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Course Outline
Introduction
Parallel Programming in Theory
- Memory architecture
- Memory organization
Thread-Based and Process-Based Parallelism
- Instantiating and determining a thread
- Working with thread synchronization
- Creating, naming, running, and synchronizing a process
- Using Asyncio for asynchronous programming
Distributed Python
- Using Celery
- Using SCOOP
- Using Pyro4
- Using PyCSP
- Using RPyC
GPU Programming
- Using the PyCUDA module
- Using NumbaPro
- Using PyOpenCL
- Testing with PyOpenCL
Testing and Troubleshooting
- Testing with unit testing
- Testing with mock testing
Summary and Conclusion
Requirements
- Python programming experience
Audience
- Software Developers
14 Hours
Testimonials (5)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Transfer of practical knowledge and experience of the trainer.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
Machine Translated
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Course - Build REST APIs with Python and Flask
As I was the only participant the training could be adapted to my needs.
