Python Parallel Programming Cookbook Second Edition

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Python Parallel Programming Cookbook

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Author : Giancarlo Zaccone
language : en
Publisher:
Release Date : 2019-09-06

Python Parallel Programming Cookbook written by Giancarlo Zaccone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-06 with Application software categories.

Implement effective programming techniques in Python to build scalable software that saves time and memory Key Features Design distributed computing systems and massive computational tasks coherently Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs Understand how to host your parallelized applications on the cloud Book Description Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. By the end of this book, you will be confident in building concurrent and high-performing applications in Python. What you will learn Synchronize multiple threads and processes to manage parallel tasks Use message passing techniques to establish communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational task Write efficient programs by adopting the event-driven programming model Explore cloud technology with Django and Google App Engine Apply parallel programming techniques that can lead to performance improvements Who this book is for The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.

Python Parallel Programming Cookbook Second Edition

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Author : Giancarlo Zaccone
language : en
Publisher:
Release Date : 2019

Python Parallel Programming Cookbook Second Edition written by Giancarlo Zaccone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Implement effective programming techniques in Python to build scalable software that saves time and memory Key Features Design distributed computing systems and massive computational tasks coherently Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs Understand how to host your parallelized applications on the cloud Book Description Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. By the end of this book, you will be confident in building concurrent and high-performing applications in Python. What you will learn Synchronize multiple threads and processes to manage parallel tasks Use message passing techniques to establish communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational task Write efficient programs by adopting the event-driven programming model Explore cloud technology with Django and Google App Engine Apply parallel programming techniques that can lead to performance improvements Who this book is for The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of par...

Python Parallel Programming Cookbook

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Author : Giancarlo Zaccone
language : en
Publisher: Packt Publishing
Release Date : 2015-08-26

Python Parallel Programming Cookbook written by Giancarlo Zaccone and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-26 with Computers categories.

Master efficient parallel programming to build powerful applications using PythonAbout This Book• Design and implement efficient parallel software• Master new programming techniques to address and solve complex programming problems• Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depthWho This Book Is ForPython Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.What You Will Learn• Synchronize multiple threads and processes to manage parallel tasks• Implement message passing communication between processes to build parallel applications• Program your own GPU cards to address complex problems• Manage computing entities to execute distributed computational tasks• Write efficient programs by adopting the event-driven programming model• Explore the cloud technology with DJango and Google App Engine• Apply parallel programming techniques that can lead to performance improvementsIn DetailThis book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool.Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker.You will understand anche Pycsp, the Scoop framework, and disk modules in Python. Further on, you will learnGPU programming withPython using the PyCUDA module along with evaluating performance limitations.Style and approachA step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts.

Parallel And High Performance Programming With Python Unlock Parallel And Concurrent Programming In Python Using Multithreading Cuda Pytorch And Dask

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Author : Fabio Nelli
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2023-04-12

Parallel And High Performance Programming With Python Unlock Parallel And Concurrent Programming In Python Using Multithreading Cuda Pytorch And Dask written by Fabio Nelli and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-12 with Computers categories.

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

Deep Learning With Tensorflow

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Author : Giancarlo Zaccone
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-03-30

Deep Learning With Tensorflow written by Giancarlo Zaccone and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-30 with Computers categories.

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key Features Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. What you will learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications Who this book is for The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.

American Book Publishing Record

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Author :
language : en
Publisher:
Release Date : 1996

American Book Publishing Record written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Books categories.

Fluent Python

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Author : Luciano Ramalho
language : en
Publisher: O'Reilly Media
Release Date : 2015

Fluent Python written by Luciano Ramalho and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.

Explains how to write idiomatic, effective Python code by leveraging its best features. Python's simplicity quickly lets you become productive with it, but this often means you aren't using everything the language has to offer. By taking you through Python's key language features and libraries, this practical book shows you how to make your code shorter, faster, and more readable all at the same time. --From publisher description.

Parallel Programming With Python

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Author : Jan Palach
language : en
Publisher: CreateSpace
Release Date : 2014-12-12

Parallel Programming With Python written by Jan Palach and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-12 with categories.

Develop efficient parallel systems using the robust Python environment Overview Demonstrates the concepts of Python parallel programming Boosts your Python computing capabilities Contains easy-to-understand explanations and plenty of examples In Detail 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 Approach A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. Who this book is written for If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

Python High Performance Second Edition

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Author : Gabriele Lanaro
language : en
Publisher:
Release Date : 2017-05-24

Python High Performance Second Edition written by Gabriele Lanaro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-24 with Computers categories.

Learn how to use Python to create efficient applicationsAbout This Book* Identify the bottlenecks in your applications and solve them using the best profiling techniques* Write efficient numerical code in NumPy, Cython, and Pandas* Adapt your programs to run on multiple processors and machines with parallel programmingWho This Book Is ForThe book is aimed at Python developers who want to improve the performance of their application. Basic knowledge of Python is expectedWhat You Will Learn* Write efficient numerical code with the NumPy and Pandas libraries* Use Cython and Numba to achieve native performance* Find bottlenecks in your Python code using profilers* Write asynchronous code using Asyncio and RxPy* Use Tensorflow and Theano for automatic parallelism in Python* Set up and run distributed algorithms on a cluster using Dask and PySparkIn DetailPython is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language.Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications.The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark.By the end of the book, readers will have learned to achieve performance and scale from their Python applications.Style and approachA step-by-step practical guide filled with real-world use cases and examples

Parallel Programming With Python

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Author : Jan Palach
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-06-25

Parallel Programming With Python written by Jan Palach and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-25 with Computers categories.

A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.