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This paper addresses the challenges of designing mesh convolution neural networks for 3D mesh dense prediction. While deep learning has achieved remarkable success in image dense prediction tasks, directly applying or extending these…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Shi Hezi , Jiang Luo , Zheng Jianmin , Zeng Jun

We propose a method that morphs high-orger meshes such that their boundaries and interfaces coincide/align with implicitly defined geometries. Our focus is particularly on the case when the target surface is prescribed as the zero…

Computational Geometry · Computer Science 2023-02-17 Jorge-Luis Barrera , Tzanio Kolev , Ketan Mittal , Vladimir Tomov

Hero-class HPC simulations rely on Adaptive Mesh Refinement (AMR) to reduce compute and memory demands while maintaining accuracy. This work analyzes the performance of Parthenon, a block-structured AMR benchmark, on CPU-GPU systems. We…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-25 Akash Poptani , Alireza Khadem , Scott Mahlke , Jonah Miller , Joshua Dolence , Reetuparna Das

Adaptive mesh refinement (AMR) offers a practical solution to reduce the computational cost and memory requirement of numerical simulations that use computational meshes. In this work, we introduce a novel smart methodology for adaptive…

Fluid Dynamics · Physics 2021-08-23 Akash A. Patel , Masoud Safdari

In recent work we have shown how an accurate reduced model can be utilized to perform mesh refinement in random space. That work relied on the explicit knowledge of an accurate reduced model which is used to monitor the transfer of activity…

Numerical Analysis · Mathematics 2016-09-21 Jing Li , Panos Stinis

Simplifying complex 3D meshes is a crucial step in robotics applications to enable efficient motion planning and physics simulation. Common methods, such as approximate convex decomposition, represent a mesh as a collection of simple parts,…

Robotics · Computer Science 2025-09-30 Brandon Vu , Shameek Ganguly , Pushkar Joshi

High-order solvers for compressible flows are vital in scientific applications. Adaptive mesh refinement (AMR) is a key technique for reducing computational cost by concentrating resolution in regions of interest. In this work, we develop…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-08 Anjiang Wei , Hang Song , Mert Hidayetoglu , Elliott Slaughter , Sanjiva K. Lele , Alex Aiken

Recovered finite element methods (R-FEM) have been recently introduced for meshes consisting of simplicial and/or box-type meshes. Here, utilising the flexibility of R-FEM framework, we extend their definition on polygonal and polyhedral…

Numerical Analysis · Mathematics 2018-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Tristan Pryer

Localized features such as singularities, sharp gradients, discontinuities, and moving sources require adaptive finite element discretizations. Conventional refinement strategies introduce significant computational overhead through…

Computational Engineering, Finance, and Science · Computer Science 2026-04-29 Jan Niklas Schmäke , Martin Ruess

Adaptive representations are increasingly indispensable for reducing the in-memory and on-disk footprints of large-scale data. Usual solutions are designed broadly along two themes: reducing data precision, e.g., through compression, or…

Graphics · Computer Science 2022-07-15 Harsh Bhatia , Duong Hoang , Nate Morrical , Valerio Pascucci , Peer-Timo Bremer , Peter Lindstrom

Computational Fluid Dynamics (CFD) is widely used in different engineering fields, but accurate simulations are dependent upon proper meshing of the simulation domain. While highly refined meshes may ensure precision, they come with high…

Graphics · Computer Science 2023-08-16 Amin Heyrani Nobari , Justin Rey , Suhas Kodali , Matthew Jones , Faez Ahmed

Hexahedral meshes are an ubiquitous domain for the numerical resolution of partial differential equations. Computing a pure hexahedral mesh from an adaptively refined grid is a prominent approach to automatic hexmeshing, and requires the…

Graphics · Computer Science 2022-09-07 Marco Livesu , Luca Pitzalis , Gianmarco Cherchi

A variational framework, initially developed for high-order mesh optimisation, is being extended for r-adaptation. The method is based on the minimisation of a functional of the mesh deformation. To achieve adaptation, elements of the…

Computational Geometry · Computer Science 2019-01-07 Julian Marcon , Michael Turner , David Moxey , Spencer J. Sherwin , Joaquim Peiró

The typical goal of surface remeshing consists in finding a mesh that is (1) geometrically faithful to the original geometry, (2) as coarse as possible to obtain a low-complexity representation and (3) free of bad elements that would hamper…

Graphics · Computer Science 2016-11-08 Kaimo Hu , Dong-Ming Yan , David Bommes , Pierre Alliez , Bedrich Benes

This work is related to PHG (Parallel Hierarchical Grid). PHG is a toolbox for developing parallel adaptive finite element programs, which is under active development at the State Key Laboratory of Scientific and Engineering Computing. The…

Computational Engineering, Finance, and Science · Computer Science 2016-11-28 Hui Liu

This work introduces an adaptive mesh refinement technique for hierarchical hybrid grids with the goal to reach scalability and maintain excellent performance on massively parallel computer systems. On the block structured hierarchical…

Numerical Analysis · Mathematics 2025-08-11 Benjamin Mann , Ulrich Rüde

Adaptive mesh refinement (AMR) is a classical technique about local refinement in space where needed, thus effectively reducing computational costs for HPC-based physics simulations. Although AMR has been used for many years, little…

Fluid Dynamics · Physics 2024-05-14 Dewen Liu , Shuai He , Haoran Cheng , Yadong Zeng

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

The functional renormalisation group (fRG) has evolved into a versatile tool in condensed matter theory for studying important aspects of correlated electron systems. Practical applications of the method often involve a high numerical…

Computational Physics · Physics 2016-09-21 Daniel Rohe

The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation methods, such as LoRA, have gained significant attention due to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-14 Sanghyeon Kim , Hyunmo Yang , Younghyun Kim , Youngjoon Hong , Eunbyung Park