Practical intro to GPU programming in Python and Julia

This is a recording of a webinar that took place on February 2, 2024. The webinar is part of the Tools for AI/ML research in life sciences event series arranged by the SciLifeLab Data Centre. This event was arranged together with ENCCS and National Supercomputing Center (NSC LiU).

Availability of Graphics Processing Units (GPUs) has transformed the way we work with machine learning and data science challenges in life sciences. The parallel processing capabilities of GPUs have allowed training of ever more complex models, allowing researchers to analyze large biological datasets with unprecedented efficiency. However, in order to make use of the potential that GPUs offer we need be able to write fitting machine learning model code and analysis pipelines. In this webinar ENCCS will present some practical tips about what to keep in mind and how to optimize your code when running analyses on GPU hardware. This webinar will be most useful to researchers who already work with large datasets and would like to improve their understanding of how to work with GPUs. At the end, the participants will also be given an overview of online materials and in-person courses where researchers can learn about this topic in depth.