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The generic matrix multiply (GEMM) function is the core element of high-performance linear algebra libraries used in many computationally-demanding digital signal processing (DSP) systems. We propose an acceleration technique for GEMM based…

Mathematical Software · Computer Science 2015-05-30 Davide Anastasia , Yiannis Andreopoulos

Elliptic interface problems whose solutions are $C^0$ continuous have been well studied over the past two decades. The well-known numerical methods include the strongly stable generalized finite element method (SGFEM) and immersed FEM…

Numerical Analysis · Mathematics 2023-02-28 Champike Attanayake , So-Hsiang Chou , Quanling Deng

In this paper, we define new unfitted finite element methods for numerically approximating the solution of surface partial differential equations using bulk finite elements. The key idea is that the $n$-dimensional hypersurface, $\Gamma…

Numerical Analysis · Mathematics 2014-03-21 Klaus Deckelnick , Charles M. Elliott , Thomas Ranner

In this paper we develop the Greedy Recombination Interpolation Method (GRIM) for finding sparse approximations of functions initially given as linear combinations of some (large) number of simpler functions. In a similar spirit to the…

Numerical Analysis · Mathematics 2024-03-11 Terry Lyons , Andrew D. McLeod

We present a multiscale simulation algorithm for amorphous materials, which we illustrate and validate in a canonical case of dense granular flow. Our algorithm is based on the recently proposed Spot Model, where particles in a dense random…

Soft Condensed Matter · Physics 2009-11-11 Chris H. Rycroft , Martin Z. Bazant , Gary S. Grest , James W. Landry

We provide a numerical platform for the analysis of particle shape and topology effect on the macroscopic behavior of granular media. We work within a Discrete Element Method (DEM) framework and apply a peridynamic model for deformable…

Soft Condensed Matter · Physics 2023-08-09 Debdeep Bhattacharya , Robert P. Lipton

We study the evolution of solidification microstructures using a phase-field model computed on an adaptive, finite element grid. We discuss the details of our algorithm and show that it greatly reduces the computational cost of solving the…

Materials Science · Physics 2009-10-31 Nikolas Provatas , Nigel Goldenfeld , Jonathan Dantzig

We present a computational framework for modeling large-scale particle-laden flows in complex domains with the goal of enabling simulations in medical-image derived patient specific geometries. The framework is based on a volume-filtered…

Fluid Dynamics · Physics 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro

The aim of this paper is to propose a novel methodology to deal with micro-structural boundary conditions for the analysis of granular materials. The response of the granular assembly is modelled through the discrete element method (DEM),…

Soft Condensed Matter · Physics 2017-02-27 J. Liu , E. Bosco , A. S. J. Suiker

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high…

Soft Condensed Matter · Physics 2022-06-29 Son Pham-Ba , Jean-François Molinari

A thin-interface phase-field model of electrochemical interfaces is developed based on Marcus kinetics for concentrated solutions, and used to simulate dendrite growth during electrodeposition of metals. The model is derived in the grand…

Materials Science · Physics 2015-07-22 Daniel A. Cogswell

The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) systems. Despite its universality, a more exact determination of…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

The study of active soft matter has developed into one of the most rapidly growing areas of physics. Field theories, which can be developed either via phenomenological considerations or by coarse-graining of a microscopic model, are a very…

Soft Condensed Matter · Physics 2022-12-02 Michael te Vrugt , Jens Bickmann , Raphael Wittkowski

In the current deep learning based recommendation system, the embedding method is generally employed to complete the conversion from the high-dimensional sparse feature vector to the low-dimensional dense feature vector. However, as the…

Information Retrieval · Computer Science 2021-08-10 Huimin Zhou , Qing Li , Yong Jiang , Rongwei Yang , Zhuyun Qi

LLM pre-training efficacy increasingly depends on data composition rather than sheer volume. Yet, optimal mixing is hindered by categorization flaws: human taxonomies suffer from ontological misalignment, and Euclidean clustering fails to…

Machine Learning · Computer Science 2026-05-27 Yue Min , Ziyun Qiao , Ruining Chen , Yujun Li

A novel multi-scale finite element formulation for contact mechanics between nominally smooth but microscopically rough surfaces is herein proposed. The approach integrates the interface finite element method (FEM) for modelling interface…

Computational Engineering, Finance, and Science · Computer Science 2025-04-03 Jacopo Bonari , Maria R. Marulli , Nora Hagmeyer , Matthias Mayr , Alexander Popp , Marco Paggi

We present a sharp-interface model of two-dimensional ramified growth during quasi-steady electrodeposition. Our model differs from previous modeling methods in that it includes the important effects of extended space-charge regions and…

Fluid Dynamics · Physics 2015-10-14 Christoffer P. Nielsen , Henrik Bruus

In most domains of network analysis researchers consider networks that arise in nature with weighted edges. Such networks are routinely dichotomized in the interest of using available methods for statistical inference with networks. The…

Methodology · Statistics 2016-11-10 James D. Wilson , Matthew J. Denny , Shankar Bhamidi , Skyler Cranmer , Bruce Desmarais

In this work, we explore the idea that effective generative models for point clouds under the autoencoding framework must acknowledge the relationship between a continuous surface, a discretized mesh, and a set of points sampled from the…

Machine Learning · Computer Science 2019-12-10 Austin Dill , Chun-Liang Li , Songwei Ge , Eunsu Kang

We adapt the Gradient Discretisation Method (GDM), originally designed for elliptic and parabolic partial differential equations, to the case of a linear scalar hyperbolic equations. This enables the simultaneous design and convergence…

Numerical Analysis · Mathematics 2019-10-28 Jérôme Droniou , Robert Eymard , T. Gallouët , R. Herbin
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