Parallel Programming with Python
Год: 2014
Автор: Palach J.
Издательство: Packt
ISBN: 978-1-78328-839-7
Язык: Английский
Формат: PDF
Качество: Изначально компьютерное (eBook)
Интерактивное оглавление: Да
Количество страниц: 122
Описание: Starting with the basics of parallel programming, you will proceed to learn about how to build parallel algorithms and their implementation. You will then gain the expertise to evaluate problem domains, identify if a particular problem can be parallelized, and how to use the Threading and Multiprocessor modules in Python.
The Python Parallel (PP) module, which is another mechanism for parallel programming, is covered in depth to help you optimize the usage of PP. You will also delve into using Celery to perform distributed tasks efficiently and easily. Furthermore, you will learn about asynchronous I/O using the asyncio module. Finally, by the end of this book you will acquire an in-depth understanding about what the Python language has to offer in terms of built-in and external modules for an effective implementation of Parallel Programming.
This is a definitive guide that will teach you everything you need to know to develop and maintain high-performance parallel computing systems using the feature-rich Python.
- What you will learn from this book
- Explore techniques to parallelize problems
- Integrate the Parallel Python module to implement Python code
- Execute parallel solutions on simple problems
- Achieve communication between processes using Pipe and Queue
- Use Celery Distributed Task Queue
- Implement asynchronous I/O using the Python asyncio module
- Create thread-safe structures
Содержание
Preface 1
Chapter 1: Contextualizing Parallel, Concurrent, and Distributed Programming 7
Chapter 2: Designing Parallel Algorithms 19
Chapter 3: Identifying a Parallelizable Problem 25
Obtaining the highest Fibonacci value for multiple inputs 25
Chapter 4: Using the threading and concurrent.futures Modules 29
Chapter 5: Using Multiprocessing and ProcessPoolExecutor 41
Chapter 6: Utilizing Parallel Python 53
Chapter 7: Distributing Tasks with Celery 67
Chapter 8: Doing Things Asynchronously 85
Index 99
Опубликовано группой
