high performance computing on graphics processing units: hgpu.org

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Large-scale Virtual Acoustics Simulation at Audio Rates Using Three Dimensional Finite Difference Time Domain and Multiple GPUs

Craig J. Webb, Alan Gray

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Tags: Acoustics, Computer science, CUDA, FDTD, Finite-difference time-domain, nVidia, Rendering, Tesla C2050

March 5, 2013 by hgpu

GEARS: A General and Efficient Algorithm for Rendering Shadows

Lili Wang, Ze Wang, Yulong Shi, Voicu Popescu

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Rendering

February 28, 2013 by hgpu

Adaptive Hardware-accelerated Terrain Tessellation

Albert Cervin

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Tags: Computer science, Rendering, Tessellation, Thesis

February 23, 2013 by hgpu

Fast Sparse Level Sets on Graphics Hardware

Andrei C. Jalba, Wladimir J. van der Laan, Jos B.T.M. Roerdink

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

January 18, 2013 by hgpu

Analytic Visibility on the GPU

T. Auzinger, M. Wimmer, S. Jescke

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 680, Rendering, Triangular meshes

January 16, 2013 by hgpu

Ray Tracing in Real-Time Games

J. Bikker

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Games, Image generation, nVidia, nVidia GeForce GTX 470, Rasterization, Raytracing, Rendering, Thesis

January 15, 2013 by hgpu

Toward Practical Real-Time Photon Mapping: Efficient GPU Density Estimation

Michael Mara, David Luebke, Morgan McGuire

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 670, Rendering

January 13, 2013 by hgpu

High Performance Multi-dimensional (2D/3D) FFT-Shift Implementation on Graphics Processing Units (GPUs)

Marwan Abdellah, Salah Saleh, Ayman Eldeib, Amr Shaarawi

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Tags: CUDA, FFT, nVidia, nVidia GeForce GTX 570, Rendering, Signal processing

January 8, 2013 by hgpu

Distributed Massive Model Rendering

Revanth N R, P. J. Narayanan

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia Quadro FX 3700 M, Rendering, Tesla C2050, Tesla C2070, Tesla S1070

January 8, 2013 by hgpu

Stereoscopic Ray Tracing on Graphics Processors

Alper Das

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Raytracing, Rendering, Thesis

December 30, 2012 by hgpu

Interactive Bi-scale Editing of Highly Glossy Materials

Kei Iwasaki, Yoshinori Dobashi, Tomoyuki Nishita

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

December 20, 2012 by hgpu

Memory-Efficient Single-Pass GPU Rendering of Multi-fragment Effects

Wencheng Wang, Guofu Xie

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Tags: Computer science, nVidia, nVidia GeForce GTX 680, OpenGL, Rendering

December 18, 2012 by hgpu

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

See all packages

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high performance computing on graphics processing units: hgpu.org

Large-scale Virtual Acoustics Simulation at Audio Rates Using Three Dimensional Finite Difference Time Domain and Multiple GPUs

GEARS: A General and Efficient Algorithm for Rendering Shadows

Adaptive Hardware-accelerated Terrain Tessellation

Fast Sparse Level Sets on Graphics Hardware

Analytic Visibility on the GPU

Ray Tracing in Real-Time Games

Toward Practical Real-Time Photon Mapping: Efficient GPU Density Estimation

High Performance Multi-dimensional (2D/3D) FFT-Shift Implementation on Graphics Processing Units (GPUs)

Distributed Massive Model Rendering

Stereoscopic Ray Tracing on Graphics Processors

Interactive Bi-scale Editing of Highly Glossy Materials

Memory-Efficient Single-Pass GPU Rendering of Multi-fragment Effects

Recent source codes

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

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