Heidelberg, Germany, in March 2010. The 12 revised full papers presented together with the extended abstracts of 3 invited lectures focus on combination of new aspects of multicore microprocessor technologies, parallel applications, numerical simulation, software development, and tools; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing.
Author : Ravishekhar Banger,Banger Bhattacharyya
Publisher : Packt Pub Limited
Page : 304 pages
File Size : 53,6 Mb
Release : 2013-11
Category : Computers
ISBN : 1849692343
This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming.If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.
Author : Robert Robey,Yuliana Zamora
Publisher : Simon and Schuster
Page : 702 pages
File Size : 54,9 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781638350385
Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code
