Hands on gpu computing python par avimanyu bandyopadhyay (18 résultats)

Etat : New.

Paperback or Softback. Etat : New. Hands-On GPU Computing with Python. Book.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback. Etat : New. Explore a GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda AccelerateKey FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use CUDA libraries such as CuDNN for deep learning on GPUsBook DescriptionGPUs 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 begins by introducing GPU computing and explaining the GPU architecture and programming models. You will learn, by example, how to perform GPU programming with Python, and look at using integrations such as PyCUDA, PyOpenCL, CuPy, and Numba with Anaconda for various tasks such as machine learning and data mining. In addition to this, you will get to grips with GPU workflows, 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 forData scientists, machine learning enthusiasts, or professionals who want to get started with GPU computation and perform the complex tasks with low-latency will find this book useful. Intermediate knowledge of Python programming is assumed.…

Etat : New. pp. 452.

Etat : New.

Etat : As New. Unread book in perfect condition.

Paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Etat : New. Explore a GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda AccelerateKey FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use CUDA libraries such as CuDNN for deep learning on GPUsBook DescriptionGPUs 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 begins by introducing GPU computing and explaining the GPU architecture and programming models. You will learn, by example, how to perform GPU programming with Python, and look at using integrations such as PyCUDA, PyOpenCL, CuPy, and Numba with Anaconda for various tasks such as machine learning and data mining. In addition to this, you will get to grips with GPU workflows, 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 forData scientists, machine learning enthusiasts, or professionals who want to get started with GPU computation and perform the complex tasks with low-latency will find this book useful. Intermediate knowledge of Python programming is assumed.…

PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Etat : New. Print on Demand pp. 452.

Etat : New. PRINT ON DEMAND pp. 452.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. GPU technologies are the paradigm shift in modern computing. This book will take you through architecting your GPU-based systems to deploying the computational models on GPUs for faster processing. You will learn to program your GPUs to build a GPU-accelera.…

Taschenbuch. Etat : Neu. Hands-On GPU Computing with Python | Avimanyu Bandyopadhyay | Taschenbuch | Kartoniert / Broschiert | Englisch | 2019 | Packt Publishing | EAN 9781789341072 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …