Julia is a high-level programming language well suited for scientific computing and data science. Just-in-time compilation, among other things, makes Julia really fast yet interactive.
For heavy computations, Julia supports multi-threaded and multi-process parallelism, both natively and via a number of external packages. It also supports memory arrays distributed across multiple processes either on the same or different nodes. In this webinar, we will start with a quick review of Julia's multi-threading features but will focus primarily on Distributed standard library and its large array of tools. We will demo parallelization using three problems: a slowly converging series, a Julia set, and an N-body solver. We will run examples on a multi-core laptop and an HPC cluster.
Speakers:
- Alex Razoumov, Visualization and Training Coordinator, WestGrid
- Marie-Hélène Burle, Research Computing Training Assistant, WestGrid
Webinar Instructions:
- Click the green "Register' button on this page. All registrants will be emailed the connection instructions for this webinar.
If you have questions or would like more information, please contact training@westgrid.ca.
