high performance computing on graphics processing units: hgpu.org

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AnySL: efficient and portable shading for ray tracing

Ralf Karrenberg, Dmitri Rubinstein, Philipp Slusallek, Sebastian Hack

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Tags: 3D Graphics and Realism, Code generation, Compilers, Computer science, nVidia, Package, Programming Languages, PTX, Raytracing, Rendering

September 13, 2011 by hgpu

A directionally adaptive edge anti-aliasing filter

Konstantine Iourcha, Jason C. Yang, Andrew Pomianowski

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Tags: Algorithms, ATI, ATI Radeon HD 4890, Computer science, DirectX, HLSL, Image generation, Rendering

September 13, 2011 by hgpu

Parallel volume rendering implementation on graphics cards using CUDA

Jens Fangerau, Susanne Kromker

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, OpenGL, Rendering, Visualization

September 13, 2011 by hgpu

SSLPV: subsurface light propagation volumes

Jesper Borlum, Brian Bunch Christensen, Thomas Kim Kjeldsen, Peter Trier Mikkelsen, Karsten Ostergaard Noe, Jens Rimestad, Jesper Mosegaard

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Tags: 3D Graphics and Realism, Algorithms, Computer science, GLSL, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenGL, Package, Rendering

September 11, 2011 by hgpu

Texture compression of light maps using smooth profile functions

Jim Rasmusson, Jacob Strom, Per Wennersten, Michael Doggett, Tomas Akenine-Moller

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Tags: Algorithms, Compression, Computer science, nVidia, OpenCL, Rendering

September 11, 2011 by hgpu

Lattice-boltzmann water waves

Robert Geist, Christopher Corsi, Jerry Tessendorf, James Westall

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Tags: 3D Graphics and Realism, Computer science, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 480, OpenCL, Rendering

September 11, 2011 by hgpu

Beyond programmable shading (parts I and II)

Aaron Lefohn, Mike Houston, Johan Andersson, Ulf Assarsson, Cass Everitt, Kayvon Fatahalian, Tim Foley, Justin Hensley, Paul Lalonde, David Luebke

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Tags: 3D Graphics and Realism, Algorithms, Computer science, DirectX, Image processing, OpenGL, Presentation, Programming techniques, Rasterization, Raytracing, Rendering

September 9, 2011 by hgpu

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

John E. Stone, Jan Saam, David J. Hardy, Kirby L. Vandivort, Wen-mei W. Hwu, Klaus Schulten

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Tags: Algorithms, Chemistry, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, Programming techniques, Rendering, Visualization

September 7, 2011 by hgpu

Real-Time Tone Mapping for High-Resolution HDR Images

Hanli Zhao, Xiaogang Jin, Jianbing Shen

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 8800 GTS, OpenGL, Rendering

September 5, 2011 by hgpu

DUODECIM – a structure for point scan compression and rendering

Jens Kruger, Jens Schneider, Rudiger Westermann

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Tags: ATI, ATI Radeon X800, Compression, Computer science, OpenGL, Rendering

September 5, 2011 by hgpu

A practical multi-viewer tabletop autostereoscopic display

Gu Ye, Andrei State, Henry Fuchs

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Tags: Computer science, Hardware Architecture, nVidia, nVidia GeForce GTX 295, Rendering

September 4, 2011 by hgpu

Visual Human – Machine Learning

Raphael Fuchs, Jurgen Waser, Meister Eduard Groller

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Tags: Algorithms, Computer science, CUDA, Genetic programming, Machine learning, nVidia, Pattern recognition, Rendering, Visualization

September 4, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

AnySL: efficient and portable shading for ray tracing

A directionally adaptive edge anti-aliasing filter

Parallel volume rendering implementation on graphics cards using CUDA

SSLPV: subsurface light propagation volumes

Texture compression of light maps using smooth profile functions

Lattice-boltzmann water waves

Beyond programmable shading (parts I and II)

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

Real-Time Tone Mapping for High-Resolution HDR Images

DUODECIM – a structure for point scan compression and rendering

A practical multi-viewer tabletop autostereoscopic display

Visual Human – Machine Learning

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)