Fast Integral Equation Solver For Variable Coefficient Elliptic Pdes In Complex Geometries
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Fast Integral Equation Solver for Variable Coefficient Elliptic PDEs in Complex Geometries
This dissertation presents new numerical algorithms and related software for the numerical solution of elliptic boundary value problems with variable coefficients on certain classes of geometries. The target applications are problems in electrostatics, fluid mechanics, low-frequency electromagnetic and acoustic scattering. We present discretizations based on integral equation formulations which are founded in potential theory and Green's functions. Advantages of our methods include high-order discretization, optimal algorithmic complexity, mesh-independent convergence rate, high-performance and parallel scalability. First, we present a parallel software framework based on kernel independent fast multipole method (FMM) for computing particle and volume potentials in 3D. Our software is applicable to a wide range of elliptic problems such as Poisson, Stokes and low-frequency Helmholtz. It includes new parallel algorithms and performance optimizations which make our volume FMM one of the fastest constant-coefficient elliptic PDE solver on cubic domains. We show that our method is orders of magnitude faster than other N-body codes and PDE solvers. We have scaled our method to half-trillion unknowns on 229K CPU cores. Second, we develop a high-order, adaptive and scalable solver for volume integral equation (VIE) formulations of variable coefficient elliptic PDEs on cubic domains. We use our volume FMM to compute integrals and use GMRES to solve the discretized linear system. We apply our method to compute incompressible Stokes flow in porous media geometries using a penalty function to enforce no-slip boundary conditions on the solid walls. In our largest run, we achieved 0.66 PFLOP/s on 2K compute nodes of the Stampede system (TACC). Third, we develop novel VIE formulations for problems on geometries that can be smoothly mapped to a cube. We convert problems on non-regular geometries to variable coefficient problems on cubic domains which are then solved efficiently using our volume FMM and GMRES. We show that our solver converges quickly even for highly irregular geometries and that the convergence rates are independent of mesh refinement. Fourth, we present a parallel boundary integral equation solver for simulating the flow of concentrated vesicle suspensions in 3D. Such simulations provide useful insights on the dynamics of blood flow and other complex fluids. We present new algorithmic improvements and performance optimizations which allow us to efficiently simulate highly concentrated vesicle suspensions in parallel.
Fast Direct Solvers for Elliptic PDEs
Fast solvers for elliptic PDEs form a pillar of scientific computing. They enable detailed and accurate simulations of electromagnetic fields, fluid flows, biochemical processes, and much more. This textbook provides an introduction to fast solvers from the point of view of integral equation formulations, which lead to unparalleled accuracy and speed in many applications. The focus is on fast algorithms for handling dense matrices that arise in the discretization of integral operators, such as the fast multipole method and fast direct solvers. While the emphasis is on techniques for dense matrices, the text also describes how similar techniques give rise to linear complexity algorithms for computing the inverse or the LU factorization of a sparse matrix resulting from the direct discretization of an elliptic PDE. This is the first textbook to detail the active field of fast direct solvers, introducing readers to modern linear algebraic techniques for accelerating computations, such as randomized algorithms, interpolative decompositions, and data-sparse hierarchical matrix representations. Written with an emphasis on mathematical intuition rather than theoretical details, it is richly illustrated and provides pseudocode for all key techniques. Fast Direct Solvers for Elliptic PDEs is appropriate for graduate students in applied mathematics and scientific computing, engineers and scientists looking for an accessible introduction to integral equation methods and fast solvers, and researchers in computational mathematics who want to quickly catch up on recent advances in randomized algorithms and techniques for working with data-sparse matrices.
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