2005
DOI: 10.1007/11549468_135
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Parallel Edge-Based Inexact Newton Solution of Steady Incompressible 3D Navier-Stokes Equations

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Cited by 11 publications
(14 citation statements)
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“…Further computational gains are obtained from data preprocessing performed by the EdgePack library-a package to improve cache reutilization based on reordering and grouping techniques [40]. All computational kernels are parallelized covering most of distributed and shared memory systems as well as vectorized and pipelined processors [21]. …”
Section: Solution Proceduresmentioning
confidence: 99%
See 1 more Smart Citation
“…Further computational gains are obtained from data preprocessing performed by the EdgePack library-a package to improve cache reutilization based on reordering and grouping techniques [40]. All computational kernels are parallelized covering most of distributed and shared memory systems as well as vectorized and pipelined processors [21]. …”
Section: Solution Proceduresmentioning
confidence: 99%
“…The main characteristics of our incompressible flow solver [19][20][21] are: SUPG and pressure-stabilizing/Petrov-Galerkin (PSPG) [3,22] stabilized finite element formulation; implicit time marching scheme with adaptive time stepping control; advanced inexact Newton solvers; edge-based data structures to save memory and improve performance; support to message passing and shared memory parallel programming models; and large eddy simulation (LES) extensions using a classical Smagorinsky model. We introduce VOF extensions in this flow solver to track the evolving free surface [11,13,14].…”
Section: Introductionmentioning
confidence: 99%
“…The computational domain follows the dimensions described in [32] and the mesh is formed by 446 662 linear tetrahedra, 1 010 367 edges and 81 991 nodes. The Reynolds number is based on the diameter of the cylinder, free-stream velocity and viscosity of the fluid.…”
Section: Vortex Shedding Around a Circular Cylinder At Re = 100mentioning
confidence: 99%
“…Most of the computational effort spent in the solution phase is devoted to matrix-vector products. In order to compute such operations more efficiently, we have used an edge-based data structure as detailed in [43]. According to Ribeiro and Coutinho [36], this data structure, when applied to problems as those described in this work, is able to reduce indirect memory access, memory requirements to hold the coefficients of the stiffness matrices and the number of floating point operations when compared with other traditional data structures such as element by element or compressed sparse row.…”
Section: Solution Proceduresmentioning
confidence: 99%
“…Time integration is a predictor-multicorrector algorithm with adaptive timestepping by a proportional-integral-Derivative (PID) controller (further details available in [42]). Within the flow solution loop, the multi-correction steps correspond to the inexact-Newton method as described in [43]. In this method, the tolerance of the linear solver is adapted according to the history of the solution residua.…”
Section: Solution Proceduresmentioning
confidence: 99%