About the webinar

In this webinar, we focus on GPU-accelerated computing with Julia, one of the most popular high-level, general-purpose dynamic programming languages for science, engineering, data analytics, and deep learning applications. Starting from the basic syntax of Julia, we will span topics on multiple-dispatch paradigm, metaprogramming, and then additional special features of Julia for classic machine learning and deep learning, with a focus on their unique features and capabilities for high-performance computing.

In the past decade, Graphics Processing Units (GPUs) have ignited the dynamic evolution of data science. But GPUs can do a lot more than machine learning – these powerful devices can accelerate and massively parallelise any general-purpose computational load in domains involving big data and heavy number crunching. You can use the GPU in your personal computer, or scale up your application to run on a supercomputer. How can you get started?

Who is the webinar for?

The GPU programming using Julia webinar is for data scientists, software developers and researchers who are:

• already familiar with one or more programming languages (Python, R, C/C++, Fortran, Matlab,…) but want to add a new exciting high-level yet performant language to their repertoire,
• need to analyze big data or perform computationally demanding modelling or analyses,
• might be mixing a high-level and a low-level language for performance reasons but want to make their life easier.