high performance computing on graphics processing units: hgpu.org

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An application of graphical numerical accelerators in simulations of ion-transport through biological membranes

A. Gorecki

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Tags: Chemistry, CUDA, Differential equations, Electrochemistry, nVidia, ODEs, Ordinary differential equations, Tesla C870

March 26, 2013 by hgpu

Time-stepping methods for the simulation of the self-assembly of nano-crystals in Matlab on a GPU

M. D. Korzec, T. Ahnert

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Tags: CUDA, Differential equations, Mathematics, Numerical simulation, nVidia, nVidia GeForce GTX 260, Partial differential equations, PDEs, Spectral methods

March 20, 2013 by hgpu

Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs

Eike Mueller, Xu Guo, Robert Scheichl, Sinan Shi

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, Differential equations, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla M2090

March 2, 2013 by hgpu

Massive Parallel Implementation of ODE Solvers

Cyril Fischer

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Tags: Algorithms, CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GT 430, nVidia Quadro FX 4000, ODEs, Ordinary differential equations

February 27, 2013 by hgpu

Computation of Air-Vortices Based on GPU Technology: Optimizing and Parallelizing a Model for Wake-Vortex Prediction Using OpenCL

Erik Peldan

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Tags: Algorithms, Computer science, Differential equations, nVidia, OpenCL, Thesis

February 21, 2013 by hgpu

Fast Global Illumination for Interactive Volume Visualization

Yubo Zhang, Kwan-Liu Ma

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Tags: 3D Graphics and Realism, Computer science, CUDA, Differential equations, Diffusion equation, nVidia, nVidia GeForce GTX 460, Visualization

January 4, 2013 by hgpu

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Denis Demidov, Karsten Ahnert, Karl Rupp, Peter Gottschling

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Source codes

Tags: ATI, ATI Radeon HD 7970, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, OpenCL, Ordinary differential equations, Package, Tesla C2070

January 2, 2013 by hgpu

Single-Pass GPU-Raycasting for Structured Adaptive Mesh Refinement Data

Ralf Kaehler, Tom Abel

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Tags: Algorithms, Astrophysics, Cosmology, Differential equations, GLSL, Instrumentation and Methods for Astrophysics, KD-tree, nVidia, nVidia GeForce GTX 680, OpenGL, Rendering, Visualization

December 18, 2012 by hgpu

CUDACLAW: a Data Parallel Solution Framework for Hyperbolic PDEs

Hrag Gorune Krikor Ohannessian

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Tags: Acoustics, CUDA, Differential equations, Finite volume method, Hyperbolic PDEs, Mathematics, nVidia, nVidia GeForce GTX 460, Partial differential equations, PDEs, Tesla C2050, Wave equation

December 12, 2012 by hgpu

GPU accelerating the FEniCS Project

Fredrik Heffer Valdmanis

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Tags: Computer science, CUDA, Differential equations, Linear Algebra, nVidia, Partial differential equations, PDEs, Tesla C2070, Thesis

December 8, 2012 by hgpu

Energy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster

Dominik Goeddeke, Dimitri Komatitsch, Markus Geveler, Dirk Ribbrock, Nikola Rajovic, Nikola Puzovic, Alex Ramirez

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Tags: ARM, Differential equations, Energy-efficient computing, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, Partial differential equations, PDEs, Spectral elements

November 26, 2012 by hgpu

Accelerating the Gillespie Exact Stochastic Simulation Algorithm Using Hybrid Parallel Execution on Graphics Processing Units

Ivan Komarov, Roshan M. D'Souza

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 480, Stochastic simulation

November 15, 2012 by hgpu

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

CRIUgpu: Transparent Checkpointing of GPU-Accelerated Workloads

KernelBench: Can LLMs Write GPU Kernels?

KernelBench: Can LLMs Write Efficient GPU Kernels?

An MLIR-based toolchain for AMD AI Engine-enabled devices

Seamless acceleration of Fortran intrinsics via AMD AI engines

Forecasting time series with constraints

See all packages

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high performance computing on graphics processing units: hgpu.org

An application of graphical numerical accelerators in simulations of ion-transport through biological membranes

Time-stepping methods for the simulation of the self-assembly of nano-crystals in Matlab on a GPU

Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs

Massive Parallel Implementation of ODE Solvers

Computation of Air-Vortices Based on GPU Technology: Optimizing and Parallelizing a Model for Wake-Vortex Prediction Using OpenCL

Fast Global Illumination for Interactive Volume Visualization

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Single-Pass GPU-Raycasting for Structured Adaptive Mesh Refinement Data

CUDACLAW: a Data Parallel Solution Framework for Hyperbolic PDEs

GPU accelerating the FEniCS Project

Energy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster

Accelerating the Gillespie Exact Stochastic Simulation Algorithm Using Hybrid Parallel Execution on Graphics Processing Units

Recent source codes

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

KernelBench: Can LLMs Write GPU Kernels?

An MLIR-based toolchain for AMD AI Engine-enabled devices

Forecasting time series with constraints

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