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DESCRIPTION:Solving large systems efficiently in multiphysics numerical sim
 ulations - May 31-June 10\, 2021 - Will be held online\n\nMultiphysics sim
 ulations have become an important problem that has practical applications 
 in many fields in science and engineering. Two examples include (i) simula
 ting the interactions between the flow of fluids in the subsurface (e.g. g
 roundwater\, oil and natural gas) and the mechanical deformation of the su
 rrounding rock due to pressure\, temperature\, etc.\; (ii) simulating the 
 interactions between the ocean and the atmosphere in meteorological predic
 tions and climate modelling. In these and many other applications\, the un
 derlying model in each regime is given by partial differential equations (
 PDEs)\, which are then discretized and solved many times over the course o
 f the simulation. The resulting algebraic systems are typically large (wit
 h millions of degrees of freedom)\, sparse (each equation only depends on 
 a few unknowns) and ill-conditioned (very sensitive to perturbations in th
 e data)\, which makes their efficient solution challenging. The past 50 ye
 ars have seen the rise of iterative methods and preconditioners that are h
 ighly efficient for particular types of PDEs\, such as heat diffusion\, fl
 uid flow\, waves arising from electromagnetism\, etc. However\, when diffe
 rent physical models interact\, it becomes essential to develop techniques
  to solve the coupled problem efficiently\, in addition to the individual 
 components. The goal of this summer school is to introduce fundamental sol
 ver techniques for dealing with these coupled problems. In particular\, we
  are interested in techniques that are able to exploit modern supercomputi
 ng architecture\, which often have tens of thousands of processors capable
  of doing many calculations in parallel.\n\n \n\nThe theoretical portion o
 f the summer school consists of three mini-courses that introduce the part
 icipants to fundamental techniques for large multiphysics problems: (i) st
 ationary iterative methods\, (ii) domain decomposition\, and (iii) multigr
 id methods. These mini-courses will be complemented by practical sessions\
 , where participants will be guided by well-designed problem sets in order
  to experiment with the methods introduced in the mini-courses\, and to ex
 plore the mathematics behind these techniques. In addition there will be f
 our seminar-style talks by invited speakers\, who will present their work 
 on multiphysics simulations and/or preconditioning techniques.\n\nThe scho
 ol is free of charge\, but registration is mandatory. Due to limited capac
 ity\, we can only accept a maximum of 200 participants on a first-come-fir
 st-serve basis.\n\n \n\nOrganizers :\n	Wing Hong Felix Kwok (Université Lav
 al)\n	Jean Deteix (Université Laval)\n	Scott MacLachlan (Memorial University
  of Newfoundland)\n	Vivien Clauzon (Michelin)\n\n \n\n \n
DTSTART;VALUE=DATE:20210531
DTEND;VALUE=DATE:20210610
SUMMARY:Solving large systems efficiently in multiphysics numerical simulat
 ions
URL:https://www.mcgill.ca/mathstat/channels/event/solving-large-systems-eff
 iciently-multiphysics-numerical-simulations-330830
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