Book Image

Hands-On GPU Computing with Python

By : Avimanyu Bandyopadhyay
Book Image

Hands-On GPU Computing with Python

By: Avimanyu Bandyopadhyay

Overview of this book

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 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.
Table of Contents (17 chapters)
Free Chapter
1
Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware
5
Section 2: Hands-On Development with GPU Programming
11
Section 3: Containerization and Machine Learning with GPU-Powered Python

The Anaconda Python distribution for package management and deployment

Anaconda is a distribution for package management and deployment. It facilitates the development of scientific computing and machine learning through Python and R (a programming language focused on statistical computing). Anaconda simplifies the process of managing various packages and also their deployment. The Anaconda repository maintains more than 1,000 professionally built packages for data science.

It has a package management system called conda to install various scientific packages. It also provides a build feature for building your own Python packages and uploading them to Anaconda servers. conda can be used for installing, executing, and also updating packages, along with their dependencies. It can facilitate software for any language, even though it was made for Python packages.

The Anaconda distribution...