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Python Parallel Programming Cookbook
von
Giancarlo Zaccone
Verlag: Packt Publishing
Erschienen 29.08.2015 - Kartoniert, 286 Seiten, 235mm x 191mm x 16mm, Sprache(n): eng
Print on Demand. Lieferbar innerhalb von 7 bis 10 Tagen
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- 📚 Bücher
- Anbieter:
- MARZIES Buch- und Medienhandel
- Bestell-Nr.:
- A25690772
- ISBN | EAN:
- 1785289586 | 9781785289583
- Stichworte:
- Python Parallel Programming Multiprocessing Threading Parallel Python module GPU computing Concurrency
- Zahlungsarten:
- Vorauskasse, PayPal
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Master efficient parallel programming to build powerful applications using Python
Key Features
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 depth
Book Description
This 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.
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 improvements
Who this book is for
Python 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.
Key Features
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 depth
Book Description
This 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.
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 improvements
Who this book is for
Python 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.
Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems. Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing. Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).
