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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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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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GPU Computing Gems, Jade Edition, offers hands-on, proven techniques for general purpose GPU programming based on the successful;
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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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) Interactive & Digital Media. The book also addresses the fundamental issues in GPU computing with a focus on big data processing. Researchers and;
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Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various;
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This book covers the new topic of GPU computing with many applications involved, taken from diverse fields such as networking, seismology;
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This book covers the new topic of GPU computing with many applications involved, taken from diverse fields such as networking, seismology;
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where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on;
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A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Book;
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Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across;
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implementation of the DEM on three popular parallel computing platforms; the multi-core PC, the GPU computer, and the cluster supercomputer. Featuring;
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of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism* Two new case studies (on;
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and NumPy modules * A hands-on guide to implementing mathematics with Python, with complete coverage of all the key concepts Who This Book;
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GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance;
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like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel;
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Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python;
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Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python;
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( This is not your average Python book I think this book is a great text for anyone teaching CS1 ). With a focus on computational problem solving;
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Python (R) is a free open-source language and environment that has tremendous potential in the scientific computing domain. Computing with;
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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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This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real;
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This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real;
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For courses in Computer Programming with Python. Social Computing and Programming with Python Introduction to Computing and Programming;
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Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python. Key Features;
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programming on a graphics processing unit (GPU) while covering some material also relevant to programming on a central processing unit (CPU). It;
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