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Application of Assembly of Finite Element Methods on Graphics Processors for Real-Time Elastodynamics

Cris Cecka, Adrian Lew, Eric Darve

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Tags: CUDA, Finite element method, Mathematics, nVidia, nVidia GeForce GTX 480, Partial differential equations, PDEs

March 2, 2011 by hgpu

Performance and accuracy of hardware-oriented native-, emulated- and mixed-precision solvers in FEM simulations (Part 2: Double Precision GPUs)

Dominik Goddeke and Robert Strzodka

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Tags: Computer science, Conjugate gradient solver, CUDA, Extended precision, Mixed precision, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Partial differential equations, PDEs, Sparse linear iterative solvers

March 2, 2011 by hgpu

Accelerating Double Precision FEM Simulations with GPUs

Dominik Goddeke, Robert Strzodka, Stefan Turek

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Tags: Computer science, Extended precision, Finite element method, nVidia, nVidia GeForce 6800, OpenGL, Partial differential equations, PDEs

March 2, 2011 by hgpu

Integrating GPUs as fast co-processors into the existing parallel FE package FEAST

Dominik Goddeke, Christian Becker, Stefan Turek

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Tags: Finite element method, Fluid dynamics, nVidia, nVidia Quadro FX 1400, Package, Partial differential equations, PDEs

March 2, 2011 by hgpu

Mixed-Precision GPU-Multigrid Solvers with Strong Smoothers

Dominik Goddeke, Robert Strzodka

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Tags: CUDA, Mathematics, Mixed precision, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

March 2, 2011 by hgpu

GPU Acceleration of Equations Assembly in Finite Elements Method – Preliminary Results

Jiri Filipovic, Igor Peterlik, Jan Fousek

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Tags: Computer science, CUDA, Finite element method, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

February 21, 2011 by hgpu

Numerical Simulation of the Complex Ginzburg-Landau Equation on GPUs with CUDA

K.A. Hawick and D.P. Playne

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Tags: CUDA, Finite difference, nVidia, nVidia GeForce GTX 480, Partial differential equations, PDEs, Physics, Thermodynamics, Visualization

February 14, 2011 by hgpu

Modelling, simulating and visualising the Cahn-Hilliard-Cook field equation

K.A. Hawick and D.P.Playne

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Tags: Algorithms, Alloys, Finite difference, Partial differential equations, PDEs, Physics, Thermodynamics, Visualization

February 14, 2011 by hgpu

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

K.A. Hawick and D.P. Playne

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Tags: Code generation, Compilers, Computer science, CUDA, Finite difference, nVidia, Partial differential equations, PDEs

February 14, 2011 by hgpu

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

K.A. Hawick, A. Leist, and D.P. Playne

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Tags: Cell processor, Computer science, CUDA, Data parallelism, Finite difference, nVidia, nVidia GeForce GTX 295, OpenCL, Partial differential equations, PDEs, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

K.A. Hawick and D.P. Playne

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Tags: Code generation, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs

February 13, 2011 by hgpu

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Partial differential equations, PDEs

February 13, 2011 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Application of Assembly of Finite Element Methods on Graphics Processors for Real-Time Elastodynamics

Performance and accuracy of hardware-oriented native-, emulated- and mixed-precision solvers in FEM simulations (Part 2: Double Precision GPUs)

Accelerating Double Precision FEM Simulations with GPUs

Integrating GPUs as fast co-processors into the existing parallel FE package FEAST

Mixed-Precision GPU-Multigrid Solvers with Strong Smoothers

GPU Acceleration of Equations Assembly in Finite Elements Method – Preliminary Results

Numerical Simulation of the Complex Ginzburg-Landau Equation on GPUs with CUDA

Modelling, simulating and visualising the Cahn-Hilliard-Cook field equation

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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