Parallel Algorithms in the Finite Element Approximation of Flow Problems

Parallel Algorithms in the Finite Element Approximation of Flow Problems
Author: Max D. Gunburger
Publisher:
Total Pages: 20
Release: 1988
Genre:
ISBN:

We discuss a portion of the research of the which has been carried out during the past years under AFOSR sponsorship. This includes work on finite element methods for a Ladyshenskaya model of viscous incompressible flow, hyperbolic partial differential equations, exterior problems, algebraic turbulence models, streamfunction vorticity formulations of ciscous flows and first order elliptic systems of partial differential equations, and on substructing methods for the approximate solution of partial differential equations. (MJM).

Parallel Finite Element Computations

Parallel Finite Element Computations
Author: B. H. V. Topping
Publisher:
Total Pages: 328
Release: 1996
Genre: Mathematics
ISBN:

Describing the main procedures for the parallelization of the finite element method for distributed memory architectures, this book is for engineers, computer scientists and mathematicians working on the application of high performance computing to finite element methods. Its procedures are applicable to distributed memory computer architectures.

Parallel Computing Using the Multiscale Finite Element Method for Sub-surface Flow Models

Parallel Computing Using the Multiscale Finite Element Method for Sub-surface Flow Models
Author: Anshul Goyal
Publisher:
Total Pages: 102
Release: 2016
Genre:
ISBN:

Subsurface flows, occurring in groundwater movement and production of hydrocarbons in the petroleum industry, are affected by the heterogeneity of the medium varying over large scales. In this thesis, we have used state of the art multiscale methods to solve one such flow model, influenced by high contrast permeability field. The focus is on the elliptic pressure equation which is solved on both fine and coarse scale for comparison purposes. Shared memory parallelism has been achieved for generating basis functions, which is computationally the most expensive portion of the multiscale implementation. Parallel systematic spectral enrichment using the GMsFEM (Generalized Multiscale Finite Element Method) is the key feature of the current work and has been compared with the MsFEM (Multiscale Finite Element Method). Efficiency of algorithmic implementation has been first tabulated for a two-dimensional finite element code using the MATLAB parallel computing toolbox and also has been given a more generalized form using a three-dimensional finite element code written in OpenMP (Open Multiprocessing) and C++. The timing comparison shows a significant decline in the execution time for the algorithms. It indicates that a higher level of enrichment and desired accuracy is achievable for large scale problems. Computational time gain and fewer memory requirements are two key features achieved in this work. Distributed parallel computing can further be implemented to achieve mass parallelism through which one can solve large problems accurately and efficiently when compared to benchmark fine scale solutions where global system solver, memory requirements and execution time become significant issues.