English
Related papers

Related papers: Unified sparse framework for large-scale material …

200 papers

In this paper, we describe a new scalable and modular material point method (MPM) code developed for solving large-scale problems in continuum mechanics. The MPM is a hybrid Eulerian-Lagrangian approach, which uses both moving material…

The Material Point Method (MPM) is a hybrid Eulerian Lagrangian simulation technique for solid mechanics with significant deformation. Structured background grids are commonly employed in the standard MPM, but they may give rise to several…

Computational Engineering, Finance, and Science · Computer Science 2024-08-02 Yadi Cao , Yidong Zhao , Minchen Li , Yin Yang , Jinhyun Choo , Demetri Terzopoulos , Chenfanfu Jiang

The Material Point Method (MPM) is a hybrid Eulerian-Lagrangian approach capable of simulating large deformation problems of history-dependent materials. While the MPM can represent complex and evolving material domains by using Lagrangian…

Geophysics · Physics 2019-10-01 Ezra Y. S. Tjung , Shyamini Kularathna , Krishna Kumar , Kenichi Soga

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

The material point method (MPM), a hybrid Lagrangian-Eulerian particle method, is increasingly used to simulate large-deformation and history-dependent behavior of geomaterials. While explicit time integration dominates current MPM…

Computational Engineering, Finance, and Science · Computer Science 2025-12-30 Yidong Zhao , Xuan Li , Chenfanfu Jiang , Jinhyun Choo

The Material Point Method (MPM) is a numerical technique that combines a fixed Eulerian background grid and Lagrangian point masses to simulate materials which undergo large deformations. Within the original MPM, discontinuous gradients of…

Numerical Analysis · Mathematics 2019-07-22 Pascal de Koster , Roel Tielen , Elizaveta Wobbes , Matthias Möller

We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. Our algorithms expect the sparse input in the popular compressed-sparse-row (CSR) format and thus do not require expensive format conversion.…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-13 Carl Yang , Aydin Buluc , John D. Owens

Deep learning demonstrates effectiveness across a wide range of tasks. However, the dense and over-parameterized nature of these models results in significant resource consumption during deployment. In response to this issue, weight…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-05 Cong Ma , Du Wu , Zhelang Deng , Jiang Chen , Xiaowen Huang , Jintao Meng , Wenxi Zhu , Bingqiang Wang , Amelie Chi Zhou , Peng Chen , Minwen Deng , Yanjie Wei , Shengzhong Feng , Yi Pan

Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental computation in graph analytics, scientific simulation, and sparse deep learning workloads. However, the extreme irregularity of real-world sparse matrices prevents existing…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-11 Aiying Li , Jingwei Sun , Han Li , Wence Ji , Guangzhong Sun

Finding corresponding pixels within a pair of images is a fundamental computer vision task with various applications. Due to the specific requirements of different tasks like optical flow estimation and local feature matching, previous…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Songyan Zhang , Xinyu Sun , Hao Chen , Bo Li , Chunhua Shen

General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method (AMG), breadth first search and shortest path problem. Compared to other sparse BLAS routines,…

Mathematical Software · Computer Science 2015-09-15 Weifeng Liu , Brian Vinter

Sparse matrix-dense matrix multiplication (SpMM) is a critical kernel in scientific computing, graph analytics, and machine learning, whose performance is often constrained by memory bandwidth. In this work, we investigate the applicability…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-09 Matthew Qian , Yahia Ramadan , Suhita Anubha , Ariful Azad

Deploying large language models (LLMs) on end-user devices is gaining importance due to benefits in responsiveness, privacy, and operational cost. Yet the limited memory and compute capability of mobile and desktop GPUs make efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-07 Rongxiang Wang , Kangyuan Shu , Felix Xiaozhu Lin

This paper presents a novel stabilized mixed material point method (MPM) designed for the unified modeling of free-surface and seepage flow. The unified formulation integrates the Navier-Stokes equation with the Darcy-Brinkman-Forchheimer…

Numerical Analysis · Mathematics 2024-09-30 Bodhinanda Chandra , Ryota Hashimoto , Ken Kamrin , Kenichi Soga

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. Mixed generalized multiscale finite element method (GMsFEM)…

Numerical Analysis · Mathematics 2017-04-05 Lijian Jiang , Qiuqi Li

Mesh-free Lagrangian methods are widely used for simulating fluids, solids, and their complex interactions due to their ability to handle large deformations and topological changes. These physics simulators, however, require substantial…

Machine Learning · Computer Science 2025-02-25 Omer Rochman Sharabi , Sacha Lewin , Gilles Louppe

The Material Point Method (MPM) is widely used to analyse coupled (solid-water) problems under large deformations/displacements. However, if not addressed carefully, MPM u-p formulations for poro-mechanics can be affected by two major…

Numerical Analysis · Mathematics 2024-05-22 Giuliano Pretti , Robert E. Bird , Nathan D. Gavin , William M. Coombs , Charles E. Augarde

A semi-implicit two-phase double-point Material Point Method (MPM) formulation, based on the incremental fractional-step method to model large deformation geotechnical problems has been derived. The semi-implicit formulation has two…

Numerical Analysis · Mathematics 2025-08-22 Mian Xie , Pedro Navas , Susana Lopez-Querol

Shock-physics numerical codes are essential tools for describing the short but extreme fragmentation stage of the hypervelocity impact process on asteroids. However, accurately representing complex interior structures, surfaces, and contact…

Earth and Planetary Astrophysics · Physics 2026-04-16 Xiaoran Yan , Patrick Michel , Ruichen Ni , Yifei Jiao , Junfeng Li

The material point method (MPM) has been increasingly used for the simulation of large deformation processes in fluid-infiltrated porous materials. For undrained poromechanical problems, however, standard MPMs are numerically unstable…

Numerical Analysis · Mathematics 2020-02-27 Yidong Zhao , Jinhyun Choo
‹ Prev 1 2 3 10 Next ›