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Assembling stiffness matrices represents a significant cost in many finite element computations. We address the question of optimizing the evaluation of these matrices. By finding redundant computations, we are able to significantly reduce…

Numerical Analysis · Mathematics 2012-05-15 Robert C. Kirby , Matthew Knepley , Anders Logg , L. Ridgway Scott

Partial differential equation (PDE) solvers are extensively utilized across numerous scientific and engineering fields. However, achieving high performance and scalability often necessitates intricate and low-level programming, particularly…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-12 Huanqi Cao , Shizhi Tang , Qianchao Zhu , Bowen Yu , Wenguang Chen

We explore the connection between fractional order partial differential equations in two or more spatial dimensions with boundary integral operators to develop techniques that enable one to efficiently tackle the integral fractional…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa

In this paper, we propose a low rank approximation method for efficiently solving stochastic partial differential equations. Specifically, our method utilizes a novel low rank approximation of the stiffness matrices, which can significantly…

Numerical Analysis · Mathematics 2023-10-20 Yujun Zhu , Ju Ming , Jie Zhu , Zhongming Wang

Efficient and suitably preconditioned iterative solvers for elliptic partial differential equations (PDEs) of the convection-diffusion type are used in all fields of science and engineering. To achieve optimal performance, solvers have to…

Numerical Analysis · Mathematics 2019-07-24 Peter Bastian , Eike Hermann Müller , Steffen Müthing , Marian Piatkowski

Finite-difference methods based on high-order stencils are widely used in seismic simulations, weather forecasting, computational fluid dynamics, and other scientific applications. Achieving HPC-level stencil computations on one…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-09 Ryuichi Sai , John Mellor-Crummey , Jinfan Xu , Mauricio Araya-Polo

A general method for accelerating fixed point schemes for problems related to partial differential equations is presented in this article. The speedup is obtained by training a reduced-order model on-the-fly, removing the need to do an…

Numerical Analysis · Mathematics 2025-12-01 Philippe-André Luneau , Jean Deteix

In this paper, we address a way to reduce the total computational cost of meshless approximation by reducing the required stencil size through spatially varying computational node regularity. Rather than covering the entire domain with…

Numerical Analysis · Mathematics 2025-02-19 Miha Rot , Mitja Jančič , Gregor Kosec

We consider the reliable implementation of high-order unfitted finite element methods on Cartesian meshes with hanging nodes for elliptic interface problems. We construct a reliable algorithm to merge small interface elements with their…

Numerical Analysis · Mathematics 2023-08-16 Zhiming Chen , Yong Liu

This work presents a novel methodology for speeding up the assembly of stiffness matrices for laminate composite 3D structures in the context of isogeometric and finite element discretizations. By splitting the involved terms into their…

Numerical Analysis · Mathematics 2019-05-15 Pablo Antolin

In the present work, we investigate the computational efficiency afforded by higher-order finite-element discretization of the saddle-point formulation of orbital-free density functional theory. We first investigate the robustness of viable…

Computational Physics · Physics 2015-05-30 Phani Motamarri , Mrinal Iyer , Jaroslaw Knap , Vikram Gavini

The paper looks at a scaled variant of the stochastic gradient descent algorithm for the matrix completion problem. Specifically, we propose a novel matrix-scaling of the partial derivatives that acts as an efficient preconditioning for the…

Machine Learning · Computer Science 2016-10-06 Bamdev Mishra , Rodolphe Sepulchre

Modern general-purpose accelerators integrate a large number of programmable area- and energy-efficient processing elements (PEs), to deliver high performance while meeting stringent power delivery and thermal dissipation constraints. In…

Hardware Architecture · Computer Science 2025-11-11 Luca Colagrande , Jayanth Jonnalagadda , Luca Benini

In the fields of control theory and machine learning, the dynamic low-rank approximation for large-scale matrices has received substantial attention. Considering large-scale semilinear stiff matrix differential equations, we propose…

Numerical Analysis · Mathematics 2025-10-14 Zi Wu , Yong-Liang Zhao , Xian-Ming Gu

Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a…

Computational Physics · Physics 2018-08-16 Konduri Aditya , Diego A. Donzis

This work presents a matrix-free finite element solver for finite-strain elasticity adopting an $hp$-multigrid preconditioner. Compared to classical algorithms relying on a global sparse matrix, matrix-free solution strategies significantly…

Computational Engineering, Finance, and Science · Computer Science 2024-12-09 Richard Schussnig , Niklas Fehn , Peter Munch , Martin Kronbichler

We consider high-order splitting schemes for large-scale differential Riccati equations. Such equations arise in many different areas and are especially important within the field of optimal control. In the large-scale case, it is critical…

Optimization and Control · Mathematics 2018-08-14 Tony Stillfjord

This paper presents a matrix-free approach for implementing the shifted boundary method (SBM) in finite element analysis. The SBM is a versatile technique for solving partial differential equations on complex geometries by shifting boundary…

Numerical Analysis · Mathematics 2025-07-24 Michał Wichrowski

In this article, we introduce a fast and memory efficient solver for sparse matrices arising from the finite element discretization of elliptic partial differential equations (PDEs). We use a fast direct (but approximate) multifrontal…

Numerical Analysis · Computer Science 2015-04-23 AmirHossein Aminfar , Eric Darve

Achieving a substantial part of peak performance on todays and future high-performance computing systems is a major challenge for simulation codes. In this paper we address this question in the context of the numerical solution of partial…

Numerical Analysis · Mathematics 2017-11-30 Steffen Müthing , Marian Piatkowski , Peter Bastian