A hands-on introduction to using Parallelware Trainer
Using Parallelware Trainer to speed up your understanding of OpenMP and how to use OpenMP in real applications.
High Performance Computing (HPC) is fundamental in solving scientific problems, from protein folder to developing nuclear fusion reactors, however, it is often viewed as complex and difficult to use. Traditional training in HPC software development, while a great foundation for the theory, often leaves attendees with a knowledge gap on how to tackle real-applications rather than the simple examples given in training.
This 3 hour course will demonstrate how to use Parallelware Trainer and to simplify your learning of OpenMP, and how to quickly and effectively use OpenMP in real applications. Find out in the practical sessions how to easily take a real application from sequential code to OpenMP enabled software in just a few hours. By using Parallelware Trainer you will also be able to minimise and nearly eliminate the introduction of syntax errors and race conditions as you are guided through the parallelisation process.
This foundation will give you the ability to appreciate how to use HPC in your field and also equip you with the tools to start making effective use of HPC facilities yourself.
On completion of the course, we expect attendees will be in a position to use Parellelware Trainer for continued self-learning of OpenMP and even start using OpenACC for accelerators. Attendees will also have all the tools needed to start developing their own OpenMP enabled applications.
The course is delivered using a mixture of lectures and practical sessions and has a very practical focus.
Intended learning outcomes
On completion of this course students should be able to:
- Use Parallelware Trainer on their own applications.
- Understand your code in terms of parallel patterns by using Parallelware Trainer to quickly identify the patterns and facilitate the introduction of parallelism.
- Understand what variables need to be protected when introducing OpenMP directives.
- Maximise limited software development time for improved code correctness and performance.
thu10dec09:00thu14:00FeaturedPractical course in vectorization and parallelization for Finisterrae using Parallelware toolsBest practices for multicore CPU programming with OpenMP covering vectorization and shared-memory parallelization09:00 – 14:00
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