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Hands-On GPU Programming with Python and CUDA

DescriptionHands-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;

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

power of GPU Key Features Explore examples to leverage the GPU processing power with OpenCV and CUDA Enhance the performance of algorithms on;

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Professional CUDA C Programming

-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive;

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Hands-On GPU Computing with Python

will learn, by example, how to perform GPU programming with Python, and you'll look at using integrations such as PyCUDA, PyOpenCL, CuPy and;

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Programming Massively Parallel Processors

-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has;

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CUDA Programming

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;

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Introduction to Cuda and Gpu Programming

operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same;

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Image Processing Using CUDA

Nowadays, GPUs are multi-core parallel processors with very high memory bandwidth. Recently for last few years developers and researchers;

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CUDA for Engineers

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do;

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GPU Computing Gems Jade Edition

explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. More specifically, it;

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GPU Parallel Program Development Using CUDA

core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia;

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CUDA Fortran for Scientists and Engineers

experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to;

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CUDA Application Design and Development

needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA;

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Programming Massively Parallel Processors

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic;

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Programming Massively Parallel Processors

of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel;

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GPU Computing Gems Emerald Edition

scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research;

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Programming Massively Parallel Processors

Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques;

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GPU Programming in MATLAB

different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book;

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Python for Beginners: An Introduction to Learn Python Programming with Tutorials and Hands-On Examples

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Programming Arcgis 10.1 With Python Cookbook

This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using;

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Accelerating MATLAB with GPU Computing

> Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics;

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Multicore and GPU Programming

Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing tools, essential;

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Python Parallel Programming Cookbook

programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered;

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IPython Interactive Computing and Visualization Cookbook

, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics;

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Hands-On Bitcoin Programming with Python

, and other visualizations Who this book is forHands-On Bitcoin Programming with Python consists of examples that will teach you to build;

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Python Workout

Features 50 hands-on exercises and solutions Basic Python sequence types Python dictionaries and sets Functional programming;

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Developing Graphics Frameworks with Python and OpenGL

API for GPU programming, with the accessibility and versatility of the Python programming language. Topics you will explore include generating;

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