Title: Practical intro to GPU programming in Python & Julia
Speaker: Yonglei Wang, PhD, Training Coordinator and Research Software Engineer and HPC application expert at ENCCS
Abstract: 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. As a result, it allows researchers to analyze large biological datasets with unprecedented efficiency. However, in order to make use of this potential we need 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 learn about online materials and in-person courses where researchers can learn about this topic in depth.
Tools for AI/ML research in life sciences is an event series by the SciLifeLab Data Centre aimed at life science researchers who use machine learning methods in their work. The goal of the events in this series is to provide introductions to different tools for ML research but also to foster discussions around our practices. The events takes place virtually (over Zoom) and are open to researchers in Sweden and beyond. Each event is scheduled for 60 minutes, consisting of a talk and an extended discussion. Follow the page of the event series to learn about future seminars.
Finally. for questions about the events please contact the organizing team by emailing email@example.com
Scientific lead: Prof. Ola Spjuth, SciLifeLab Data Centre and Uppsala University
Contact information: firstname.lastname@example.org
Additionally, if you want to learn more about GPU programming and related fields, check our lessons material.