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Computational Engineering at NACADAlvaro L.G.A. Coutinho

NACAD-Center for Parallel ComputingCOPPE/Federal University of Rio de Janeiro, Brazil

alvaro@nacad.ufrj.brwww.nacad.ufrj.br

October, 2003

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Contents:Contents:Introduction: Who we are and what we doField Equations for Grid-based ApplicationsFinite Element DiscretizationComputational IngredientsGrid-based Demonstration ProblemsConcluding Remarks

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IntroductionIntroductionWho are we ?

NACAD Center for Parallel Computing, COPPE/Federal University of Rio de Janeiro, Brazil

Associated Laboratories

LAMCE, NTT, LAB2M, CEMONComputer Methods in Engineering Lab, Data Mining Lab, Basin Simulation Lab, Environment Monitoring Lab Civil Engineering Department

LASPOTPower Systems LaboratoryElectrical Engineering Department

Parallel Computing LaboratoryComputer Science Department

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Introduction (contIntroduction (contd)d)What we do ? High Performance Computing: research and development

Parallel, vector, and cluster computing Scientific visualization Applications to:

Petroleum EngineeringPower SystemsAerospace Engineering Environment Data MiningGovernanceFinancial EngineeringMeteorology

Cray SV1

InfoServer Itautec

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Field Equations for GridField Equations for Grid--based based ApplicationsApplications

General Form of PDEs for Engineering Systems

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Governing Equations in Eulerian Framework

=

+=++

in

inTpt

0

),f(q

u

c1u-uuu

Navier-Stokes Equations

Energy Transport Equation

=+ inThTkTc

tTc

pp),()(

1cu

Mass Transfer Equations

=+ inT

t),(h)(

2cccuc

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Eulerian Governing Equations

Multi-phase Darcy-flow in Porous Media:

j

ij

x

=

K

u

zg = p

( )

qxt

S

j

ij +

=

K

=1, 2, ... , nphases

From Mendona, 2003

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Governing Equations in Lagrangian Framework

Equation of Motion for Solids and Structures:

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Lagrangian Governing Equations

Remarks:

From Quaranta&Alves, 2002

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Arbitrary Eulerian Lagrangian Governing Equations

Incompressible N_S equations in ALE frame moving with velocity w:

Velocity w is conveniently adjusted to Eulerian (w=0), far from moving object to Lagrangian (w=u) on the fluid-structure interface.Fluid is considered attached to the body.Need to solve extra-field equation to define mesh movement: our choice is to solve the Laplacian.

From Felippa, Park and Farhat (CMAME, 2001)

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FEM DiscretizationFEM Discretization

Good mathematical background and ability to handle complex geometries by using unstructured grids

FEM FEM DiscretizationDiscretization

Variational Formulation

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FEM Computational IngredientsFEM Computational Ingredients

Space-Time AdaptationAdaptive step sizeMesh refinement/unrefinement

Non-linear Solution Methods, Iterative SolversData Structures: Memory complexity O(meshparameters)Partitioned Time-Marching SchemesHigh Performance Computing Issues

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Adaptive Step size Control for Time Step Selection

CFL

Valli, Coutinho, Carey, CNME, 2002

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Adaptive Mesh Refinement

Fundamental for high accuracy computationsWe prefer adaptive remeshing with Delaunay triangulation with a coarse background meshZZ viscous stress error indicator do guide adaptationALE we need to move both background and current meshes

Sampaio&Coutinho, IJNMF, 1999

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Nonlinear Solution Method: Inexact Newton Method

Given utol, rtol, relative unknown and residual tolerances and RHS vector, b do i while convergence Compute residual vector, 11 = iii uJbr Update jacobian matrix, iJ Compute tolerance for iterative driver, i Solve ii ruJ = for tolerance i Update solution, uuu +

If toluuu

and toli

rbr

then convergence

End while

Backtracking is sometimes useful !Coutinho et al, IJNME, 2001

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Iterative Solution Methods

Symmetric systems: PCGNon-symmetric systems: GMRESMatrix-vector products Element-by-element

Matrix-free

Preconditioning keeping same data structures

epKpKnel

1ee

=

=

( )=

=nel

1eepLwpK )(,

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Edge-based Solution

FE mesh Graph representation

Sparse matrix

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Edge-based FE Scheme

Disassembling of Element Matrix

++=

0000

0

00

000

00000

321 EdgeEdgeEdgeElement

Assembling of Edge Matrix

I

J

K

L

E1E2

EdgeIJ Elem Elem

=

+

1 2

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Edge Matrices and Matvec

=

=m

s

es

e

1KK

Element matrices disassemblingm is the number of element edges, which is 6 for tetrahedra or 28 for hexahedra.

Edge Matrix

=Es

ess KK E is the set of all elements sharinga given edge s

Edge-by-edge matrix-vector product

s

nedges

ss pKpK

==

1

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Computational costs for symmetric sparse matrix-vector products in tetrahedral meshes

DataStructure

Memory flop i/a

EBE 429 nnodes 1,386 nnodes 198 nnodes

Edges 63 nnodes 252 nnodes 126 nnodes

nel 5.5nnodes, nedges 7nnodes

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SuperedgesIdea introduced by Lhner (94) and implemented in CSM and CFD by Martins et al (97,98,02) and Coutinho et al (01) for tetrahedraand hexahedraDesigned to improve i/a ratio and flop balanceOnce data have been gathered from memory to processor (registers), reuse them as much as possibleFormed by edge list reorderingDifferent grouping are possible increasing code complexityNodes reordered in increasing order as they appear in the superedge list (Lhner, 93)2D triangle, 3D tetrahedra

Superedges in blue

Guanabara Bay

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Partitioned Time Marching Scheme

Mesh partitioning algorithms for time-marching: I/E, E/E, Iterative/Direct, etc

Partition can evolve in time

Implicit Edges in RED

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High Performance Computing High Performance Computing IssuesIssues

FEM is a unstructured grid method characterized by:

Discontinuous data no i-j-kaddressingGather-scatter operationsRandom memory access patternsData dependenceMinimize indirect addressing is a must

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Parallel Solution Strategies

Shared Memory: Mesh Coloring

Distributed Memory: Mesh Partitioning

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GridGrid--based Demonstration based Demonstration ProblemsProblems

Fluid Flow in Deformable Porous Media -Well Stability: What you can do in a PCReservoir Engineering: Effects of Memory SpeedHydrodynamic computations in Araruama Lagoon: Example of Cluster ComputingFluid-Structure Interaction in Rio-Niteroi BridgeStress analysis of sedimentary basins

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Fluid Flow in Deformable Porous Media Well Stability: What you can do in a PC

Quasi-static deformation of plastic porous media coupled with 1-phase flowStrain depends on poro-pressurePorosity is function of volumetric changeStaggered coupling

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Coupled 1-phase (water) and Solid in 3D: Vertical and Horizontal Wells

Mesh Data

36,105 nodes,

191,163 elements,

236,090 edges (23% simple, 18% s3 and 59% s6)

Solid Material Data

Internal radius 0.11 m; External Radius 20.0 m

Formation Pressure: 32.4 MPa

Insitu stresses (V/H): 32.1 MPa; 9.0 MPa

Youngs modulus: 1.2 GPa, Poisson: 0.2

Internal angle: 45; Cohesion: 8.5 MPa; Biot: 1.00

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Coupled 1-phase (water) and Solid in 3D: Vertical and Horizontal Wells

Stiffness Updating

PCG total PCG Average

NR BCT Time (s)

Secant 931 93,1 10 0 579,1 Tangent 931 93,1 10 0 551,4

Stiffness Updating

PCG total PCG average

NR BCT Time (s)

Secant 6.049 40,1 148 0 4.709,2Tangent 1.291 92,2 14 4 981,4

3 poro-pressure load steps: 34,088, 14,9 e 4,9 MPa;Non-linear Solver: Edge-based Inexact Newton; PIII 1GHz

Vertical Well

Horizontal Well

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Numerical Results for Horizontal Well

Plastic fringes around well Total displacements around well

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Reservoir Engineering: Effects of Memory Speed

True heterogeneous reservoir: SPE 10thcomparative project: http://www.streamsim.com/pages/spe10.htmlReservoir dimensions: 1200x2200x170 ftUnstructured grid generated from 60x220x85 cells

5,610,000 tetrahedra1,159,366 points6,843,365 edges

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Effects Memory Speed

From Jack Dongarra, 2002

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Preprocessing and Matvec performance on the CRAY SV1

SuperE

Edge

G&

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