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The multi-level hp-refinement scheme is a powerful extension of the finite element method that allows local mesh adaptation without the trouble of constraining hanging nodes. This is achieved through hierarchical high-order overlay meshes,…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-05 John N. Jomo , Nils Zander , Mohamed Elhaddad , Ali Özcan , Stefan Kollmannsberger , Ralf-Peter Mundani , Ernst Rank

We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods. The proposed kernel is defined based on a hierarchical partitioning of the underlying data domain, where…

Machine Learning · Computer Science 2017-08-15 Jie Chen , Haim Avron , Vikas Sindhwani

We present an efficient integral equation approach to solve the heat equation, $u_t (\x) - \Delta u(\x) = F(\x,t)$, in a two-dimensional, multiply connected domain, and with Dirichlet boundary conditions. Instead of using integral equations…

Numerical Analysis · Mathematics 2010-08-02 Mary-Catherine Kropinski , Bryan Quaife

In this paper, we present a new multibody physics simulation framework that utilizes the subsystem-based structure and the Alternating Direction Method of Multiplier (ADMM). The major challenge in simulating complex high degree of freedom…

Robotics · Computer Science 2023-03-01 Jeongmin Lee , Minji Lee , Dongjun Lee

The three most common methods, Ewald, fast multipole (FMM) and the particle-particle particle-mesh (PPPM), used to compute the interactions in many body Coulombic systems are compared for single and multi-processor machines. The Ewald…

Condensed Matter · Physics 2009-10-28 E. L. Pollock , Jim Glosli

We have implemented a parallel version of the Barnes-Hut 3-D N-body tree algorithm under PVM 3.2.5, adopting an SPMD paradigm. We parallelize the problem by decomposing the physical domain by means of the {\bf Orthogonal Recursive…

Astrophysics · Physics 2007-05-23 V. Antonuccio-Delogu , U. Becciani

The fast marching method is well-known for its worst-case optimal computational complexity in solving the Eikonal equation, and has been employed in numerous scientific and engineering fields. However, it has barely benefited from…

Computational Physics · Physics 2018-11-02 Jianming Yang

Multiple comparisons in hypothesis testing often encounter structural constraints in various applications. For instance, in structural Magnetic Resonance Imaging for Alzheimer's Disease, the focus extends beyond examining atrophic brain…

Methodology · Statistics 2023-11-08 Yang Cao , Xinwei Sun , Yuan Yao

Kernel methods are a highly effective and widely used collection of modern machine learning algorithms. A fundamental limitation of virtually all such methods are computations involving the kernel matrix that naively scale quadratically…

Machine Learning · Computer Science 2021-06-09 John Paul Ryan , Sebastian Ament , Carla P. Gomes , Anil Damle

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

The binary-forking model is a parallel computation model, formally defined by Blelloch et al. very recently, in which a thread can fork a concurrent child thread, recursively and asynchronously. The model incurs a cost of $\Theta(\log n)$…

Data Structures and Algorithms · Computer Science 2020-09-04 Zafar Ahmad , Rezaul Chowdhury , Rathish Das , Pramod Ganapathi , Aaron Gregory , Mohammad Mahdi Javanmard

Non-negative Matrix Factorization (NMF) is a key kernel for unsupervised dimension reduction used in a wide range of applications, including topic modeling, recommender systems and bioinformatics. Due to the compute-intensive nature of…

Machine Learning · Computer Science 2019-04-18 Gordon E. Moon , Aravind Sukumaran-Rajam , Srinivasan Parthasarathy , P. Sadayappan

We present an implementation of the fast multipole method for computing coulombic electrostatic and polarization forces from polarizable force-fields based on induced point dipole moments. We demonstrate the expected $O(N)$ scaling of that…

Chemical Physics · Physics 2015-06-22 Jonathan P. Coles , Michel Masella

We present a generalized, data-driven collisional operator for one-component plasmas, learned from molecular dynamics simulations, to extend the collisional kinetic model beyond the weakly coupled regime. The proposed operator features an…

Numerical Analysis · Mathematics 2025-10-20 Yue Zhao , Huan Lei

Low-rank metric learning aims to learn better discrimination of data subject to low-rank constraints. It keeps the intrinsic low-rank structure of datasets and reduces the time cost and memory usage in metric learning. However, it is still…

Machine Learning · Computer Science 2019-09-16 Han Liu , Zhizhong Han , Yu-Shen Liu , Ming Gu

We consider fast kernel summations in high dimensions: given a large set of points in $d$ dimensions (with $d \gg 3$) and a pair-potential function (the {\em kernel} function), we compute a weighted sum of all pairwise kernel interactions…

Machine Learning · Computer Science 2015-02-16 William B. March , George Biros

This article presents a fast direct solver, termed Algebraic Inverse Fast Multipole Method (from now on abbreviated as AIFMM), for linear systems arising out of $N$-body problems. AIFMM relies on the following three main ideas: (i) Certain…

Numerical Analysis · Mathematics 2023-01-31 Vaishnavi Gujjula , Sivaram Ambikasaran

The increasing complexity and scale of photonic and electromagnetic devices demand efficient and accurate numerical solvers. In this work, we develop a parallel overlapping domain decomposition method (DDM) based on the finite-difference…

Optics · Physics 2025-09-26 Zhanwen Wang , Chengnian Huang , Wangtao Lu , Yuntian Chen , Wei E. I. Sha

With endless amounts of data and very limited bandwidth, fast data compression is one solution for the growing datasharing problem. Compression helps lower transfer times and save memory, but if the compression takes too long, this no…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-21 David Noel , Elizabeth Graham , Liyuan Liu

The Material Point Method (MPM) has become a cornerstone of physics-based simulation, widely used in geomechanics and computer graphics for modeling phenomena such as granular flows, viscoelasticity, fracture mechanics, etc. Despite its…

Graphics · Computer Science 2025-05-07 Michael Liu , Xinlei Wang , Minchen Li
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