55 research outputs found
Local Fourier analysis of multigrid for hybridized and embedded discontinuous Galerkin methods
In this paper we present a geometric multigrid method with Jacobi and Vanka
relaxation for hybridized and embedded discontinuous Galerkin discretizations
of the Laplacian. We present a local Fourier analysis (LFA) of the two-grid
error-propagation operator and show that the multigrid method applied to an
embedded discontinuous Galerkin (EDG) discretization is almost as efficient as
when applied to a continuous Galerkin discretization. We furthermore show that
multigrid applied to an EDG discretization outperforms multigrid applied to a
hybridized discontinuous Galerkin (HDG) discretization. Numerical examples
verify our LFA predictions
Error Estimation and Adaptation in Hybridized Discontinous Galerkin Methods
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140705/1/6.2014-0078.pd
A Coupled Hybridizable Discontinuous Galerkin and Boundary Integral Method for Analyzing Electromagnetic Scattering
A coupled hybridizable discontinuous Galerkin (HDG) and boundary integral
(BI) method is proposed to efficiently analyze electromagnetic scattering from
inhomogeneous/composite objects. The coupling between the HDG and the BI
equations is realized using the numerical flux operating on the equivalent
current and the global unknown of the HDG. This approach yields sparse coupling
matrices upon discretization. Inclusion of the BI equation ensures that the
only error in enforcing the radiation conditions is the discretization.
However, the discretization of this equation yields a dense matrix, which
prohibits the use of a direct matrix solver on the overall coupled system as
often done with traditional HDG schemes. To overcome this bottleneck, a
"hybrid" method is developed. This method uses an iterative scheme to solve the
overall coupled system but within the matrix-vector multiplication subroutine
of the iterations, the inverse of the HDG matrix is efficiently accounted for
using a sparse direct matrix solver. The same subroutine also uses the
multilevel fast multipole algorithm to accelerate the multiplication of the
guess vector with the dense BI matrix. The numerical results demonstrate the
accuracy, the efficiency, and the applicability of the proposed HDG-BI solver
Towards Efficient and Scalable Discontinuous Galerkin Methods for Unsteady Flows
openNegli ultimi anni, la crescente disponibilit`a di risorse computazionali ha contribuito alla diffusione della fluidodinamica computazionale per la ricerca e per la progettazione industriale. Uno degli approcci pi promettenti si basa sul metodo agli elementi finiti discontinui di Galerkin (dG).
Nellâambito di queste metodologie, il contributo della tesi e' triplice. Innanzi- tutto, il lavoro introduce un algoritmo di parallelizzazione ibrida MPI/OpenMP per lâutilizzo efficiente di risorse di super calcolo. In secondo luogo, propone strategie di soluzione efficienti, scalabili e con limitata allocazione di memoria per la soluzione di problemi complessi. Infine, confronta le strategie di soluzione introdotte con nuove tecniche di discretizzazione dette âibridizzabiliâ, su problemi riguardanti la soluzione delle equazioni di NavierâStokes non stazionarie.
Lâefficienza computazionale e' stata valutata su casi di crescente complessita' riguardanti la simulazione della turbolenza. In primo luogo, e' stata considerata la convezione naturale di Rayleigh-Benard e il flusso turbolento in un canale a numeri di Reynolds moderatamente alti. Le strategie di soluzione proposte sono risultate fino a cinque volte piu` veloci rispetto ai metodi standard allocando solamente il 7% della memoria. In secondo luogo, e' stato analizzato il flusso attorno ad una piastra piana con bordo arrotondato sottoposta a diversi livelli di turbolenza in ingresso. Nonostante la maggiore complessitĂ ' dovuta allâuso di elementi curvi ed anisotropi, lâalgoritmo proposto e' risultato oltre tre volte piu` veloce allocando il 15% della memoria rispetto ad un metodo standard. Concludendo, viene riportata la simulazione del âBoeing Rudimentary Landing Gearâ a Re = 10^6. In tutti i casi i risultati ottenuti sono in ottimo accordo con i dati sperimentali e con precedenti simulazioni numeriche pubblicate in letteratura.In recent years the increasing availability of High Performance Computing (HPC) resources strongly promoted the widespread of high fidelity simulations, such as the Large Eddy Simulation (LES), for industrial research and design. One of the most promising approaches to those kind of simulations is based on the discontinuous Galerkin (dG) discretization method.
The contribution of the thesis towards this research area is three-fold. First, the work introduces an efficient hybrid MPI/OpenMP parallelisation paradigm to fruitfully exploit large HPC facilities. Second, it reports efficient, scalable and memory saving solution strategies for stiff dG discretisations. Third, it compares those solution strategies, for the first time using the same numerical framework, to hybridizable discontinuous Galerkin (HDG) methods, including a novel implementation of a p-multigrid preconditioning approach, on unsteady flow problems involving the solution of the NavierStokes equations.
The improvements in computational efficiency have been evaluated on cases of growing complexity involving large eddy simulations of turbulent flows. First, the Rayleigh-Benard convection problem and the turbulent channel flow at moderately high Reynolds numbers is presented. The solution strategies proposed resulted up to five times faster than standard matrix-based methods while al- locating the 7% of the memory. A second family of test cases involve the LES simulation of a rounded leading edge flat plate under different levels of free-stream turbulence. Although the increased stiffness of the iteration matrix due to the use of curved and stretched elements, the solver resulted more than three times faster while allocating the 15% of the memory if compared to standard methods. Finally, the large eddy simulation of the Boeing Rudimentary Landing Gear at Re = 10^6 is reported. In all the cases, a remarkable agreement with experimental data as well as previous numerical simulations is documented.INGEGNERIA INDUSTRIALEopenFranciolini, Matte
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Fast and scalable solvers for high-order hybridized discontinuous Galerkin methods with applications to fluid dynamics and magnetohydrodynamics
The hybridized discontinuous Galerkin methods (HDG) introduced a decade ago is a promising candidate for high-order spatial discretization combined with implicit/implicit-explicit time stepping. Roughly speaking, HDG methods combines the advantages of both discontinuous Galerkin (DG) methods and hybridized methods. In particular, it enjoys the benefits of equal order spaces, upwinding and ability to handle large gradients of DG methods as well as the smaller globally coupled linear system, adaptivity, and multinumeric capabilities of hybridized methods. However, the main bottleneck in HDG methods, limiting its use to small to moderate sized problems, is the lack of scalable linear solvers. In this thesis we develop fast and scalable solvers for HDG methods consisting of domain decomposition, multigrid and multilevel solvers/preconditioners with an ultimate focus on simulating large scale problems in fluid dynamics and magnetohydrodynamics (MHD). First, we propose a domain decomposition based solver namely iterative HDG for partial differential equations (PDEs). It is a fixed point iterative scheme, with each iteration consisting only of element-by-element and face-by-face embarrassingly parallel solves. Using energy analysis we prove the convergence of the schemes for scalar and system of hyperbolic PDEs and verify the results numerically. We then propose a novel geometric multigrid approach for HDG methods based on fine scale Dirichlet-to-Neumann maps. The algorithm combines the robustness of algebraic multigrid methods due to operator dependent intergrid transfer operators and at the same time has fixed coarse grid construction costs due to its geometric nature. For diffusion dominated PDEs such as the Poisson and the Stokes equations the algorithm gives almost perfect hp--scalability. Next, we propose a multilevel algorithm by combining the concepts of nested dissection, a fill-in reducing ordering strategy, variational structure and high-order properties of HDG, and domain decomposition. Thanks to its root in direct solver strategy the performance of the solver is almost independent of the nature of the PDEs and mostly depends on the smoothness of the solution. We demonstrate this numerically with several prototypical PDEs. Finally, we propose a block preconditioning strategy for HDG applied to incompressible visco-resistive MHD. We use a least squares commutator approximation for the inverse of the Schur complement and algebraic multigrid or the multilevel preconditioner for the approximate inverse of the nodal block. With several 2D and 3D transient examples we demonstrate the robustness and parallel scalability of the block preconditionerAerospace Engineerin
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