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Ph.D. Thesis Numerical Solution of PDEs and Their Object-oriented Parallel Implementations
Xing Cai October 26, 1998
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Overview 10 publications covering: Numerical solution of PDEs
Object orientation & parallel computing Additional work October 26, 1998
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Nonlinear water waves Free water surface Dynamic solution domain
3D velocity potential field Divergence free, irrotational Efficient numerical simulation October 26, 1998
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Mathematical model October 26, 1998
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Domain transformation
October 26, 1998
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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
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An optimal preconditioner
Pressure equation Low permeable zone Preconditioner Eigenvalue analysis Two-level preconditioning scheme October 26, 1998
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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
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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
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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
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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
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A generic framework Object-oriented programming
An add-on library (SPMD model) Flexibility and portability Simplified parallelization process for end-user October 26, 1998
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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
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O-O implementation ParaPDESolver SPAdmUDC BasicDDSolver KrylovDDSolver
ConjGradDD BiCGStabDD October 26, 1998
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Subdomain Simulator Subdomain Simulator -- a generic representation
C++ class hierarchy Standard interface of generic member functions October 26, 1998
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Coding example Existing sequential simulator PoissonSolver
New subdomain solver SubdomainFESolver SubdomainFEMSolver PoissonSolver SubdomainFESolver October 26, 1998
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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
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2-phase porous media flow
October 26, 1998
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Adaptivity October 26, 1998
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Multigrid 1 2 3 4 Common October 26, 1998
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DD approach Schwarz two level method Multigrid for coarse grid
Multigrid for local sub-problems October 26, 1998
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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
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Partition example October 26, 1998
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Solving 2D Lapalce’s equation
October 26, 1998
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CPU-measurements October 26, 1998
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Scalability Measurements obtained on 16 processors October 26, 1998
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Scientific visualization
October 26, 1998
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Acknowledgements Sincere thanks to my supervisors: Aslak Tveito
Even Mehlum Hans Petter Langtangen October 26, 1998
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