This workshop provides an introduction to high-performance computing, focusing on the basics of parallel programming and GPU acceleration using Python. Participants will get an overview of key HPC concepts, including the different hardware components, how an HPC system is organized, and how to run Python code efficiently on these systems. The workshop will introduce tools such as Numba and MPI for distributed computing and get participants ready for more advanced workshops.

By the end of the workshop, participants will have a foundational understanding of parallel programming principles and how to submit jobs using a PBS batch scheduler. This workshop is designed as a starting point for those new to HPC, offering a high-level overview rather than in-depth technical training.

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

Prerequisites

Experience with Python.
Experience with bash or similar Unix shells.
Having a valid NCI account and vp91 membership
The training session is driven on the NCI ARE service. You can find relevant documentations here: ARE User Guide.

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 organised.
Learn how to submit a Job to a PBS batch scheduler.

Topics Covered

Topics	Material	Exercises	Duration
Basic of Parallelism	20 minutes	15 minutes	35 minutes
Requesting a Job	10 minutes	10 minutes	20 minutes
High-level HPC Architecture	20 minutes	15 minutes	35 minutes
Vector Parallelism	20 minutes	10 minutes	30 minutes
Multi-core Parallelism	20 minutes	10 minutes	30 minutes
GPU Parallelism	30 minutes	15 minutes	45 minutes
Multi-node Parallelism	20 minutes	15 minutes	35 minutes