Nowadays, GPU programming plays an important role in software development. The massive parallel hardware enables us to analyze bigger datasets, process data in finer details or visualize simulations in real-time. Still, due to the programming complexity and the lack of knowledge, GPUs are not regularly used in many scientific fields. Thankfully, GPU programming matures and provides simpler tools to utilize GPU hardware. In this presentation, we describe multiple GPU programming frameworks (ranging from high-level to low-level) and showcase them on selected bioinformatics algorithms.

About the speaker

Adam Šmelko is a third year doctoral student in the Department of Distributed and Dependable Systems at Charles University in Prague with the dissertation topic of Employing parallel computing in data-intensive tasks. 
He specializes in GPU programming and in the analysis of memory accesses in programs. 
His current research topic involves development of tools for effective memory layouts  and traversals of data structures. 

Who is this course for?

This webinar is part of PerMedCoE webinar series and is open for anyone interested in PerMedCoE products and developments, as well as for researchers in the life sciences, bioinformaticians and life sciences software developers.

The goal of PerMedCoE is to provide an efficient and sustainable entry point to the HPC/Exascale-upgraded methodology to translate omics analyses into actionable models of cellular functions of medical relevance.

Outcomes

By the end of this webinar, you will be able to:

• Describe GPU threads architecture
• Find suitable parallelisation opportunities
• Define the first steps in coding on GPUs

This webinar, hosted on Zoom Webinar, is free to attend, but you need to register for a place beforehand, using the 'Register' button. Once registered, you will receive a confirmation email with a link to join the webinar