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Hands-On GPU Programming with Python and CUDA

You're reading from   Hands-On GPU Programming with Python and CUDA Explore high-performance parallel computing with CUDA

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788993913
Length 310 pages
Edition 1st Edition
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Author (1):
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Dr. Brian Tuomanen Dr. Brian Tuomanen
Author Profile Icon Dr. Brian Tuomanen
Dr. Brian Tuomanen
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Table of Contents (15) Chapters Close

Preface 1. Why GPU Programming? FREE CHAPTER 2. Setting Up Your GPU Programming Environment 3. Getting Started with PyCUDA 4. Kernels, Threads, Blocks, and Grids 5. Streams, Events, Contexts, and Concurrency 6. Debugging and Profiling Your CUDA Code 7. Using the CUDA Libraries with Scikit-CUDA 8. The CUDA Device Function Libraries and Thrust 9. Implementation of a Deep Neural Network 10. Working with Compiled GPU Code 11. Performance Optimization in CUDA 12. Where to Go from Here 13. Assessment 14. Other Books You May Enjoy

Where to Go from Here

This book has been a journey, much like a daring mountain hike… but now, at last, we have arrived at the end of our trek. We now stand upon the summit of mount introductory-GPU-programming, and we stand proud as we gaze back upon our native village of serial-programming-ville and smile as we think about the quaint naivity of our old one-dimensional programming traditions, where we considered forking a process in Unix to be our entire understanding of the notion of parallel programming. We have braved many pitfalls and dangers to arrive at this point, and we may have even made such mishaps as installing a broken NVIDIA driver module in Linux, or maybe downloading the wrong Visual Studio version over a slow 100k connection while visiting our parents for vacation. But these setbacks were only temporary, leaving wounds that developed into calluses that...

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