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WEBINAR: Pro tips for scaling bioinformatics workflows to HPC

This webinar has ended. Watch the recording or download the slides.

Description:

High Performance Computing (HPC) infrastructures offer the computational scale and efficiency that life scientists need to handle complex biological datasets and multi-step computational workflows. But scaling workflows to HPC from smaller, more familiar computational infrastructures brings with it new jargon, expectations, and processes to learn. To make the most of HPC resources, bioinformatics workflows need to be designed for distributed computing environments and carefully manage varying resource requirements, and data scale related to biology.  

In this webinar, Dr Georgina Samaha from the Sydney Informatics Hub, Dr Matthew Downton from the National Computational Infrastructure (NCI) and Dr Sarah Beecroft from the Pawsey Supercomputing Research Centre help you navigate the world of HPC for running and developing bioinformatics workflows. They explain when you should take your workflows to HPC and highlight the architectural features you should make the most of to scale your analyses once you’re there. You’ll hear pro-tips for dealing with common pain points like software installation, optimising for parallel computing and resource management, and will find out how to get access to Australia’s National HPC infrastructures at NCI and Pawsey. 

Speakers: 

Dr Georgina Samaha, Senior Bioinformatician, Sydney Informatics Hub, University of Sydney

Dr Sarah Beecroft, Life Sciences Applications Specialist, Pawsey Supercomputing Research Centre

Dr Matthew Downton, Associate Director - Performance Optimisation, NCI Australia

Date/time: 31 May 2023, 1 - 2pm AEST / 12:30 - 1:30pm ACST / 11am - 12pm AWST

Who the webinar is for:

This webinar is intended for Australian life science researchers who wish to scale their research to HPC infrastructures or improve the computational efficiency of their existing workflows on HPCs. 

How to join:

Registrations are now closed.

Cover image: From Canva