high performance computing on graphics processing units: hgpu.org

Programming

Two Simple Single-pass GPU methods for Multi-channel Surface Voxelization of Dynamic Scenes

Athanasios Gaitatzes, Pavlos Mavridis, Georgios Papaioannou

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Tags: Algorithms, Computer science, Fluid simulation, GLSL, Image generation, nVidia, nVidia GeForce GTX 285, OpenGL, Rendering, Voxelization

January 1, 2012 by hgpu

GPU-Based Computation of Voxelized Minkowski Sums with Applications

Wei Li

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Tags: Algorithms, CAD, Collision detection, Computer science, CUDA, nVidia, nVidia Quadro FX 6000, Voxelization

December 31, 2011 by hgpu

Performance Considerations When Using a Dedicated Ray Traversal Engine

Tomas Davidovic, Lukas Marsalek, Philipp Slusallek

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Tags: Algorithms, Computer science, nVidia, Optimization, Raytracing

December 31, 2011 by hgpu

Fast Computing Adaptively Sampled Distance Field on GPU

Kangxue Yin, Youquan Liu, Enhua Wu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Visualization

December 31, 2011 by hgpu

Efficient Triangle and Quadrilateral Clipping within Shaders

M. McGuire

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Tags: Algorithms, Computer science, GLSL, nVidia, nVidia GeForce GTX 580, OpenGL, Optimization, Package, Rasterization

December 31, 2011 by hgpu

Fast Speaker Diarization Using a Specialization Framework for Gaussian Mixture Model Training

Ekaterina Gonina

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Tags: Acoustics, Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Python, Thesis

December 31, 2011 by hgpu

Boosting quantum evolutions using Trotter-Suzuki algorithms on GPUs

Carlos S. Bederian, Axel D. Dente

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Tags: Algorithms, Computer science, CUDA, Numerical simulation, nVidia, Physics, Tesla C2070

December 31, 2011 by hgpu

Fast K-selection Algorithms for Graphics Processing Units

Tolu Alabi, Jeffrey D. Blanchard, Bradley Gordon, Russel Steinbach

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, Package, Sorting, Tesla C2070

December 31, 2011 by hgpu

Hierarchical Stochastic Motion Blur Rasterization

Jacob Munkberg, Petrik Clarberg, Jon Hasselgren, Robert Toth, Masamichi Sugihara, Tomas Akenine-Moller

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Tags: Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 290, Rasterization

December 31, 2011 by hgpu

Comparison of Fragmentation/Dispersion Models for Asteroid Nuclear Disruption Mission Design

Brian D. Kaplinger, Bong Wie

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, nVidia, Tesla C2050

December 31, 2011 by hgpu

Optimising the DBCSR GPU Implementation

Jay Chetty

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C2050, Thesis

December 31, 2011 by hgpu

Hardware-Assisted High-Efficiency Ray Casting of Unstructured Time-Varying Flows Using Temporal Coherence

Qianli Ma, Liang Zeng, Huaxun Xu, Wenke Wang, Sikun Li

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Tags: Algorithms, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTS 250, Rendering

December 31, 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

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Two Simple Single-pass GPU methods for Multi-channel Surface Voxelization of Dynamic Scenes

GPU-Based Computation of Voxelized Minkowski Sums with Applications

Performance Considerations When Using a Dedicated Ray Traversal Engine

Fast Computing Adaptively Sampled Distance Field on GPU

Efficient Triangle and Quadrilateral Clipping within Shaders

Fast Speaker Diarization Using a Specialization Framework for Gaussian Mixture Model Training

Boosting quantum evolutions using Trotter-Suzuki algorithms on GPUs

Fast K-selection Algorithms for Graphics Processing Units

Hierarchical Stochastic Motion Blur Rasterization

Comparison of Fragmentation/Dispersion Models for Asteroid Nuclear Disruption Mission Design

Optimising the DBCSR GPU Implementation

Hardware-Assisted High-Efficiency Ray Casting of Unstructured Time-Varying Flows Using Temporal Coherence

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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