high performance computing on graphics processing units: hgpu.org

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High-quality pre-integrated volume rendering using hardware-accelerated pixel shading

Klaus Engel, Martin Kraus, Thomas Ertl

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Tags: 3D Graphics and Realism, Computer science, Image generation, nVidia, nVidia GeForce 3, OpenGL, Rendering, Shaders, Visualization

November 24, 2010 by hgpu

Fast matrix multiplies using graphics hardware

E. Scott Larsen, David Mcallister

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Tags: Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 3, OpenGL

November 24, 2010 by hgpu

A practical and robust bump-mapping technique for today’s GPU’s

M. Kilgard

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Tags: Algorithms, Computer science, nVidia, OpenGL, Shaders, Visualization

November 24, 2010 by hgpu

Comparing GPU-based multi-volume ray casting techniques

Nicole Schubert, Ingrid Scholl

Tags: Computer science, CUDA, nVidia, Rendering, Visualization

November 24, 2010 by hgpu

Performance modeling and automatic ghost zone optimization for iterative stencil loops on GPUs

Jiayuan Meng, Kevin Skadron

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Programming techniques

November 23, 2010 by hgpu

Many-core algorithms for statistical phylogenetics

Marc A. Suchard, Andrew Rambaut

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280

November 23, 2010 by hgpu

Synergistic execution of stream programs on multicores with accelerators

Abhishek Udupa, R. Govindarajan, Matthew J. Thazhuthaveetil

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTS, Package

November 23, 2010 by hgpu

Graphical Asian Options

Mark Joshi

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Tags: Asia options, CUDA, Finance, Monte Carlo simulation, nVidia, nVidia Quadro FX 4600

November 23, 2010 by hgpu

Challenges and opportunities of obtaining performance from multi-core CPUs and many-core GPUs

T. P. Chen, Yen-Kuang Chen

Tags: Image processing, nVidia

November 23, 2010 by hgpu

Implementation of a Lattice Boltzmann kernel using the Compute Unified Device Architecture developed by nVIDIA

Jonas Tolke

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Tags: Computer science, CUDA, Lattice Boltzmann model, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 Ultra

November 23, 2010 by hgpu

Efficient Probabilistic Model Checking on General Purpose Graphics Processors

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Probabilistic model checking

November 23, 2010 by hgpu

Parallel computation of mutual information on the GPU with application to real-time registration of 3D medical images

Ramtin Shams, Parastoo Sadeghi, Rodney Kennedy, Richard Hartley

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Tags: CUDA, Image processing, Image registration, Medicine, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280

November 23, 2010 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

High-quality pre-integrated volume rendering using hardware-accelerated pixel shading

Fast matrix multiplies using graphics hardware

A practical and robust bump-mapping technique for today’s GPU’s

Comparing GPU-based multi-volume ray casting techniques

Performance modeling and automatic ghost zone optimization for iterative stencil loops on GPUs

Many-core algorithms for statistical phylogenetics

Synergistic execution of stream programs on multicores with accelerators

Graphical Asian Options

Challenges and opportunities of obtaining performance from multi-core CPUs and many-core GPUs

Implementation of a Lattice Boltzmann kernel using the Compute Unified Device Architecture developed by nVIDIA

Efficient Probabilistic Model Checking on General Purpose Graphics Processors

Parallel computation of mutual information on the GPU with application to real-time registration of 3D medical images

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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