Python Parallel Programming Solutions [Video]

More Information
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
About

This course will teach you parallel programming techniques using examples in Python and 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, we move 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 and will learn about the performance of MPI Python Modules.

Moving on, you’ll get to grips with the asynchronous parallel programming model using the Python asyncio module, and will see how to handle exceptions. 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 get hands-on in GPU programming with Python using the PyCUDA module and will evaluate performance limitations.

Style and Approach

A step-by-step guide to parallel programming using Python, with videos that feature one or more programming examples. It is a practically-oriented course and has all the necessary underlying parallel computing concepts.

Features
  • Design and implement efficient parallel software using the examples and topics covered in great depth
  • Master new programming techniques to address and solve complex programming problems
  • Explore the world of parallel programming with this course, your go-to resource for different kinds of parallel computing tasks in Python
Course Length 3 hours 59 minutes
ISBN 9781787280496
Date Of Publication 27 Dec 2016

Authors

Giancarlo Zaccone

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).