Many scientific modelling programs are written in C, one of the most popular programming languages used by the HPC community. This course covers the basic concepts of C programming, including syntax, core features, and best practices. It targets students and researchers who have little to no programming background, but would like to learn a low level programming language in depth. Those with some basic C knowledge will also likely learn something new.
Note that although C++ is not covered directly, the vast majority of the content is directly transferrable as a starting point for learning C++.
If you have any questions regarding this training, please contact training.nci@anu.edu.au.
Date/Time
Nov 8-9, 2022 13:00 - 16:00 AEDT, Register via this link.
Prerequisites
Objectives
The training is designed to be the first parallel programming course for scientists. As such, it aims to help attendees
- understand the multithreaded programming model,
- convert serial iterations into parallel,
- reduce errors from common misusages of OpenMP clauses.
Learning Outcomes
At the completion of this training session, you will be able to
- know when to use OpenMP,
- create Parallel Construct,
- create a team of threads,
- identify potential data race conditions,
- distinguish data storage attributes,
- understand how to split loop iterations to improve efficiency,
- understand the limitations of multithreaded programming,
- feel confident to advance to next-level parallel programming.
Topics Covered
- Threading in OpenMP
- Shared-memory system v.s. Distributed-memory system
- Loop parallelism methodologies
- Parallel construct
- Worksharing-loop construct
- Reduction
- Data race condition
- OpenMP Library routines
- Synchronisations
- Data storage attributes
- Loop Scheduling
- Profiling OpenMP
Overview
Content Tools