heterogeneous computing with opencl 2 0

Heterogeneous Computing With OpenCL 2 0
Author: David R. Kaeli
Publisher: Morgan Kaufmann
Release Date: 2015-06-18
Pages: 330
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 2 0  Third Edition
Author: David Kaeli
Publisher:
Release Date: 2015
Pages: 330
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Heterogeneous Computing With OpenCL
Author: Benedict Gaster
Publisher: Elsevier
Release Date: 2012
Pages: 277
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

"Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include different types of hardware: Central Processing Units (CPUs), Digital Signal Processors (DSPs), Graphic Processing Units (GPUs) and Accelerated Processing Units (APUs). Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future.

Using OpenCL
Author: J. Kowalik
Publisher: IOS Press
Release Date: 2012-02-29
Pages: 312
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

In 2011 many computer users were exploring the opportunities and the benefits of the massive parallelism offered by heterogeneous computing. In 2000 the Khronos Group, a not-for-profit industry consortium, was founded to create standard open APIs for parallel computing, graphics and dynamic media. Among them has been OpenCL, an open system for programming heterogeneous computers with components made by multiple manufacturers. This publication explains how heterogeneous computers work and how to program them using OpenCL. It also describes how to combine OpenCL with OpenGL for displaying graphical effects in real time. Chapter 1 describes briefly two older de facto standard and highly successful parallel programming systems: MPI and OpenMP. Collectively, the MPI, OpenMP, and OpenCL systems cover programming of all major parallel architectures: clusters, shared-memory computers, and the newest heterogeneous computers. Chapter 2, the technical core of the book, deals with OpenCL fundamentals: programming, hardware, and the interaction between them. Chapter 3 adds important information about such advanced issues as double-versus-single arithmetic precision, efficiency, memory use, and debugging. Chapters 2 and 3 contain several examples of code and one case study on genetic algorithms. These examples are related to linear algebra operations, which are very common in scientific, industrial, and business applications. Most of the book’s examples can be found on the enclosed CD, which also contains basic projects for Visual Studio, MinGW, and GCC. This supplementary material will assist the reader in getting a quick start on OpenCL projects.

Digital Information Processing And Communications  Part II
Author: Vaclav Snasael
Publisher: Springer
Release Date: 2011-06-28
Pages: 549
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This two-volume-set (CCIS 188 and CCIS 189) constitutes the refereed proceedings of the International Conference on Digital Information Processing and Communications, ICDIPC 2011, held in Ostrava, Czech Republic, in July 2011. The 91 revised full papers of both volumes presented together with 4 invited talks were carefully reviewed and selected from 235 submissions. The papers are organized in topical sections on network security; Web applications; data mining; neural networks; distributed and parallel processing; biometrics technologies; e-learning; information ethics; image processing; information and data management; software engineering; data compression; networks; computer security; hardware and systems; multimedia; ad hoc network; artificial intelligence; signal processing; cloud computing; forensics; security; software and systems; mobile networking; and some miscellaneous topics in digital information and communications.

CUDA By Example
Author: Jason Sanders
Publisher: Addison-Wesley Professional
Release Date: 2010-07-19
Pages: 312
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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

Programming Multicore And Many Core Computing Systems
Author: Sabri Pllana
Publisher: John Wiley & Sons
Release Date: 2017-02-06
Pages: 528
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Programming multi-core and many-core computing systems Sabri Pllana, Linnaeus University, Sweden Fatos Xhafa, Technical University of Catalonia, Spain Provides state-of-the-art methods for programming multi-core and many-core systems The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems. Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream. The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle. Key features: Lessons, challenges, and roadmaps ahead. Contains real world examples and case studies. Helps programmers in mastering the efficient programming of multi-core and many-core systems. The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.

The Leading Edge
Author:
Publisher:
Release Date: 2010
Pages:
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

FPGA Based Implementation Of Signal Processing Systems
Author: Roger Woods
Publisher: John Wiley & Sons
Release Date: 2017-05
Pages: 356
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Revised edition of: FPGA-based implementation of signal processing systems / Roger Woods ... [et al.]. 2008.

CUDA Programming
Author: Shane Cook
Publisher: Morgan Kaufmann
Release Date: 2017-10-01
Pages: 608
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

CUDA Programming: A Developer's Guide to Parallel Computing with GPUs, Second Edition is a fully revised, updated, practical guide that provides a solid foundation for developers learning parallel programming with CUDA. This guide iincludes updates that cover both the Kepler and Maxwell GPUs from NVIDIA, as well as the latest heterogeneous systems from AMD. Suitable for someone without a parallel programming background or previous CUDA experience, as well as those who already have dabbled in GPU programming, the contents range from installation and getting started, to building your own GPU workstation. This revision includes a new chapter on visualizing data, and new content on the latest CUDA features including data caching, shared memory, and dynamic parallelism. Author Shane Cook also covers the latest host systems and changes to the installation process, NVIDIA’s Parallel NSight IDE, and hardware systems that run CUDA applications. The final new chapter looks ahead to future GPU platforms and releases including on-core ARM CPU and NVlink technologies. Provides a solid foundation in how to program GPUs using in CUDA Discusses multiple options such as libraries, OpenCL, OpenACC and other programming languages Explains how to design and optimize code for several generations of GPUs and platforms Covers the latest debugging and profiling tools