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GPU Parallel Program Development Using CUDA

####GPU Parallel Program Development Using CUDA Tolga Soyata ebook

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

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.

    Tolga Soyata: GPU Parallel Program Development Using CUDA ...
    'GPU Parallel Program Development Using CUDA' by Tolga Soyata is a digital EPUB ebook for direct download to PC, Mac, Notebook, Tablet, iPad, iPhone, Smartphone, eReader - but not for Kindle. A DRM capable reader equipment is required.
    GPU Parallel Program Development Using CUDA - hds.bme.hu
    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
    Programming On The Gpu With Cuda | Download eBook PDF/EPUB
    Format Available : PDF, ePub, Mobi Total Read : 41 Total Download : 693 File Size : 44,5 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.
    Parallel Programming with CUDA Ian Buck
    M02: High Performance Computing with CUDA. CUDA Programming Model. Parallel code (kernel) is launched and executed on a device by many threads Threads are grouped into thread blocks Parallel code is written for a thread. Each thread is free to execute a unique code path Built-in thread and block ID variables.
    PDF Download Gpu Parallel Program Development Using Cuda Free
    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.