Introduction to Parallel Programming using Python - UNSW

This Parallel Python workshop is designed to teach cutting edge techniques to work with big data and process data in parallel using Python and is suitable for all participants who want to enhance their data science capabilities.

Python is one of the most used programming languages worldwide with applications in almost every data-oriented application domain. The Python data science ecosystem is a rich platform for scaling up workflows, enhancing scientific research and improving insight. However, Python can be performance limited when large datasets or challenging computations are required. Parallel computing and efficient data handling can overcome this barrier, enhancing research throughput.

If you have any questions regarding this training, please contact training.nci@anu.edu.au.

Prerequisites

1. Experience with Python.
2. Experience with bash or similar Unix shells.
   
3. Having a valid NCI account and vp91 membership
4. The training session is driven on the NCI ARE service. Attendees are encouraged to review the following page for background information: https://opus.nci.org.au/displa...

Learning Outcomes

After this training session, you will be able to

• Learn the basic concepts of parallel programming.
• Learn the different hardware components that make up an HPC machine.
• Learn how an HPC machine is organized.
• Learn how to submit a Job to a PBS batch scheduler.

Topics Covered