GPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. This book is intended to help those who are facing the challenge of programming systems to effectively use GPUs to achieve efficiency and performance goals. It offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Readers will learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution. The insights and ideas as well as practical hands-on skills in the book can be immediately put to use. Computer programmers, software engineers, hardware engineers, and computer science students will find this volume a helpful resource. For useful source codes discussed throughout the book, the editors invite readers to the following website: ..." Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use

Produk Detail:

  • Author : Anonim
  • Publisher : Elsevier
  • Pages : 886 pages
  • ISBN : 9780123849892
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKGPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 13 January 2011
GET THIS BOOKGPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. This book is intended to help those who

GPU Computing Gems Jade Edition

GPU Computing Gems Jade Edition
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 02 November 2011
GET THIS BOOKGPU Computing Gems Jade Edition

GPU Computing Gems, Jade Edition, offers hands-on, proven techniques for general purpose GPU programming based on the successful application experiences of leading researchers and developers. One of few resources available that distills the best practices of the community of CUDA programmers, this second edition contains 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, and green computing. It covers new tools and frameworks for productive GPU computing application development and provides immediate benefit to researchers

CUDA Application Design and Development

CUDA Application Design and Development
  • Author : Rob Farber
  • Publisher : Elsevier
  • Release : 09 March 2021
GET THIS BOOKCUDA Application Design and Development

Machine generated contents note: 1. How to think in CUDA 2. Tools to build, debug and profile 3. The GPU performance envelope 4. The CUDA memory subsystems 5. Exploiting the CUDA execution grid 6. MultiGPU applications and scaling 7. Numerical CUDA, libraries and high-level language bindings 8. Mixing CUDA with rendering 9. High Performance Machine Learning 10. Scientific Visualization 11. Multimedia with OpenCV 12. Ultra Low-power Devices: Tegra.

CUDA Programming

CUDA Programming
  • Author : Shane Cook
  • Publisher : Newnes
  • Release : 09 March 2021
GET THIS BOOKCUDA Programming

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

Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL
  • Author : Benedict Gaster,Lee Howes,David R. Kaeli,Perhaad Mistry,Dana Schaa
  • Publisher : Elsevier
  • Release : 30 September 2011
GET THIS BOOKHeterogeneous Computing with OpenCL

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

Programming Massively Parallel Processors

Programming Massively Parallel Processors
  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Elsevier
  • Release : 22 February 2010
GET THIS BOOKProgramming Massively Parallel Processors

Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable to high-performance parallel computing. It utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for

Cloud Computing

Cloud Computing
  • Author : Dan C. Marinescu
  • Publisher : Newnes
  • Release : 30 May 2013
GET THIS BOOKCloud Computing

Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across

MATLAB for Neuroscientists

MATLAB for Neuroscientists
  • Author : Pascal Wallisch,Michael E. Lusignan,Marc D. Benayoun,Tanya I. Baker,Adam Seth Dickey,Nicholas G. Hatsopoulos
  • Publisher : Academic Press
  • Release : 09 January 2014
GET THIS BOOKMATLAB for Neuroscientists

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional

Programming Massively Parallel Processors

Programming Massively Parallel Processors
  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Morgan Kaufmann
  • Release : 24 November 2016
GET THIS BOOKProgramming Massively Parallel Processors

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,

GPU Gems 3

GPU Gems 3
  • Author : Hubert Nguyen
  • Publisher : Addison-Wesley Professional
  • Release : 09 March 2021
GET THIS BOOKGPU Gems 3

Still more useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.

HOX Genes

HOX Genes
  • Author : Anonim
  • Publisher : Academic Press
  • Release : 19 July 2009
GET THIS BOOKHOX Genes

A subgroup of homeobox genes, which play an important role in the developmental processes of a variety of multicellular organisms, Hox genes have been shown to play a critical role in vertebrate pattern formation. Hox genes can be thought of as general purpose control genes—that is, they are similar in many organisms and direct the same processes in a variety of organisms, from mouse, to fly, to human. * Provides researchers an overview and synthesis of the latest research findings

CUDA Fortran for Scientists and Engineers

CUDA Fortran for Scientists and Engineers
  • Author : Gregory Ruetsch,Massimiliano Fatica
  • Publisher : Elsevier
  • Release : 11 September 2013
GET THIS BOOKCUDA Fortran for Scientists and Engineers

CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and

The CUDA Handbook

The CUDA Handbook
  • Author : Nicholas Wilt
  • Publisher : Addison-Wesley
  • Release : 11 June 2013
GET THIS BOOKThe CUDA Handbook

The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers will appreciate the expert coverage of topics such as the driver API and context migration, as

Professional CUDA C Programming

Professional CUDA C Programming
  • Author : John Cheng,Max Grossman,Ty McKercher
  • Publisher : John Wiley & Sons
  • Release : 09 September 2014
GET THIS BOOKProfessional CUDA C Programming

Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers

GPU Programming in MATLAB

GPU Programming in MATLAB
  • Author : Nikolaos Ploskas,Nikolaos Samaras
  • Publisher : Morgan Kaufmann
  • Release : 25 August 2016
GET THIS BOOKGPU Programming in MATLAB

GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage