high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

GPU-Based Research of Highly Efficient Ray Tracing

He Jin, Fang Zhiyi, Ji Liang, Cai Ruicheng, Chen Lin

View

Download (PDF)

Tags: Computer science, DirectX, GLSL, HLSL, nVidia, nVidia Quadro FX 570, Raytracing, Rendering

December 31, 2011 by hgpu

Fast Computing Adaptively Sampled Distance Field on GPU

Kangxue Yin, Youquan Liu, Enhua Wu

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

View

Download (PDF)

Source codes

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

December 31, 2011 by hgpu

A GPU Accelerated Volumetric Ray Tracer for Incandescent Gas

Andrew Zonenberg, Sylvia Forrest

View

Download (PDF)

Tags: Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GTX 460 M, Rendering

December 31, 2011 by hgpu

Boosting quantum evolutions using Trotter-Suzuki algorithms on GPUs

Carlos S. Bederian, Axel D. Dente

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

View

Download (PDF)

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

December 31, 2011 by hgpu

Optimising the DBCSR GPU Implementation

Jay Chetty

View

Download (PDF)

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

December 31, 2011 by hgpu

Torch7: A Matlab-like Environment for Machine Learning

Ronan Collobert, Koray Kavukcuoglu, Clement Farabet

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 460

December 31, 2011 by hgpu

A 3D Convex Hull Algorithm for Graphics Hardware

Mingcen Gao, Thanh-Tung Cao, Tiow-Seng Tan, Zhiyong Huang

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenGL, Package, Voronoi diagram

December 31, 2011 by hgpu

Construction and Rendering of Trimmed Blending Surfaces with Sharp Features on a GPU

Dae-Hyun Ko, Jieun Lee, Seong-Jae Lim, Seung-Hyun Yoon

View

Download (PDF)

Tags: Cg, Computer science, nVidia, nVidia GeForce 6800 Ultra, 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

Applications

GPU-Based Research of Highly Efficient Ray Tracing

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

A GPU Accelerated Volumetric Ray Tracer for Incandescent Gas

Boosting quantum evolutions using Trotter-Suzuki algorithms on GPUs

Fast K-selection Algorithms for Graphics Processing Units

Hierarchical Stochastic Motion Blur Rasterization

Optimising the DBCSR GPU Implementation

Torch7: A Matlab-like Environment for Machine Learning

A 3D Convex Hull Algorithm for Graphics Hardware

Construction and Rendering of Trimmed Blending Surfaces with Sharp Features on a GPU

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

Most viewed papers (last 30 days)