nach der Bestellung gedruckt Neuware - Printed after ordering - This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing.The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing.The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them.By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead.TABLE OF CONTENTS1. Introduction to Parallel Programming2. Building Multithreaded Programs3. Working with Multiprocessing and mpi4py Library4. Asynchronous Programming with AsyncIO5. Realizing Parallelism with Distributed Systems6. Maximizing Performance with GPU Programming using CUDA7. Embracing the Parallel Computing Revolution8. Scaling Your Data Science Applications with Dask9. Exploring the Potential of AI with Parallel Computing10. Hands-on Applications of Parallel Computing.

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Bibliographic Details

Title: Parallel and High Performance Programming with Python : Unlock parallel and concurrent programming in Python using multithreading, CUDA, Pytorch and Dask.
Publisher: Orange Education Pvt Ltd
Publication Date: 2023
Language: English
ISBN 10: 9388590732
ISBN 13: 9789388590730
Binding: Taschenbuch
Condition: Neu
Dimensions: 235 millimeters width by 191 millimeters height by 22 millimeters depth
Weight: 733 grams

About this title

Synopsis

Unleash the capabilities of Python and its libraries for solving high performance computational problems.

Key Features

● Explores parallel programming concepts and techniques for high-performance computing.

● Covers parallel algorithms, multiprocessing, distributed computing, and GPU programming.

● Provides practical use of popular Python libraries/tools like NumPy, Pandas, Dask, and TensorFlow.

Book Description

This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing.

The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing.

The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them.

By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead.

What you will learn

● Build faster, smarter, and more efficient applications for data analysis, machine learning, and scientific computing

● Implement parallel algorithms in Python

● Best practices for designing, implementing, and scaling parallel programs in Python

Who is this book for?

This book is aimed at software developers who wish to take their careers to the next level by improving their skills and learning about concurrent and parallel programming. It is also intended for Python developers who aspire to write fast and efficient programs, and for students who wish to learn the fundamentals of parallel computing and its practical uses.

Table of Contents

1. Introduction to Parallel Programming

2. Building Multithreaded Programs

3. Working with Multiprocessing and mpi4py Library

4. Asynchronous Programming with AsyncIO

5. Realizing Parallelism with Distributed Systems

6. Maximizing Performance with GPU Programming using CUDA

7. Embracing the Parallel Computing Revolution

8. Scaling Your Data Science Applications with Dask

9. Exploring the Potential of AI with Parallel Computing

10. Hands-on Applications of Parallel Computing

About the Author

Fabio Nelli holds a Master's Degree in Chemistry and a Bachelor's Degree in IT and Automation Engineering. He currently works at various research institutes and private companies, where he delivers educational courses on data analysis and data visualization technologies. He contributes to writing articles on the web and writes in-depth books on the subject.

"About this title" may belong to another edition of this title.

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