CUDA 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 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

Produk Detail:

  • Author : Shane Cook
  • Publisher : Newnes
  • Pages : 576 pages
  • ISBN : 0124159338
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKCUDA Programming

CUDA Programming

CUDA Programming
  • Author : Shane Cook
  • Publisher : Newnes
  • Release : 07 May 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

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

CUDA by Example

CUDA by Example
  • Author : Jason Sanders,Edward Kandrot
  • Publisher : Addison-Wesley Professional
  • Release : 19 July 2010
GET THIS BOOKCUDA by Example

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

Learn CUDA Programming

Learn CUDA Programming
  • Author : Jaegeun Han,Bharatkumar Sharma
  • Publisher : Packt Publishing Ltd
  • Release : 27 September 2019
GET THIS BOOKLearn CUDA Programming

Explore different GPU programming methods using libraries and directives, such as OpenACC, with extension to languages such as C, C++, and Python Key Features Learn parallel programming principles and practices and performance analysis in GPU computing Get to grips with distributed multi GPU programming and other approaches to GPU programming Understand how GPU acceleration in deep learning models can improve their performance Book Description Compute Unified Device Architecture (CUDA) is NVIDIA's GPU computing platform and application programming interface. It's designed

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

Hands-On GPU Programming with Python and CUDA

Hands-On GPU Programming with Python and CUDA
  • Author : Dr. Brian Tuomanen
  • Publisher : Packt Publishing Ltd
  • Release : 27 November 2018
GET THIS BOOKHands-On GPU Programming with Python and CUDA

Build real-world applications by writing effective GPU code, CUDA kernels, and device functions with the latest features of Python 3.7, CUDA 9 and CUDA 10 Key Features Expand your background in GPU programming—PyCUDA, scikit-cuda, and Nsight Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver Apply GPU programming to modern data science applications Book Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler

GPU Parallel Program Development Using CUDA

GPU Parallel Program Development Using CUDA
  • Author : Tolga Soyata
  • Publisher : CRC Press
  • Release : 19 January 2018
GET THIS BOOKGPU Parallel Program Development Using CUDA

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism

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

CUDA Application Design and Development

CUDA Application Design and Development
  • Author : Rob Farber
  • Publisher : Elsevier
  • Release : 07 May 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.

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

GPU Parallel Program Development Using CUDA

GPU Parallel Program Development Using CUDA
  • Author : Tolga Soyata
  • Publisher : CRC Press
  • Release : 19 January 2018
GET THIS BOOKGPU Parallel Program Development Using CUDA

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism

Learning CUDA 10 Programming

Learning CUDA 10 Programming
  • Author : Nathan Weston
  • Publisher : Unknown Publisher
  • Release : 07 May 2021
GET THIS BOOKLearning CUDA 10 Programming

Harness the power of GPUs to speed up your applications About This Video Learn parallel programming principles, practices, and performance analysis in GPU programming Learn to design and implement optimized parallel algorithms Learn to write programs in the CUDA language with the latest CUDA toolkit In Detail Do you want to write GPU-accelerated applications, but don't know how to get started? With CUDA 10, you can easily add GPU processing to your C and C++ projects. CUDA 10 is the de-facto framework

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,