Ph.D. Thesis Numerical Solution of PDEs and Their Object-oriented Parallel Implementations Xing Cai October 26, 1998.

Slides:



Advertisements
Similar presentations
Parallel Jacobi Algorithm Steven Dong Applied Mathematics.
Advertisements

A Discrete Adjoint-Based Approach for Optimization Problems on 3D Unstructured Meshes Dimitri J. Mavriplis Department of Mechanical Engineering University.
03/29/2006, City Univ1 Iterative Methods with Inexact Preconditioners and Applications to Saddle-point Systems & Electromagnetic Maxwell Systems Jun Zou.
1 Numerical Solvers for BVPs By Dong Xu State Key Lab of CAD&CG, ZJU.
Geometric (Classical) MultiGrid. Hierarchy of graphs Apply grids in all scales: 2x2, 4x4, …, n 1/2 xn 1/2 Coarsening Interpolate and relax Solve the large.
High performance flow simulation in discrete fracture networks and heterogeneous porous media Jocelyne Erhel INRIA Rennes Jean-Raynald de Dreuzy Geosciences.
Parallel Solution of Navier Stokes Equations Xing Cai Dept. of Informatics University of Oslo.
An efficient parallel particle tracker For advection-diffusion simulations In heterogeneous porous media Euro-Par 2007 IRISA - Rennes August 2007.
CISC October Goals for today: Foster’s parallel algorithm design –Partitioning –Task dependency graph Granularity Concurrency Collective communication.
CSE351/ IT351 Modeling and Simulation
Avoiding Communication in Sparse Iterative Solvers Erin Carson Nick Knight CS294, Fall 2011.
Landscape Erosion Kirsten Meeker
Network and Grid Computing –Modeling, Algorithms, and Software Mo Mu Joint work with Xiao Hong Zhu, Falcon Siu.
Chapter 13 Finite Difference Methods: Outline Solving ordinary and partial differential equations Finite difference methods (FDM) vs Finite Element Methods.
MCE 561 Computational Methods in Solid Mechanics
Module on Computational Astrophysics Jim Stone Department of Astrophysical Sciences 125 Peyton Hall : ph :
PETE 603 Lecture Session #29 Thursday, 7/29/ Iterative Solution Methods Older methods, such as PSOR, and LSOR require user supplied iteration.
Direct and iterative sparse linear solvers applied to groundwater flow simulations Matrix Analysis and Applications October 2007.
Numerical methods for PDEs PDEs are mathematical models for –Physical Phenomena Heat transfer Wave motion.
1 Parallel Simulations of Underground Flow in Porous and Fractured Media H. Mustapha 1,2, A. Beaudoin 1, J. Erhel 1 and J.R. De Dreuzy IRISA – INRIA.
Tools for Multi-Physics Simulation Hans Petter Langtangen Simula Research Laboratory Oslo, Norway Department of Informatics, University of Oslo.
An approach for solving the Helmholtz Equation on heterogeneous platforms An approach for solving the Helmholtz Equation on heterogeneous platforms G.
Processing of a CAD/CAE Jobs in grid environment using Elmer Electronics Group, Physics Department, Faculty of Science, Ain Shams University, Mohamed Hussein.
Solving the Poisson Integral for the gravitational potential using the convolution theorem Eduard Vorobyov Institute for Computational Astrophysics.
Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Parallel Programming in C with MPI and OpenMP Michael J. Quinn.
ParCFD Parallel computation of pollutant dispersion in industrial sites Julien Montagnier Marc Buffat David Guibert.
CFD Lab - Department of Engineering - University of Liverpool Ken Badcock & Mark Woodgate Department of Engineering University of Liverpool Liverpool L69.
Strategies for Solving Large-Scale Optimization Problems Judith Hill Sandia National Laboratories October 23, 2007 Modeling and High-Performance Computing.
The swiss-carpet preconditioner: a simple parallel preconditioner of Dirichlet-Neumann type A. Quarteroni (Lausanne and Milan) M. Sala (Lausanne) A. Valli.
A Software Strategy for Simple Parallelization of Sequential PDE Solvers Hans Petter Langtangen Xing Cai Dept. of Informatics University of Oslo.
Interactive Computational Sciences Laboratory Clarence O. E. Burg Assistant Professor of Mathematics University of Central Arkansas Science Museum of Minnesota.
Parallel Solution of the Poisson Problem Using MPI
Parallelizing finite element PDE solvers in an object-oriented framework Xing Cai Department of Informatics University of Oslo.
Implementing Hypre- AMG in NIMROD via PETSc S. Vadlamani- Tech X S. Kruger- Tech X T. Manteuffel- CU APPM S. McCormick- CU APPM Funding: DE-FG02-07ER84730.
Domain Decomposition in High-Level Parallelizaton of PDE codes Xing Cai University of Oslo.
A Dirichlet-to-Neumann (DtN)Multigrid Algorithm for Locally Conservative Methods Sandia National Laboratories is a multi program laboratory managed and.
We have recently implemented a microwave imaging algorithm which incorporated scalar 3D wave propagation while reconstructing a 2D dielectric property.
23/5/20051 ICCS congres, Atlanta, USA May 23, 2005 The Deflation Accelerated Schwarz Method for CFD C. Vuik Delft University of Technology
Outline Introduction Research Project Findings / Results
Discretization for PDEs Chunfang Chen,Danny Thorne Adam Zornes, Deng Li CS 521 Feb., 9,2006.
An Object-Oriented Software Framework for Building Parallel Navier-Stokes Solvers Xing Cai Hans Petter Langtangen Otto Munthe University of Oslo.
A Software Framework for Easy Parallelization of PDE Solvers Hans Petter Langtangen Xing Cai Dept. of Informatics University of Oslo.
On the Performance of PC Clusters in Solving Partial Differential Equations Xing Cai Åsmund Ødegård Department of Informatics University of Oslo Norway.
F. Fairag, H Tawfiq and M. Al-Shahrani Department of Math & Stat Department of Mathematics and Statistics, KFUPM. Nov 6, 2013 Preconditioning Technique.
Adaptive grid refinement. Adaptivity in Diffpack Error estimatorError estimator Adaptive refinementAdaptive refinement A hierarchy of unstructured gridsA.
Quality of Service for Numerical Components Lori Freitag Diachin, Paul Hovland, Kate Keahey, Lois McInnes, Boyana Norris, Padma Raghavan.
Multipole-Based Preconditioners for Sparse Linear Systems. Ananth Grama Purdue University. Supported by the National Science Foundation.
Parallel Computing Activities at the Group of Scientific Software Xing Cai Department of Informatics University of Oslo.
A Software Framework for Easy Parallelization of PDE Solvers Hans Petter Langtangen Xing Cai Dept. of Informatics University of Oslo.
Solving linear systems in fluid dynamics P. Aaron Lott Applied Mathematics and Scientific Computation Program University of Maryland.
High Performance Computing Seminar II Parallel mesh partitioning with ParMETIS Parallel iterative solvers with Hypre M.Sc. Caroline Mendonça Costa.
Application of Design Patterns to Geometric Decompositions V. Balaji, Thomas L. Clune, Robert W. Numrich and Brice T. Womack.
Relaxation Methods in the Solution of Partial Differential Equations
ON NUMERICAL UPSCALING FOR STOKES AND STOKES-BRINKMAN FLOWS
Hui Liu University of Calgary
Xing Cai University of Oslo
Analysis of the Solver Performance for Stokes Flow Problems in Glass Forming Process Simulation Models Speaker: Hans Groot Supervisors: Dr. Hegen (TNO.
Introduction to Design Patterns
Deflated Conjugate Gradient Method
Deflated Conjugate Gradient Method
GENERAL VIEW OF KRATOS MULTIPHYSICS
Supported by the National Science Foundation.
Objective Numerical methods Finite volume.
Investigators Tony Johnson, T. V. Hromadka II and Steve Horton
Introduction to Scientific Computing II
A Software Framework for Easy Parallelization of PDE Solvers
Comparison of CFEM and DG methods
Parallelizing Unstructured FEM Computation
Oswald Knoth, Detlev Hinneburg
Presentation transcript:

Ph.D. Thesis Numerical Solution of PDEs and Their Object-oriented Parallel Implementations Xing Cai October 26, 1998

Overview 10 publications covering: Numerical solution of PDEs Object orientation & parallel computing Additional work October 26, 1998

Nonlinear water waves Free water surface Dynamic solution domain 3D velocity potential field Divergence free, irrotational Efficient numerical simulation October 26, 1998

Mathematical model October 26, 1998

Domain transformation October 26, 1998

Solving Laplace’s equation Variable coefficient after transformation Domain imbedding Finite element discretization Fast Poisson solver as preconditioner Fixed computational domain Simple shape October 26, 1998

An optimal preconditioner Pressure equation Low permeable zone Preconditioner Eigenvalue analysis Two-level preconditioning scheme October 26, 1998

A question Starting point: sequential PDE simulators. How to do the parallelization? Resulting parallel simulators should have Good parallel performance Good overall numerical performance A relative simple parallelization process We need a good parallelization strategy a good implementation of the strategy October 26, 1998

3 key words Parallel Computing faster solution, larger simulation Domain Decomposition (additive Schwarz method) good algorithmic efficiency mathematical foundation of parallelization Object-Oriented Programming extensible sequential simulator flexible implementation framework for parallelization October 26, 1998

A simulator-parallel model Each processor hosts an arbitrary number of subdomains One subdomain is assigned with a sequential simulator Flexibility - different linear system solvers, preconditioners, convergence monitors etc. can easily be chosen for different subproblems Domain decomposition at the level of subdomain simulators! October 26, 1998

Advantages & disadvantages Reuse of existing sequential simulators Data distribution is implied No need for global data Needs additional functionalities for exchanging nodal values inside the overlapping region Needs some global administration October 26, 1998

A generic framework Object-oriented programming An add-on library (SPMD model) Flexibility and portability Simplified parallelization process for end-user October 26, 1998

Administrator Parameter Interface solution method or preconditioner, max iterations, stopping criterion etc DD algorithm Interface access to predefined numerical algorithm e.g. CG Operation Interface (standard codes & UDC) access to subdomain simulators, matrix-vector product, inner product etc

O-O implementation ParaPDESolver SPAdmUDC BasicDDSolver KrylovDDSolver ConjGradDD BiCGStabDD October 26, 1998

Subdomain Simulator Subdomain Simulator -- a generic representation C++ class hierarchy Standard interface of generic member functions October 26, 1998

Coding example Existing sequential simulator PoissonSolver New subdomain solver SubdomainFESolver SubdomainFEMSolver PoissonSolver SubdomainFESolver October 26, 1998

P: number of processors. 2D Poisson’s equation Fixed M=32 subdomains based on a 481 x 481 global grid. Straightforward parallelization of an existing simulator. Subdomain solves use CG+FFT P: number of processors. October 26, 1998

2-phase porous media flow October 26, 1998

Adaptivity October 26, 1998

Multigrid 1 2 3 4 Common October 26, 1998

DD approach Schwarz two level method Multigrid for coarse grid Multigrid for local sub-problems October 26, 1998

Grid generation/partition Non-overlapping grid partition on a single processor (metis) Create overlap Pick subgrid for each processor Uniform refinement of subgrid Communication pattern determination October 26, 1998

Partition example October 26, 1998

Solving 2D Lapalce’s equation October 26, 1998

CPU-measurements October 26, 1998

Scalability Measurements obtained on 16 processors October 26, 1998

Scientific visualization October 26, 1998

Acknowledgements Sincere thanks to my supervisors: Aslak Tveito Even Mehlum Hans Petter Langtangen October 26, 1998