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Showing 1 to 10 of 10 for “"Multigrid algorithms"”.
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Multigrid Algorithms for Massively Parallel Machines
… of solving <em>pde's</em> is the use of the multigrid algorithm. However, the implementation of the multigrid algorithm on massively parallel machines is not very efficient because of (i) low processor utilization and (ii) high communication overheads. These problems need to be addressed to …
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Multigrid algorithms and complexity results for discrete-time stochastic control and related fixed-point problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.
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Multilevel solution procedures for structural dynamics eigenvalue problems
Three multigrid algorithms are described that can solve the symmetric generalized eigenvalue problem encountered in structural dynamics. First, the multigrid algorithm for solving linear matrix equations is incorporated into the subspace iteration and block Lanczos methods to produce implicit …
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A Parallel Aggregation Algorithm for Inter-Grid Transfer Operators in Algebraic Multigrid
… problems, there is an increasing need for fast algorithms. Nowadays there are many GPU/CPU parallel approaches to solve such problems. Multigrid methods can be used to solve large-scale problems, or even better they can be used to precondition the conjugate gradient method, yielding better …
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Implicit-explicit methods for time-dependent PDE’s
… relative performance in the context of fast multigrid algorithms and aliasing reduction for spectral methods. For the prototype linear advection-diffusion equation, a stability analysis for first, second, third and fourth order multistep IMEX schemes is performed. Stable schemes permitting …
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Riblets in the viscous sublayer : Optimal Shape Design of Microstructures
… using finite elements on unstructured grids and multigrid algorithms. The results obtained with this approach give us a drag reduction of approximately 2-6% relative to the drag of the smooth configuration.
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From efficient high-order methods to scientific machine learning.
… serendipity elements and can be extended to multigrid algorithms. Lastly, we introduce Torchfire, a differentiable programming interface that combines PyTorch and Firedrake to perform model-constrained deep learning of solutions of parameterized PDEs and PDE-constrained inverse problems. It …
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From efficient high-order methods to scientific machine learning.
… serendipity elements and can be extended to multigrid algorithms. Lastly, we introduce Torchfire, a differentiable programming interface that combines PyTorch and Firedrake to perform model-constrained deep learning of solutions of parameterized PDEs and PDE-constrained inverse problems. It …
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Integration and Validation of Flow Image Quantification (Flow-IQ) System
… of this work was to test the performance of DPIV algorithms in wall shear flows, and to test the performance of several particle sizing algorithms for use in spray sizing and average diameter calculation. Several particle sizing algorithms which assume a circular particle profile were tested with …
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Application of Helmholtz/Hodge Decomposition to Finite Element Methods for Two-Dimensional Maxwell's Equations
… equations. We use the extraction formulas and multigrid method to overcome the low regularity of the solution for the Maxwell interface problem. The theoretical results obtained in this dissertation are confirmed by numerical experiments.