Hands-On GPU Computing with Python

Hands-On GPU Computing with Python
Author :
Publisher : Packt Publishing Ltd
Total Pages : 441
Release :
ISBN-10 : 9781789342406
ISBN-13 : 1789342406
Rating : 4/5 (06 Downloads)

Book Synopsis Hands-On GPU Computing with Python by : Avimanyu Bandyopadhyay

Download or read book Hands-On GPU Computing with Python written by Avimanyu Bandyopadhyay and published by Packt Publishing Ltd. This book was released on 2019-05-14 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use the CUDA libraries like CuDNN for deep learning on GPUsBook Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learnUtilize Python libraries and frameworks for GPU accelerationSet up a GPU-enabled programmable machine learning environment on your system with AnacondaDeploy your machine learning system on cloud containers with illustrated examplesExplore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm.Perform data mining tasks with machine learning models on GPUsExtend your knowledge of GPU computing in scientific applicationsWho this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.


Hands-On GPU Computing with Python Related Books

Hands-On GPU Computing with Python
Language: en
Pages: 441
Authors: Avimanyu Bandyopadhyay
Categories: Computers
Type: BOOK - Published: 2019-05-14 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key Featu
Hands-On GPU Programming with Python and CUDA
Language: en
Pages: 300
Authors: Dr. Brian Tuomanen
Categories: Computers
Type: BOOK - Published: 2018-11-27 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across
Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA
Language: en
Pages: 373
Authors: Bhaumik Vaidya
Categories: Computers
Type: BOOK - Published: 2018-09-26 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPU Key Fea
Programming Massively Parallel Processors
Language: en
Pages: 519
Authors: David B. Kirk
Categories: Computers
Type: BOOK - Published: 2012-12-31 - Publisher: Newnes

DOWNLOAD EBOOK

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detai
CUDA Programming
Language: en
Pages: 592
Authors: Shane Cook
Categories: Computers
Type: BOOK - Published: 2012-11-13 - Publisher: Newnes

DOWNLOAD EBOOK

'CUDA Programming' offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU