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Dates: 28 - 29 Nov, 2023

LocationBirch 1.43 Interactive Theatre 35 Science Rd, The Australian National University

Event type: In-person Workshop

Hosts: School of Computing and its Computational Science Cluster, NCI Australia and Monash University

Lecturers: Prof. Santiago Badia, Monash UniversityDr. Alberto F. Martín, ANU;  Jordi Manyer, Monash University

 


Workshop Overview

This two-day hands-on workshop will showcase the main features of Gridap, an ecosystem of Julia packages for the simulation of problems governed by PDEs. Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretisations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap has a very expressive user interface, allowing one to solve complex PDE systems by stating the problem using whiteboard notation. It implements multiple state-of-the-art finite element methods that can efficiently exploit large-scale HPC supercomputers. 

The workshop will be tutorial-based and will cover the main features of Gridap, its application to several problems, and its deployment in distributed memory machines. There will also be a brief introduction to finite element methods addressed to participants without previous background in these techniques. The emphasis will be mainly on presenting the main software abstractions underlying these packages and how these can be combined to solve a variety of PDEs with application to different problems in science and engineering. The choice of the PDE systems to be discussed in the workshop will be based on the participant's interests gathered during registration.  

The event will be cohosted by its main developers (Prof. Santiago Badia, Monash University, and Dr. Alberto F. Martín, ANU) and the National Computational Infrastructure (NCI). We extend a warm invitation to all, whether you possess extensive programming expertise, are curious about Julia, or are enthusiastic about delving into finite elements—a widely utilized technique for generating numerical approximations to partial differential equations (PDEs)


Grant Support

We provide grants to assist research students (Honours, MPhil, PhD) at Australian universities and public research institutions. These grants include full accommodation for a two-night hotel stay on November 27th and 28th as well as partial travel support. Research students applying for a grant must upload a letter of support from their supervisor/course coordinator/Head of School that includes a statement supporting their request for financial assistance. It is the applicant's responsibility to check their home institution's guidelines BEFORE booking travel. Applicants must, at the time of the event, be enrolled as a research student in Mathematics, Engineering, Physics, Computer Science, or related fields.


Registration

The workshop is fully booked now. Thanks a lot for your interest in participating! 


Course Materials

https://gridap.github.io/GridapWorkshopNCI2023/


Important Dates

Funding Application: Sunday, 5th Nov 2023 (See below for details)

General Admission (application without funding): Sunday, 26th Nov 2023 (Note that only a limited number of seats are available, so the earlier you apply, the better)

Workshop Dates: 28 - 29 Nov, 2023

Participants must bring their own laptops. Instructions will be provided to install the software before the workshop takes place. 


                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          


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