The short course begins at 9AM in room 2018b in the education building, see here for a campus map, note the education building to the far left of this map, also see for a floor plan of the education building . Participants will want to arrive in St. John's by Saturday July 21, 2018. The meeting will end by 1pm on Friday July 27, 2018.

The short course will begin at 9am on Sunday, coffee will be available at 8:30 am! The short course should end at 5:30pm, lunch will be served from 12:30-2:00

Introductory Domain Decomposition Short Course - Sunday July 22, 2018, Room 2018B Education Building

Instructors: Dr. Laurence Halpern (Université PARIS), Dr. Felix Kwok (Hong Kong Baptist University) and Dr. Martin Gander (Université Genève)

The goal of this one day course is to introduce basic domain decomposition methods to researchers interested in understanding these methods, and to give them detailed insight on how these methods reduce various error components. There will be a theoretical and a practical component to this short course, spanning the morning and the afternoon sessions respectively. The morning session will be organized into three one-hour lectures. The first will be on Schwarz methods, which are the first domain decomposition methods that were invented and which classically work with overlapping subdomains. The second hour will be on Dirichlet-Neumann and Neumann-Neumann methods, which work on non-ovelapping subdomains and are precursors to FETI methods. The third hour will be on modern coarse spaces, which fix the defects in the above methods and make them scalable. In the three-hour afternoon session, participants will experiment with these three classes of methods by using and modifying sample codes written in Matlab. Registration details are available here . There is a $30 fee for the short-course. The option to pay for the short course can be chosen when you register for the meeting.

Sponsors

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We also acknowledge the support of the Department of Mathematics and Statistics and Faculty of Engineering at Memorial and the United States national labs LANL (Los Alamos National Lab) and LLNL (Lawrence Livermore National Lab)