high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Special Relativistic Visualization by Local Ray Tracing

Thomas Muller, Sebastian Grottel, Daniel Weiskopf

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Tags: 3D Graphics and Realism, Computer science, GLSL, nVidia, nVidia GeForce GTX 280, OpenGL, Raytracing, Rendering

June 6, 2011 by hgpu

Illustrative Stream Surfaces

Silvia Born, Alexander Wiebel, Jan Friedrich, Gerik Scheuermann, Dirk Bartz

Tags: Computer science, Fluid simulation, Rendering, Visualization

June 6, 2011 by hgpu

Massively Parallel Network Coding on GPUs

Xiaowen Chu, Kaiyong Zhao, Mea Wang

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Tags: Algorithms, Computer science, CUDA, Networks, nVidia, nVidia GeForce GTX 260

June 6, 2011 by hgpu

Real-time 3D surface modeling for image based relighting

Sae-woon Ryu, Sang Hwa Lee, Jong-il Park

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Real-time graphics, Rendering

June 6, 2011 by hgpu

Leveraging Computation Sharing and Parallel Processing in Location-Based Services

Jonathan Cazalas, Kien Hua

Tags: Algorithms, Computer science, Databases

June 6, 2011 by hgpu

An adaptive octree textures painting algorithm

Gang Dang, Hang Li, Zhi-Quan Cheng, Kai Xu, Yan-Zhen Wang, Bao Li

Tags: 3D Graphics and Realism, Algorithms, Image generation, Image processing

June 6, 2011 by hgpu

Exploiting Computing Power on Graphics Processing Unit

Ziyi Liu, Wenjing Ma

Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, Performance

June 5, 2011 by hgpu

Large neighborhood local search optimization on graphics processing units

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Search

June 5, 2011 by hgpu

Employ Bump Mapping to Enrich the 3D NPR Image

Zhien Luo

Tags: 3D Graphics and Realism, Image processing, Rendering

June 5, 2011 by hgpu

How to Render FDTD Computations More Effective Using a Graphics Accelerator

P. Sypek, A. Dziekonski, M. Mrozowski

Tags: Computer science, FDTD, Finite-difference time-domain

June 5, 2011 by hgpu

Interective Point Clouds Fairing on Many-Core System

Tang Jie, Wu Gangshan, Xu Bo, Gong Zhongliang

Tags: Computer science, CUDA, Nearest neighbour, nVidia

June 5, 2011 by hgpu

I3DC: Interactive Three-Dimensional Cubes

Ke Yang, Yinan Li, Qiong Luo, P.V. Sander, Jiaoying Shi

Tags: Computer science, Rendering, Visualization

June 5, 2011 by hgpu

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

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Special Relativistic Visualization by Local Ray Tracing

Illustrative Stream Surfaces

Massively Parallel Network Coding on GPUs

Real-time 3D surface modeling for image based relighting

Leveraging Computation Sharing and Parallel Processing in Location-Based Services

An adaptive octree textures painting algorithm

Exploiting Computing Power on Graphics Processing Unit

Large neighborhood local search optimization on graphics processing units

Employ Bump Mapping to Enrich the 3D NPR Image

How to Render FDTD Computations More Effective Using a Graphics Accelerator

Interective Point Clouds Fairing on Many-Core System

I3DC: Interactive Three-Dimensional Cubes

Recent source codes

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

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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