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Teratec 2022 Forum
Wednesday, June 15 - Application Workshop

Workshop 03 - 9:00 to 12:30 pm

HPC and computer codes: a constantly evolving ecosystem
Chaired by Cyril BAUDRY, Architecte SI scientifique, EDF R&D et Jean-Albert Vilmer, Regional Director EMEA South, MSC Software Hexagon

Scaling Computational Biology Software: Experimental Evolution and Solving of Ordinary Differential Equation
By Jonathan Rouzaud-Cornabas, Maître de conférences, Inria

In Biology, the usage of high performance computational resources is quite limited in comparison with other scientific domains. But since few years, the requirement of such resources has grown and is becoming critical. Nonetheless, the models and the software that implement them are not ready to such platform. Accordingly, we have a big opportunity to redevelop or port these software to modern HPC platform while using state of the art methodology to do so.

We will present the work we have done around the Aevol software, an artificial evolution software, and how we redesign it from the ground up to be able to support both CPU and GPU computing. Such work would not be possible without a strong understanding of the biological model and how it works.

We state that such work is possible only with a strong and close collaboration between biological modeler and HPC scientist.

To conclude, we will give a first feedback of our new project ExODE that is working on a new performance portable ODE Solver for Biological model.

Biography: Jonathan Rouzaud-Cornabas is an associate professor at INSA Lyon in the Computer Science department. He is doing his research in the LIRIS Lab and within the Inria Beagle research team. His primary focus is artificial evolution and the study of genome and biologicial network structures and the origin of their complexity. He is also involved in multiple High Performance Computational Biology project to increase the usage of supercomputer within the biology community and disseminates good practice such as performance portability. He is the PI of ExODE (Scaling the solving of Ordinary Differential Equation for Computational Biology), a project focusing on the usage of mix precision and modern HPC platform to improve performance and scalability of ODE Solver for biology model.

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