Krylov Subspace Iterative Methods Research Articles

Accurate Description of Coulombic Interactions in Organic Field‐Effect Transistors Enabled by Efficient 3D Poisson's Equation Solver with Mixed Boundary Conditions

AbstractThe rational development of organic electronic devices can greatly benefit from a molecular‐level description, where an accurate description of the Coulombic interactions among charge carriers holds paramount importance. However, the molecular‐level organic field‐effect transistor (OFET) simulations do not fully include the short‐range charge‐carrier Coulombic interactions, thus limiting their accuracy. Here, an efficient solution is demonstrated to the 3D Poisson's equation with mixed boundary conditions, optimized for integration into the simulations of organic electronic devices. It leverages the finite difference method for discretization, the Krylov subspace iterative methods for solving the linear system, the algebraic multigrid algorithm for preconditioning, and OpenMP and CUDA parallelization for acceleration. For the organic field‐effect transistors of micrometer sizes or smaller dimensions, obtaining the electric potential within the device takes less than 0.1 s, which is sufficiently efficient for molecular‐level modeling. As a result, both short‐ and long‐range electrostatic interactions are successfully incorporated in the molecular‐level modeling of OFET devices. This integration significantly enhances the robustness of OFET modeling for future applications.

Matrix splitting preconditioning based on sine transform for solving two-dimensional space-fractional diffusion equations

Finite difference discretization of the two-dimensional space-fractional diffusion equations derives a complicated linear system consisting of identity matrix and four scaled block-Toeplitz with Toeplitz block (BTTB) matrices resulted from the left and right Riemann–Liouville fractional derivatives in different directions. Incorporating with the diffusion coefficients and the symmetric parts of the BTTB matrices, we construct a diagonal and symmetric splitting (DSS) iteration method, which is demonstrated to be convergent conditionally when the considered space-fractional diffusion equations have sufficiently close diffusion coefficients. By further replacing the symmetric Toeplitz matrices involved in the BTTB matrices with τ matrices, an approximated DSS (ADSS) preconditioner based on two-dimensional fast sine transform is designed to accelerate the convergence rates of the Krylov subspace iteration methods. In this way, the total computational complexity of the ADSS-preconditioned GMRES method will be of O(n2logn), where n2 represents the dimension of the corresponding discrete linear system. In addition, theoretical analysis demonstrates that the eigenvalues of the ADSS-preconditioned matrix are weakly clustered around a complex disk centered at 1 with the radius less than 1. Numerical experiments show that the ADSS-preconditioned GMRES method is much more efficient than the other existing methods, and can show h-independent convergence behavior.

Algebraic spectral analysis of the DSSR preconditioner

The dimension-wise splitting with selective relaxation (DSSR) is an efficient iterative method for solving linear systems arising from the discretization of incompressible Navier-Stokes equations. The unconditional convergence properties and optimal relaxation parameters are analyzed at the continuous level on model problems in Gander et al. (2016) [15] In this paper, we provide an algebraically spectral analysis of the DSSR preconditioner when applied to Krylov subspace methods. The analysis indicates that most eigenvalues of the preconditioned matrix are 1, and the corresponding eigenspace is nondeficient, which is an important favorable property for fast convergence of Krylov subspace iterative method. Finally, the preconditioner is explained from the deflation point of view, which provides a clue for developing hybrid direct iterative solvers.

On preconditioning of double saddle point linear systems arising from liquid crystal director modeling

We establish an effective iteration method for solving the double saddle point problems arising from liquid crystal director modeling. The convergence property of the proposed iteration method is studied in detail and the induced preconditioner is used to accelerate the Krylov subspace iteration methods. Moreover, the spectral property of this preconditioned matrix is investigated. Numerical example validates the efficiency of the proposed preconditioner.

An unconditionally convergent RSCSCS iteration method for Riesz space fractional diffusion equations with variable coefficients

In this paper, a respectively scaled circulant and skew-circulant splitting (RSCSCS) iteration method is employed to solve the Toeplitz-like linear systems arising from time-dependent Riesz space fractional diffusion equations with variable coefficients. The RSCSCS iteration method is shown to be convergent unconditionally by a novel technique, and only requires computational costs of O(NlogN) with N denoting the number of interior mesh points in space. In theory, we obtain an upper bound for the convergence factor of the RSCSCS iteration method and discuss the optimal value of its iteration parameter that minimizes the corresponding upper bound. Meanwhile, we also design a fast induced RSCSCS preconditioner to accelerate the convergence rate of the Krylov subspace iteration method likes generalized minimal residual (GMRES) method. Numerical results are presented to show that the efficiencies of our proposed RSCSCS iteration method and the preconditioned GMRES method with the RSCSCS preconditioner.

Tensor Krylov subspace methods via the Einstein product with applications to image and video processing

In the present paper, we are interested in developing iterative Krylov subspace methods in tensor structure to solve a class of multilinear systems via the Einstein product. In particular, we develop tensor variants of the GMRES and Golub–Kahan bidiagonalization processes in tensor framework. We further consider the case that mentioned equation may be possibly corresponds to a discrete ill-posed multidimensional problem. Applications arising from color image and video restoration are included.

High-order implicit weighted compact nonlinear scheme for nonlinear coupled viscous Burgers’ equations

In this paper a high-order implicit weighted compact nonlinear scheme for nonlinear coupled viscous Burgers’ equations is presented. The fifth-order weighted compact nonlinear scheme is used for the spatial discretization, while the third-order diagonal implicit Runge–Kutta method is used for the time discretization. The generated nonlinear system is solved by the Jacobian-free Newton–Krylov nonlinear solver, which is composed of the outer Newton iteration method and the inner Krylov subspace iteration method. Stability analysis shows that the presented implicit weighted compact nonlinear scheme is unconditionally stable. Numerical results indicate that the implicit scheme can achieve the designed third-order accuracy in time and has a great advantage in the computation efficiency compared to the third-order explicit total variation diminishing Runge–Kutta weighted essentially non-oscillatory scheme. In addition, the implicit scheme can capture discontinuities and shock waves with high resolution and can solve Burgers’ equations with all kinds of Reynolds numbers.

Block splitting preconditioner for time-space fractional diffusion equations

<abstract><p>For solving a block lower triangular Toeplitz linear system arising from the time-space fractional diffusion equations more effectively, a single-parameter two-step split iterative method (TSS) is introduced, its convergence theory is established and the corresponding preconditioner is also presented. Theoretical analysis shows that the original coefficient matrix after preconditioned can be expressed as the sum of the identity matrix, a low-rank matrix, and a small norm matrix. Numerical experiments show that the preconditioner improve the calculation efficiency of the Krylov subspace iteration method.</p></abstract>

Parallel finite volume simulation of the spherical shell dynamo with pseudo-vacuum magnetic boundary conditions

In this paper, we study the parallel simulation of the magnetohydrodynamic (MHD) dynamo in a rapidly rotating spherical shell with pseudo-vacuum magnetic boundary conditions. A second-order finite volume scheme based on a collocated quasi-uniform cubed-sphere grid is applied to the spatial discretization of the MHD dynamo equations. To ensure the solenoidal condition of the magnetic field, we adopt a widely-used approach whereby a pseudo-pressure is introduced into the induction equation. The temporal integration is split by a second-order approximate factorization approach, resulting in two linear algebraic systems both solved by a preconditioned Krylov subspace iterative method. A multi-level restricted additive Schwarz preconditioner based on domain decomposition and multigrid method is then designed to improve the efficiency and scalability. Accurate numerical solutions of two benchmark cases are obtained with our code, comparable to the existing local method results. Several large-scale tests performed on the Sunway TaihuLight supercomputer show good strong and weak scalabilities and a noticeable improvement from the multi-level preconditioner with up to 10368 processor cores.

Krylov subspace iterative methods for time domain equivalent sources method based nearfield acoustical holography

This paper studies the acoustic field reconstruction on an arbitrarily shaped vibrating surface using the time-domain equivalent source method (ESM) based near-field acoustic holography (NAH) from measurements of the pressure field on a nearby conformal surface. For the classical frequency-dependent ESM, we represent the acoustic field by a set of frequency-dependent monopole sources strategically distributed over a close and conformal surface to the vibrating structure. We demonstrated that in this setup, the ESM representation approximates the classical integral representations, which justifies the ESM as an extension to the classical integral theory. For time-domain ESM in a similar manner, we demonstrate that a set of time-dependent monopole sources approximates the single layer retarded potential and then characterize the acoustic field. The discretization of time-domain ESM produces a matrix system with a particular sparse structure that can be efficiently solved using Krylov subspace iterative methods. The iterative methods that will be of our interest are Conjugate Gradients Normal equation Residual, Conjugate Gradients Normal equation Error and Least Squares QR. To reduce the amplification of measurement in the numerical reconstructions, we combine the proposed iterative methods with heuristic stopping rules like L-curve, Quasi-Optimality, Hanke–Raus, Brezinski–Rodriguez–Seatzu and a posteriori stopping rule. To determine the best combination of reconstruction technique, iteration and stopping rule, we develop a statistical study that uses multiple samples of numerically generated data by Gaussian pulses over a sphere. We produce these samples using a random source position and different noise levels. Finally, we validate our proposed methodology using scattering data from an elastic spherical shell.

On tensor GMRES and Golub-Kahan methods via the T-product for color image processing

The present paper is concerned with developing tensor iterative Krylov subspace methods to solve large multi-linear tensor equations. We use the T-product for two tensors to define tensor tubal global Arnoldi and tensor tubal global Golub-Kahan bidiagonalization algorithms. Furthermore, we illustrate how tensor-based global approaches can be exploited to solve ill-posed problems arising from recovering blurry multichannel (color) images and videos, using the so-called Tikhonov regularization technique, to provide computable approximate regularized solutions. We also review a generalized cross-validation and discrepancy principle type of criterion for the selection of the regularization parameter in the Tikhonov regularization. Applications to image sequence processing are given to demonstrate the efficiency of the algorithms.

Performance Analysis of the χMD Matrix Solver Package for MODFLOW-USG.

The χMD matrix solver package is incorporated into USGS groundwater modeling software, such as MODFLOW-NWT, MODFLOW-USG, and MT3D. The solver is used to solve matrices assembled through numerical discretization of the groundwater flow equation, and solute transport equations. χMD has demonstrated its higher robustness, faster execution speed, and more efficient memory usage compared to the existing solvers for many types of groundwater flow problems. χMD uses preconditioned iterative Krylov-subspace methods and consists of preconditioning and acceleration modules. Because the solver package uses a variety of preconditioning features including level-based incomplete lower-upper (ILU) factorization method with a drop tolerance scheme, users must choose optimal preconditioning parameters to improve execution speed and robustness. In order to examine how the preconditioning parameters, ILU factorization level, and drop tolerance values affect the overall performance of the matrix solver, we evaluated five different groundwater model applications using MODFLOW-USG that include different numerical complexities. For those five cases, the number of discretization nodes varied from 10,000 cells to 730,300 cells. From the analysis, we found that the preconditioning parameters greatly affect execution times and memory usage of the preconditioning and acceleration procedures. In addition, a combination of the ILU level between five to seven and the drop tolerance value between 10-2 and 10-3 usually resulted in shorter overall execution time. Our study suggests that the users can elicit higher performance and robustness of the χMD matrix solver using this combination of the parameters and enhance computational efficiency of solving groundwater and solute transport problems.

A finite-difference iterative solver of the Helmholtz equation for frequency-domain seismic wave modeling and full-waveform inversion

We have developed a finite-difference iterative solver of the Helmholtz equation for seismic modeling and inversion in the frequency domain. The iterative solver involves the shifted Laplacian operator and two-level preconditioners. It is based on the application of the preconditioners to the Krylov subspace stabilized biconjugate gradient method. A critical factor for the iterative solver is the introduction of a new preconditioner into the Krylov subspace iteration method to solve the linear equation system resulting from the discretization of the Helmholtz equation. This new preconditioner is based on a reformulation of an integral equation-based convergent Born series for the Lippmann-Schwinger equation to an equivalent differential equation. We have determined that our iterative solver combined with the novel preconditioner when incorporated with the finite-difference method accelerates the convergence of the Krylov subspace iteration method for frequency-domain seismic wave modeling. A comparison of a direct solver, a one-level Krylov subspace iterative solver, and our two-level iterative solver verified the accuracy and accelerated convergence of the new scheme. Extensive tests in full-waveform inversion demonstrate the solver’s applicability to such problems.

Cell‐by‐cell approximate Schur complement technique in preconditioning of meshfree discretized piezoelectric equations

AbstractThe radial point interpolation meshfree discretization is a very efficient numerical framework for the analysis of piezoelectricity, in which the fundamental electrostatic equations governing piezoelectric media are solved without mesh generation. Due to the mechanical‐electrical coupling property and the piezoelectric constant, the discrete linear system is sparse, of generalized saddle point form and often very ill conditioned. In this work, we propose a technique for constructing a family of cell‐by‐cell approximate Schur complement matrices, to be used in preconditioning to accelerate the convergence of Krylov subspace iteration methods for such problems. The approximate Schur complement matrices are simply and cheaply constructed in the process of the meshfree discretization and have a sparse structure. It is proved that the so‐constructed approximate Schur complement matrices are spectrally equivalent to the exact Schur complement matrix, which leads to very fast convergence when used in preconditioning. In addition, nondimensionalization of the piezoelectric equations is considered to make the computations more stable. The robustness and the efficiency of the proposed preconditioners is illustrated numerically on two test problems, arising from a piezoelectric strip shear deformation problem and a piezoelectric strip bending problem. Numerical results show that the number of iterations to achieve a given tolerance is independent of the number of degrees of freedom as well as of the various problem parameters.

3-D Crosswell Electromagnetic Inversion Based on General Measures

The crosshole electromagnetic (EM) method is used in reservoir development monitoring and evaluation. It reflects the resistivity distribution between wells in the form of EM response changes and describes the spatial distribution of pore fluids in subsurface reservoirs based on the correlation between resistivity and pore fluids. This technique has been used to describe reservoirs, monitor steam and brine flooding to improve oil recovery, optimize the design of infilled wells, and verify the effectiveness of reservoir numerical simulations. However, due to the complexity of the electrical distribution of underground reservoirs and the limitations of the crosswell EM response range, there is still a lack of practical and effective crosswell EM imaging methods. This article presents a three-dimensional EM inversion scheme for interpreting crosswell data in the frequency domain with general measures. For the forward modeling, the equation for the secondary electric field was discretized using the staggered-grid finite difference scheme and was solved using the Krylov subspace iterative method. For the inversion problem, the general measure of the data misfit and regularization constraints were integrated using the Gauss–Newton minimization method to form an objective function. By selecting appropriate parameters and regularization constraints, the sharp boundaries and blocky features of the inverted target were recovered. The sensitivity was calculated using the reciprocity relationship, and the method was found to be beneficial to determining appropriate initial values of regularization coefficients. Two synthetic data sets and a field data inversion of a crosswell configuration demonstrate the feasibility of this scheme.

Optimal rotated block-diagonal preconditioning for discretized optimal control problems constrained with fractional time-dependent diffusive equations

For a class of optimal control problems constrained with certain time- and space-fractional diffusive equations, by making use of mixed discretizations of temporal finite-difference and spatial finite-element schemes along with Lagrange multiplier approach, we obtain specially structured block two-by-two linear systems. We demonstrate positive definiteness of the coefficient matrices of these discrete linear systems, construct rotated block-diagonal preconditioning matrices, and analyze spectral properties of the corresponding preconditioned matrices. Both theoretical analysis and numerical experiments show that the preconditioned Krylov subspace iteration methods, when incorporated with these rotated block-diagonal preconditioners, can exhibit optimal convergence property in the sense that their convergence rates are independent of both discretization stepsizes and problem parameters, and their computational workloads are linearly proportional with the number of discrete unknowns.

A high accurate scheme for numerical simulation of two-dimensional mass transfer processes in food engineering

This paper contributes to develop a highly accurate numerical method for solving two-dimensional mass transfer equations during convective air drying of apple slices. The numerical scheme is based on the interpolating the solution of the mentioned equations over the roots of the orthogonal Jacobi polynomials (i.e., the Jacobi-Gauss-Lobatto points) in a nodal form. Moreover, for speeding up the procedure of numerical technique, operational matrices of differentiation are applied to discretize the derivatives of both spatial and temporal variables. After implementing the proposed technique, two-dimensional mass transfer equations would be transferred into the associated systems of linear algebraic equations which can be solved by appropriate iterative solvers such as robust Krylov subspace iterative methods. Some constructed artificial examples are provided to show the efficiency and applicability of the Jacobi pseudo-spectral method for solving two-dimensional mass transfer equations. Finally, a real example is considered and numerical results are validated by the experimental data which confirm the accuracy of the presented numerical approach.

GPU Accelerated Nonlinear Electronic Circuits Solver for Transient Simulation of Systems with Large Number of Components

GPU cards have been used for scientific calculations for many years. Despite their ever-increasing performance, there are cases where they may still have problems. This article addresses possible performance and memory issues and their solutions that may occur during GPU calculations of iterative algorithms. Specifically, the article focuses on the optimization of transient simulation of extra-large highly nonlinear time-dependent circuits in SPICE-like electronic circuit simulator core enhanced with NVIDIA/CUDA (Compute Unified Device Architecture) interface and iterative Krylov Subspace methods with emphasis on improved accuracy. The article presents procedures for solving problems that may occur during this integration and negatively affect either the simulation speed or the accuracy of the calculation. Finally, a comparison of the implementation of an iterative calculation procedure with the use of GPU cards, calculation by the direct method and calculation on the CPU only is presented.

About the granularity portability of block‐based Krylov methods in heterogeneous computing environments

SummaryLarge‐scale problems in engineering and science often require the solution of sparse linear algebra problems and the Krylov subspace iteration methods (KM) have led to a major change in how users deal with them. But, for these solvers to use extreme‐scale hardware efficiently a lot of work was spent to redesign both the KM algorithms and their implementations to address challenges like extreme concurrency, complex memory hierarchies, costly data movement, and heterogeneous node architectures. All the redesign approaches bases the KM algorithm on block‐based strategies which lead to the Block‐KM (BKM) algorithm which has high granularity (i.e., the ratio of computation time to communication time). The work proposes novel parallel revisitation of the modules used in BKM which are based on the overlapping of communication and computation. Such revisitation is evaluated by a model of their granularity and verified on the basis of a case study related to a classical problem from numerical linear algebra.

The regularizing properties of global GMRES for solving large-scale linear discrete ill-posed problems with several right-hand sides

The global Krylov subspace iterative methods are an attractive class of iterative solvers for solving linear systems with several right-hand sides. In this paper, the global version of the GMRES method is applied to solve linear discrete ill-posed problems that arise from the discretization of linear ill-posed problems, pattern classification and dimensionality reduction. The regularizing properties of the global GMRES method are analyzed, and a regularized global GMRES method is developed for solving linear discrete ill-posed problems with multiple right-hand sides contaminated by errors. Some numerical experiments on test matrices are presented to show the efficiency of the proposed method.