Search Results for "heterogeneous-computing-with-opencl-2-0"

Heterogeneous Computing with OpenCL 2.0

Heterogeneous Computing with OpenCL 2.0

  • Author: David R. Kaeli,Perhaad Mistry,Dana Schaa,Dong Ping Zhang
  • Publisher: Morgan Kaufmann
  • ISBN: 0128016493
  • Category: Computers
  • Page: 330
  • View: 791
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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

Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL

  • Author: Benedict Gaster
  • Publisher: Newnes
  • ISBN: 0124058949
  • Category: Computers
  • Page: 291
  • View: 7727
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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

Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL

Revised OpenCL 1.2 Edition

  • Author: Benedict Gaster,Lee Howes,David R. Kaeli,Perhaad Mistry,Dana Schaa
  • Publisher: Newnes
  • ISBN: 0124055206
  • Category: Computers
  • Page: 308
  • View: 9755
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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

OpenCL Programming Guide

OpenCL Programming Guide

  • Author: Aaftab Munshi,Benedict Gaster,Timothy G. Mattson,Dan Ginsburg
  • Publisher: Pearson Education
  • ISBN: 9780132594554
  • Category: Computers
  • Page: 648
  • View: 9688
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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/

OpenCL Parallel Programming Development Cookbook

OpenCL Parallel Programming Development Cookbook

  • Author: Raymond Tay
  • Publisher: Packt Publishing Ltd
  • ISBN: 1849694532
  • Category: Computers
  • Page: 302
  • View: 3795
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OpenCL Parallel Programming Development Cookbook will provide a set of advanced recipes that can be utilized to optimize existing code. This book is therefore ideal for experienced developers with a working knowledge of C/C++ and OpenCL.This book is intended for software developers who have often wondered what to do with that newly bought CPU or GPU they bought other than using it for playing computer games; this book is also for developers who have a working knowledge of C/C++ and who want to learn how to write parallel programs in OpenCL so that life isn't too boring.

Design of FPGA-Based Computing Systems with OpenCL

Design of FPGA-Based Computing Systems with OpenCL

  • Author: Hasitha Muthumala Waidyasooriya,Masanori Hariyama,Kunio Uchiyama
  • Publisher: Springer
  • ISBN: 3319681613
  • Category: Technology & Engineering
  • Page: 126
  • View: 5234
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This book provides wide knowledge about designing FPGA-based heterogeneous computing systems, using a high-level design environment based on OpenCL (Open Computing language), which is called OpenCL for FPGA. The OpenCL-based design methodology will be the key technology to exploit the potential of FPGAs in various applications such as low-power embedded applications and high-performance computing. By understanding the OpenCL-based design methodology, readers can design an entire FPGA-based computing system more easily compared to the conventional HDL-based design, because OpenCL for FPGA takes care of computation on a host, data transfer between a host and an FPGA, computation on an FPGA with a capable of accessing external DDR memories. In the step-by-step way, readers can understand followings: how to set up the design environment how to write better codes systematically considering architectural constraints how to design practical applications

OpenCL Programming by Example

OpenCL Programming by Example

  • Author: Ravishekhar Banger,Koushik Bhattacharyya
  • Publisher: Packt Publishing Ltd
  • ISBN: 1849692351
  • Category: Computers
  • Page: 304
  • View: 1510
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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.

Using OpenCL

Using OpenCL

Programming Massively Parallel Computers

  • Author: Janusz Kowalik,Tadeusz Puźniakowski
  • Publisher: IOS Press
  • ISBN: 1614990298
  • Category: Computers
  • Page: 295
  • View: 5127
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OpenCL in Action

OpenCL in Action

How to Accelerate Graphics and Computation

  • Author: Matthew Scarpino
  • Publisher: Manning Publications
  • ISBN: 9781617290176
  • Category: Computers
  • Page: 434
  • View: 8043
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"OpenCL in Action blends the theory of parallel computing with the practical reality of building high-performance applications using OpenCL. It first guides you through the fundamental data structures in an intuitive manner. Then, it explains techniques for high-speed sorting, image processing, matrix operations, and fast Fourier transform. The book concludes with a deep look at the all-important subject of graphics acceleration. Numerous challenging examples give you different ways to experiment with working code."--Pub. desc.

Programming Massively Parallel Processors

Programming Massively Parallel Processors

A Hands-on Approach

  • Author: David B. Kirk,Wen-mei W. Hwu
  • Publisher: Morgan Kaufmann
  • ISBN: 012811987X
  • Category: Computers
  • Page: 576
  • View: 8633
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Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing Utilizes CUDA version 7.5, NVIDIA's software development tool created specifically for massively parallel environments Contains new and updated case studies Includes coverage of newer libraries, such as CuDNN for Deep Learning

Advances in GPU Research and Practice

Advances in GPU Research and Practice

  • Author: Hamid Sarbazi Azad
  • Publisher: Morgan Kaufmann
  • ISBN: 0128037881
  • Category: Computers
  • Page: 774
  • View: 5008
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Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The topics treated cover a range of issues, ranging from hardware and architectural issues, to high level issues, such as application systems, parallel programming, middleware, and power and energy issues. Divided into six parts, this edited volume provides the latest research on GPU computing. Part I: Architectural Solutions focuses on the architectural topics that improve on performance of GPUs, Part II: System Software discusses OS, compilers, libraries, programming environment, languages, and paradigms that are proposed and analyzed to help and support GPU programmers. Part III: Power and Reliability Issues covers different aspects of energy, power, and reliability concerns in GPUs. Part IV: Performance Analysis illustrates mathematical and analytical techniques to predict different performance metrics in GPUs. Part V: Algorithms presents how to design efficient algorithms and analyze their complexity for GPUs. Part VI: Applications and Related Topics provides use cases and examples of how GPUs are used across many sectors. Discusses how to maximize power and obtain peak reliability when designing, building, and using GPUs Covers system software (OS, compilers), programming environments, languages, and paradigms proposed to help and support GPU programmers Explains how to use mathematical and analytical techniques to predict different performance metrics in GPUs Illustrates the design of efficient GPU algorithms in areas such as bioinformatics, complex systems, social networks, and cryptography Provides applications and use case scenarios in several different verticals, including medicine, social sciences, image processing, and telecommunications

High Performance Parallelism Pearls Volume One

High Performance Parallelism Pearls Volume One

Multicore and Many-core Programming Approaches

  • Author: James Reinders,James Jeffers
  • Publisher: Morgan Kaufmann
  • ISBN: 0128021993
  • Category: Computers
  • Page: 600
  • View: 6105
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High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming – illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocessors and Intel Xeon processors or other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as chemistry, engineering, and environmental science. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of these powerful systems, but also how to leverage parallelism across these heterogeneous systems. Promotes consistent standards-based programming, showing in detail how to code for high performance on multicore processors and Intel® Xeon PhiTM Examples from multiple vertical domains illustrating parallel optimizations to modernize real-world codes Source code available for download to facilitate further exploration

CUDA by Example

CUDA by Example

An Introduction to General-Purpose GPU Programming, Portable Documents

  • Author: Jason Sanders,Edward Kandrot
  • Publisher: Addison-Wesley Professional
  • ISBN: 0132180138
  • Category: Computers
  • Page: 312
  • View: 1953
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CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html

GPGPU Computing with OpenCL

GPGPU Computing with OpenCL

  • Author: Bernhard Manfred Gruber
  • Publisher: N.A
  • ISBN: 9783656829843
  • Category:
  • Page: 132
  • View: 8659
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Bachelor Thesis from the year 2013 in the subject Computer Science - Programming, grade: 1.0, University of Applied Sciences Oberosterreich, Hagenberg, course: Software Engineering, language: English, abstract: This thesis provides an introduction into programming for GPUs using OpenCL. After a historical overview of how graphic cards have evolved, the peculiarities of GPU and CPU hardware are discussed. Based on this knowledge, OpenCL is introduced as an API supporting all kinds of processing hardware. A deeper look into OpenCL's execution and memory model, which allows handling heterogeneous hardware, is rounded off by a simple, yet full example code. The thesis then continues with several implementations of standard algorithms for the GPU. The chosen problems start with matrix multiplication and go along with the all-prefix sum and sorting. As the first problem already offers parallelism naturally, performance analysis and optimization is focused during the first implementation chapter. The all-prefix sum and sorting are both problems being more dicult to split into independent pieces of work. Techniques will be discussed to tackle such kind of problems. Each GPU implementation is benchmarked and compared with one or more traditional CPU approaches. As GPUs and CPUs have different hardware architectures, appropriate algorithms and optimizations have been chosen to solve the problems by exploiting the underlying platform at best.

Heterogeneous System Architecture

Heterogeneous System Architecture

A New Compute Platform Infrastructure

  • Author: Wen-mei W. Hwu
  • Publisher: Morgan Kaufmann
  • ISBN: 0128008016
  • Category: Computers
  • Page: 206
  • View: 1150
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Heterogeneous Systems Architecture - a new compute platform infrastructure presents a next-generation hardware platform, and associated software, that allows processors of different types to work efficiently and cooperatively in shared memory from a single source program. HSA also defines a virtual ISA for parallel routines or kernels, which is vendor and ISA independent thus enabling single source programs to execute across any HSA compliant heterogeneous processer from those used in smartphones to supercomputers. The book begins with an overview of the evolution of heterogeneous parallel processing, associated problems, and how they are overcome with HSA. Later chapters provide a deeper perspective on topics such as the runtime, memory model, queuing, context switching, the architected queuing language, simulators, and tool chains. Finally, three real world examples are presented, which provide an early demonstration of how HSA can deliver significantly higher performance thru C++ based applications. Contributing authors are HSA Foundation members who are experts from both academia and industry. Some of these distinguished authors are listed here in alphabetical order: Yeh-Ching Chung, Benedict R. Gaster, Juan Gómez-Luna, Derek Hower, Lee Howes, Shih-Hao HungThomas B. Jablin, David Kaeli,Phil Rogers, Ben Sander, I-Jui (Ray) Sung. Provides clear and concise explanations of key HSA concepts and fundamentals by expert HSA Specification contributors Explains how performance-bound programming algorithms and application types can be significantly optimized by utilizing HSA hardware and software features Presents HSA simply, clearly, and concisely without reading the detailed HSA Specification documents Demonstrates ideal mapping of processing resources from CPUs to many other heterogeneous processors that comply with HSA Specifications

CUDA for Engineers

CUDA for Engineers

An Introduction to High-Performance Parallel Computing

  • Author: Duane Storti,Mete Yurtoglu
  • Publisher: Addison-Wesley Professional
  • ISBN: 013417755X
  • Category: Computers
  • Page: 352
  • View: 7979
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CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you’ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA’s parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA’s shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations

FPGA Frontiers

FPGA Frontiers

New Applications in Reconfigurable Computing, 2017 Edition

  • Author: Nicole Hemsoth,Timothy Prickett Morgan
  • Publisher: Next Platform Press
  • ISBN: 9780692835463
  • Category:
  • Page: N.A
  • View: 3462
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While field programmable gate arrays (FPGAs) are certainly not new, their time to take the market by force did not fully arrive until 2016, at least for a new wave of applications in research, enterprise, and machine learning. With key acquisitions, highly publicized use cases of FPGAs at scale for real-world applications, and momentum to make programming these devices easier, FPGAs found the limelight-and that story is just beginning. Tracing the progression of FPGA use cases, technology developments, and market trends via the compute infrastructure analysis publication, The Next Platform, authors Nicole Hemsoth and Timothy Prickett Morgan pull together the last year in FPGA developments and offer a synthesized, holistic view of where the industry is heading-and where the new application areas will emerge. From the use of these devices in deep learning and machine learning, high performance computing (HPC), and enterprise applications, the range of FPGA acceleration is growing. In this 2017 edition of the book, readers will see the big picture for FPGAs in terms of past, present, and future and be armed with a sense of direction for new applications and innovations on the device and software sides.

Euro-Par 2012 Parallel Processing

Euro-Par 2012 Parallel Processing

18th International Conference, Euro-Par 2012, Rhodes Island, Greece, August 27-31, 2012. Proceedings

  • Author: Christos Kaklamanis,Theodore Papatheodorou,Paul G. Spirakis
  • Publisher: Springer
  • ISBN: 3642328202
  • Category: Computers
  • Page: 960
  • View: 5604
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This book constitutes the thoroughly refereed proceedings of the 18th International Conference, Euro-Par 2012, held in Rhodes Islands, Greece, in August 2012. The 75 revised full papers presented were carefully reviewed and selected from 228 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance network and communication; mobile and ubiquitous computing; high performance and scientific applications; GPU and accelerators computing.