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DOWNLOAD [PDF] {EPUB} GPU Parallel Program Development Using CUDA

GPU Parallel Program Development Using CUDA by Tolga Soyata

Book GPU Parallel Program Development Using CUDA


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GPU Parallel Program Development Using CUDA Tolga Soyata ebook

  • Page: 476
  • Format: pdf
  • ISBN: 9781498750752
  • Publisher: Taylor & Francis

 


 

GPU Parallel Program Development Using CUDA Tolga Soyata ebook

GPU Parallel Program Development Using CUDA by Tolga Soyata 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 using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs. Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple’s Swift and Metal,) and the deep learning library cuDNN.

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Chapter 1 Introduction to CPU Parallel Programming 3 1.1 EVOLUTION OF PARALLEL PROGRAMMING 3 1.2 MORE CORES, MORE PARALLELISM 4 1.3 CORES VERSUS THREADS 5 1.3.1 More Threads or More Cores to Parallelize? 5 1.3.2 In uence of Core Resource Sharing 7 1.3.3 In uence of Memory Resource Sharing 7 1.4 OUR FIRST SERIAL PROGRAM 8 Tolga Soyata: GPU Parallel Program Development Using CUDA ...
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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. (PDF) GPU Parallel Program Development Using CUDA
PDF | This book teaches CPU and GPU parallel programming. Although the Nvidia CUDA platform is the primary focus of the book, a chapter is included with an introduction to Open CL. For CPU Cuda By Example | Download eBook pdf, epub, tuebl, mobi
Format Available : PDF, ePub, Mobi Total Read : 76 Total Download : 696 File Size : 45,8 Mb. Description : 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.



 



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