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We present a new adaptive parallel algorithm for the challenging problem of multi-dimensional numerical integration on massively parallel architectures. Adaptive algorithms have demonstrated the best performance, but efficient many-core…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-24 Ioannis Sakiotis , Kamesh Arumugam , Marc Paterno , Desh Ranjan , Balša Terzić , Mohammad Zubair

This paper presents a Graphics Processing Units (GPUs) acceleration method of an iterative scheme for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work features a fast converging…

Computational Physics · Physics 2020-01-08 Lianhua Zhu , Peng Wang , Songze Chen , Zhaoli Guo , Yonghao Zhang

Distributed computing has been widely applied in distributed edge networks for reducing the processing burden of high-dimensional data centralization, where a high-dimensional computational task is decomposed into multiple low-dimensional…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-22 Mengchun Xia , Zhicheng Dong , Donghong Cai , Fang Fang , Lisheng Fan , Pingzhi Fan

This paper presents a new method, Diffusing Winding Gradients (DWG), for reconstructing watertight 3D surfaces from unoriented point clouds. Our method exploits the alignment between the gradients of the generalized winding number (GWN)…

Graphics · Computer Science 2024-10-10 Weizhou Liu , Jiaze Li , Xuhui Chen , Fei Hou , Shiqing Xin , Xingce Wang , Zhongke Wu , Chen Qian , Ying He

Recent work [4] analyses the local convergence of Adam in a neighbourhood of an optimal solution for a twice-differentiable function. It is found that the learning rate has to be sufficiently small to ensure local stability of the optimal…

Machine Learning · Computer Science 2021-12-14 Guoqiang Zhang , Niwa Kenta , W. Bastiaan Kleijn

In additive manufacturing (AM), particularly for laser-based metal AM, process optimization is crucial to the quality of products and the efficiency of production. The identification of optimal process parameters out of a vast parameter…

Materials Science · Physics 2024-07-25 Xiao Shang , Evelyn Li , Ajay Talbot , Haitao Wen , Tianyi Lyu , Jiahui Zhang , Yu Zou

We demonstrate a high-performance vendor-agnostic method for massively parallel solving of ensembles of ordinary differential equations (ODEs) and stochastic differential equations (SDEs) on GPUs. The method is integrated with a widely used…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-20 Utkarsh Utkarsh , Valentin Churavy , Yingbo Ma , Tim Besard , Prakitr Srisuma , Tim Gymnich , Adam R. Gerlach , Alan Edelman , George Barbastathis , Richard D. Braatz , Christopher Rackauckas

As local AI grows in popularity, there is a critical gap between the benchmark performance of object detectors and their practical viability on consumer-grade hardware. While models like YOLOv10s promise real-time speeds, these metrics are…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Mahmudul Islam Masum , Miad Islam

The Random Phase Approximation (RPA) for correlation energy in the grid-based projector augmented wave (gpaw) code is accelerated by porting to the Graphics Processing Unit (GPU) architecture. The acceleration is achieved by grouping…

Computational Physics · Physics 2013-07-31 Jun Yan , Lin Li , Christopher O'Grady

Subsequence Dynamic Time Warping (sDTW) is the metric of choice when performing many sequence matching and alignment tasks. While sDTW is flexible and accurate, it is neither simple nor fast to compute; significant research effort has been…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-12 Daniel Latta-Lin , Sofia Isadora Padilla Munoz

The emergence of artificial intelligence (AI) accelerators like NVIDIA Tensor Cores offers new opportunities to speed up tensor-heavy scientific computations. However, applying them to quantum chemistry is challenging due to strict accuracy…

Chemical Physics · Physics 2026-04-20 Hua Huang , Wenkai Shao , Jeff Hammond

In modern supervised learning, many deep neural networks are able to interpolate the data: the empirical loss can be driven to near zero on all samples simultaneously. In this work, we explicitly exploit this interpolation property for the…

Machine Learning · Computer Science 2020-08-04 Leonard Berrada , Andrew Zisserman , M. Pawan Kumar

Adapting a pre-trained foundation model on downstream tasks should ensure robustness against distribution shifts without the need to retrain the whole model. Although existing weight interpolation methods are simple yet effective, we argue…

Machine Learning · Computer Science 2025-06-02 Changdae Oh , Yixuan Li , Kyungwoo Song , Sangdoo Yun , Dongyoon Han

One of the primary goals of coastal water quality monitoring is to characterize spatial variation. Generally, this monitoring takes place at a limited number of fixed sampling points. The alternative sampling methodology explored in this…

Applications · Statistics 2015-04-07 Joseph Stachelek , Christopher J. Madden

Adaptive finite elements combined with geometric multigrid solvers are one of the most efficient numerical methods for problems such as the instationary Navier-Stokes equations. Yet despite their efficiency, computations remain expensive…

Numerical Analysis · Mathematics 2025-12-23 Manuel Liebchen , Robert Jendersie , Utku Kaya , Christian Lessig , Thomas Richter

We discuss an implementation of adaptive fast multipole methods targeting hybrid multicore CPU- and GPU-systems. From previous experiences with the computational profile of our version of the fast multipole algorithm, suitable parts are…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-09-03 Marcus Holm , Stefan Engblom , Anders Goude , Sverker Holmgren

The quality of datasets is a critical issue in big data mining. More interesting things could be mined from datasets with higher quality. The existence of missing values in geographical data would worsen the quality of big datasets. To…

Numerical Analysis · Mathematics 2020-02-21 Kaifeng Gao , Gang Mei , Salvatore Cuomo , Francesco Piccialli , Nengxiong Xu

Interpolation methodologies have been widely used within the domain of indoor positioning systems. However, existing indoor positioning interpolation algorithms exhibit several inherent limitations, including reliance on complex…

Machine Learning · Computer Science 2023-11-28 Suorong Yang , Geng Zhang , Jian Zhao , Furao Shen

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task -- especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm…

Chemical Physics · Physics 2016-08-24 Markus Kowalewski , Elisabeth Larsson , Alfa Heryudono

This paper presents a GPU-accelerated implementation of two-dimensional Smart Laplacian smoothing. This implementation is developed under the guideline of our paradigm for accelerating Laplacianbased mesh smoothing [13]. Two types of…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-25 Kunyang Zhao , Gang Mei , Nengxiong Xu , Jiayin Zhang