Domain decomposition methods consists in decomposing the original mathematical problem into a collection of smaller (and computationally cheaper) subproblems, each of which can be solved independently. The divide-and-conquer philosophy at the basis of iterative domain decomposition methods has been proved to be the ideal paradigm for large-scale simulation on massively parallel computers.
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Valley of Grenoble: decomposed computational domain for the numerical simulation of seismic wave propagation in near-fault conditions
Sequence of agglomerated polygonal meshes for geometric multigrid.
Multigrid and multilevel methods employs a hierarchy of discretizations to solve differential problems. The main idea at the basis of these techniques is to accelerate the convergence of basic iterative solvers employing (recursively) a global coarse correction. For a certain class of problems, multigrid methods are among the fastest solution techniques known today since they feature optimal computational complexity and scaling properties.
View a list of journal publications and MOX Reports related to domain decomposition methods.
View a list of theses related to domain decomposition methods.