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Geometric predicates are at the core of many algorithms, such as the construction of Delaunay triangulations, mesh processing and spatial relation tests. These algorithms have applications in scientific computing, geographic information…

Numerical Analysis · Mathematics 2023-08-01 Tinko Bartels , Vissarion Fisikopoulos , Martin Weiser

Fixed-point iterations are at the heart of numerical computing and are often a computational bottleneck in real-time applications that typically need a fast solution of moderate accuracy. We present neural fixed-point acceleration which…

Machine Learning · Computer Science 2021-07-26 Shobha Venkataraman , Brandon Amos

This article aims to present the $AT$ algorithm, a novel two-step iterative approach for approximating fixed points of weak contractions within complete normed linear spaces. The article demonstrates the convergence of $AT$ algorithm…

Classical Analysis and ODEs · Mathematics 2024-07-08 Akansha Tyagi , Sachin Vashistha

The widespread adoption of machine learning algorithms necessitates hardware acceleration to ensure efficient performance. This acceleration relies on custom matrix engines that operate on full or reduced-precision floating-point…

Hardware Architecture · Computer Science 2024-08-23 Kosmas Alexandridis , Christodoulos Peltekis , Dionysios Filippas , Giorgos Dimitrakopoulos

Douglas-Rachford Splitting (DRS) methods based on the proximal point algorithms for the Poisson and Gaussian log-likelihood functions are proposed for ptychography and phase retrieval. Fixed point analysis shows that the DRS iterated…

Numerical Analysis · Mathematics 2020-04-13 A. Fannjiang , Z. Zhang

In this paper, we study the operational problem of connected hydro power reservoirs which involves sequential decision-making in an uncertain and dynamic environment. The problem is traditionally formulated as a stochastic dynamic program…

Optimization and Control · Mathematics 2022-05-17 Farzaneh Pourahmadi , Trine Krogh Boomsma

We present a new optimization-based method for atomistic-to-continuum (AtC) coupling. The main idea is to cast the coupling of the atomistic and continuum models as a constrained optimization problem with virtual Dirichlet controls on the…

Numerical Analysis · Mathematics 2013-04-19 Derek Olson , Pavel Bochev , Mitchell Luskin , Alexander V. Shapeev

In this paper, three efficient ensemble algorithms are proposed for fast-solving the random fluid-fluid interaction model. Such a model can be simplified as coupling two heat equations with random diffusion coefficients and a friction…

Numerical Analysis · Mathematics 2023-01-24 Yizhong Sun , Jiangshan Wang , Haibiao Zheng

A large class of non-smooth practical optimization problems can be written as minimization of a sum of smooth and partly smooth functions. We examine such structured problems which also depend on a parameter vector and study the problem of…

Optimization and Control · Mathematics 2024-10-28 Sheheryar Mehmood , Peter Ochs

The purpose of this paper is to study the influence of relaxation and acceleration techniques on the convergence behavior of the non-overlapping Schwarz algorithm with alternating Dirichlet-Neumann transmission conditions in the context of…

Numerical Analysis · Mathematics 2026-03-19 Giulia Sambataro , Irina Tezaur

In this paper, we are interested in the acceleration of numerical simulations. We focus on a hypersonic planetary reentry problem whose simulation involves coupling fluid dynamics and chemical reactions. Simulating chemical reactions takes…

Machine Learning · Statistics 2022-10-03 Paul Novello , Gaël Poëtte , David Lugato , Simon Peluchon , Pietro Marco Congedo

In this paper, we introduce a novel parallel contact algorithm designed to run efficiently in High-Performance Computing based supercomputers. Particular emphasis is put on its computational implementation in a multiphysics finite element…

Computational Engineering, Finance, and Science · Computer Science 2022-08-02 G. Guillamet , M. Rivero , M. Zavala-Aké , M. Vázquez , G. Houzeaux , S. Oller

This paper proposes an algorithmic framework for solving parametric optimization problems which we call adjoint-based predictor-corrector sequential convex programming. After presenting the algorithm, we prove a contraction estimate that…

Optimization and Control · Mathematics 2011-09-14 Q. Tran Dinh , C. Savorgnan , M. Diehl

Although Anderson acceleration (AA) is known to speed up fixed-point iterations, it is rarely applied in constrained optimization, in particular sequential quadratic programming (SQP). We show that the local convergence behavior of a…

Optimization and Control · Mathematics 2026-04-17 Jonathan Frey , David Kiessling , Katrin Baumgärtner , Moritz Diehl

We introduce a hybrid method to couple continuous Galerkin finite element methods and high-order finite difference methods in a nonconforming multiblock fashion. The aim is to optimize computational efficiency when complex geometries are…

Numerical Analysis · Mathematics 2021-11-24 Tuan Anh Dao , Ken Mattsson , Murtazo Nazarov

The accuracy and stability of implicit CFD codes are frequently impaired by the decoupling between variables, which can ultimately lead to numerical divergence. Coupled solvers, which solve all the governing equations simultaneously, have…

Computational Physics · Physics 2019-09-24 Francisco Pimenta , Manuel A. Alves

Multi-term floating-point addition appears in vector dot-product computations, matrix multiplications, and other forms of floating-point data aggregation. A critical step in multi-term floating point addition is the alignment of fractions…

Hardware Architecture · Computer Science 2024-10-30 Kosmas Alexandridis , Giorgos Dimitrakopoulos

We develop an inertial coupling method for modeling the dynamics of point-like 'blob' particles immersed in an incompressible fluid, generalizing previous work for compressible fluids. The coupling consistently includes excess (positive or…

Soft Condensed Matter · Physics 2015-08-06 F. Balboa Usabiaga , R. Delgado-Buscalioni , B. E. Griffith , A. Donev

The feasibility pump algorithm is an efficient primal heuristic for finding feasible solutions to mixed-integer programming problems. The algorithm suffers mainly from fast convergence to local optima. In this paper, we investigate the…

Optimization and Control · Mathematics 2019-06-18 Nicolas Pradignac , Maliheh Aramon , Helmut G. Katzgraber

Recently, the authors of this paper proposed a method for the Harmonic Power-Flow (HPF) calculus in polyphase grids with widespread deployment of Converter-Interfaced Distributed Energy Resources (CIDERs). The HPF problem was formulated by…

Systems and Control · Electrical Eng. & Systems 2024-03-20 Antonio Di Pasquale , Johanna Kristin Maria Becker , Andreas Martin Kettner , Mario Paolone
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