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Performant low-order matrix-free finite element kernels on GPU architectures

Randolph R. Settgast, Yohann Dudouit, Nicola Castelletto, William R. Tobin, Benjamin C. Corbett, Sergey Klevtsov

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Tags: AMD Radeon Instinct MI250X, ATI, FEM, Finite element method, Mathematics, Numerical Analysis, nVidia, nVidia A100, nVidia V100, Package, Sparse

August 28, 2023 by hgpu

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Chong Chen

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, Package, Sparse matrix, Tesla V100

April 17, 2022 by hgpu

Portable high-order finite element kernels I: Streaming Operations

Noel Chalmers, Tim Warburton

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Tags: AMD, AMD Radeon Instinct MI60, AMD Radeon VII, Computer science, CUDA, FEM, HIP, Mathematical Software, nVidia, nVidia GeForce GTX Titan V, OCCA, Portability, Tesla V100

October 18, 2020 by hgpu

GPU-based matrix-free finite element solver exploiting symmetry of elemental matrices

Utpal Kiran, Sachin Singh Gautam, Deepak Sharma

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, Sparse matrix, Tesla K40

June 28, 2020 by hgpu

GPU Accelerated Finite Element Assembly with Runtime Compilation

Tao Cui, Xiaohu Guo, Hui Liu

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Partial differential equations, PDEs, Symbolic Computation, Tesla K20, Tesla M2090, Tesla V100

February 15, 2018 by hgpu

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Lukas Polok

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Tags: Algorithms, Computer science, Differential equations, Factorization, FEM, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla K40, Thesis

December 19, 2017 by hgpu

Acceleration of tensor-product operations for high-order finite element methods

Kasia Swirydowicz, Noel Chalmers, Ali Karakus, Timothy Warburton

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Tags: Computer science, CUDA, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Overview, Performance, Tesla P100

November 7, 2017 by hgpu

Simulating the Cardinal Movements of Childbirth Using Finite Element Analysis on the Graphics Processing Unit

Zelimkhan Gerikhanov

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Tags: AMD Radeon HD 8970 M, ATI, Biology, Biomechanics, FEM, Finite element method, Medicine, MRI, OpenCL, Thesis

August 17, 2017 by hgpu

GPU performance analysis of a nodal discontinuous Galerkin method for acoustic and elastic models

Axel Modave, Amik St-Cyr, Tim Warburton

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Tags: BLAS, Computational Physics, CUBLAS, CUDA, FEM, Finite element method, Geoscience, Linear Algebra, nVidia, nVidia GeForce GTX 980, OCCA, Physics, Profiling, Seismic modeling, Seismology

March 1, 2016 by hgpu

High-Performance Tensor Contractions for GPUs

A. Abdelfattah, M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, Tz. Kolev, I. Masliah, S. Tomov

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Tags: Algorithms, Code generation, Computer science, CUDA, FEM, Finite element method, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Tesla K40

January 29, 2016 by hgpu

Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

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Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

Hong-yu Li, Jun Teng, Zuo-hua Li, Lu Zhang

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GT 430, nVidia GeForce GT 720 M, nVidia GeForce GTX 460

December 8, 2015 by hgpu

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

An approach to performance portability through generic programming

Redco: A Lightweight Tool to Automate Distributed Training

Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs

OpenRAND: Reproducible Random Number For Parallel Computations

OpenRAND: A Performance Portable, Reproducible Random Number Generation Library for Parallel Computations

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high performance computing on graphics processing units: hgpu.org

Performant low-order matrix-free finite element kernels on GPU architectures

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Portable high-order finite element kernels I: Streaming Operations

GPU-based matrix-free finite element solver exploiting symmetry of elemental matrices

GPU Accelerated Finite Element Assembly with Runtime Compilation

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Acceleration of tensor-product operations for high-order finite element methods

Simulating the Cardinal Movements of Childbirth Using Finite Element Analysis on the Graphics Processing Unit

GPU performance analysis of a nodal discontinuous Galerkin method for acoustic and elastic models

High-Performance Tensor Contractions for GPUs

Parallel Explicit FEM Algorithms Using GPU’s

Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

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