Название: Parallel and High Performance Programming with Python: Unlock parallel and concurrent programming in Python using multithreading, CUDA, Pytorch and DaskАвтор: Fabio Nelli
Издательство: Orange Education Pvt Ltd, AVA
Год: 2023
Страниц: 372
Язык: английский
Формат: pdf, epub
Размер: 10.96 MB
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.
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 (AI), 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.
Chapter 1 will start with an introduction to parallelism in Python and then will explain how the operating system handles multiple processes and threads. Its purpose will be to introduce you to the concept of parallel programming by talking about all the fundamental concepts that are involved, and which are necessary to fully understand the features and uses. Once these general concepts have been introduced, you will see the peculiarities of Python in this area, especially with threads, talking about the GIL (Global Interpreter Lock) and the problems it introduces. We will also learn about standard Python library modules such as threading and multiprocessing.
Chapter 2 will cover parallel programming in Python that uses Threads as concurrent elements. Specifically, the chapter will deal with the threading module that allows us to easily implement threads and provide a whole series of useful tools for their synchronization.
Chapter 3 will cover parallel programming in Python that uses Processes. There are two main approaches by which processes can be implemented in parallel programming: the multiprocessing module of the standard library and the mpi4py library which extends the MPI protocol also for the Python language.
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Chapter 9 will cover another very interesting field of application, which in part extends to what was said in Data Science: Artificial Intelligence. Machine Learning and Deep Learning are subsets of Artificial Intelligence and they provide us with a good tool to explore data. Lately, these techniques are expanding enormously by exploiting parallel and distributed computing.
Chapter 10 will show you how developments and trends of this way of programming are fitting perfectly with the most innovative new technologies.
What will you 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.
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