Learn Parallel Computing in Python
Learn Parallel Computing in Python
Discover Multithreading, Multiprocessing, Concurrency & Parallel programming with practical and fun examples in Python
Created by James Cutajar | 5 hours on-demand video course
This is far from the truth. Our minds are very much used to dealing with concurrency. In fact we do this in our everyday life without any problem but somehow we struggle to translate this into our code. One of the reasons for this is that we’re not familiar with the concepts and tools available to us to manage this concurrency. This course is here to help you understand how to use multithreading and multiprocessing tools and concepts to manage your parallel programming. It is designed to be as practical as possible. We start with some theory around parallelism and then explain how the operating system handles multiple processes and threads. Later we move on to explain the multiple tools available by solving example problems using concurrent programming. In this course we use the Python language, however the concepts learned here can be applied to most programming languages. All code in this course can be found on github, username/project: cutajarj/multithreadinginpython
What you’ll learn
- Discover how to create responsive and high performance software.
- See how to use multithreading and multiprocessing for modeling certain types of problems.
- Develop programs with Python that are highly Concurrent and Parallel.
- Understand the advantages, limits and properties of Parallel computing.
- Improve your programming skills in Python with more advanced, mulithreading and multiprocessing topics.
- Learn about threads, processes, mutexes, barriers, waitgroups, queues, pipes, condition variables, deadlocks and more.
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