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hgpu.org » Programming » CUDA

Real-Time Image Segmentation on a GPU

Alexey Abramov, Tomas Kulvicius, F. Worgotter, B. Dellen

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 295, Real-time graphics

March 13, 2011 by hgpu

A Quantitative Performance Analysis Model for GPU Architectures

Yao Zhang, John D. Owens

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Tags: Computer science, CUDA, Hardware Architecture, Linear Algebra, nVidia, nVidia GeForce GTX 285, Optimization

March 13, 2011 by hgpu

GPU Octrees and Optimized Search

Daniel Madeira, Anselmo Montenegro, Esteban Clua, Thomas Lewiner

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce 9600 M GT, Search

March 12, 2011 by hgpu

Acceleration of a CFD Code with a GPU

Dennis C. Jespersen

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, nVidia GeForce 8800 GTX

March 12, 2011 by hgpu

Empowering Visual Categorization With the GPU

Koen E. A. Van De Sande, Theo Gevers, Cees G. M. Snoek

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Tags: CUDA, Image processing, Information Retrieval, nVidia, nVidia GeForce GTX 260

March 12, 2011 by hgpu

GPU Computing with Orientation Maps for Extracting Local Invariant Features

Naoyuki Ichimura

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Tags: Computer science, Computer vision, CUDA, Image recognition, nVidia, nVidia GeForce GTX 280, nVidia Quadro FX 4600

March 12, 2011 by hgpu

GEMM on a GPU

Jonathan Monette

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Poster

March 12, 2011 by hgpu

To GPU Synchronize or Not GPU Synchronize?

Wu-Chun Feng, Shucai Xiao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Programming techniques, Synchronization

March 12, 2011 by hgpu

Stereo depth with a Unified Architecture GPU

Joel Gibson, Oge Marques

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Tags: Computer science, Computer vision, CUDA, Image recognition, nVidia

March 11, 2011 by hgpu

GPU-Accelerated Text Mining

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Text mining

March 11, 2011 by hgpu

Interactive SPH Simulation and Rendering on the GPU

Prashant Goswami, Philipp Schlegel, Barbara Solenthaler, Renato Pajarola

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Rendering

March 11, 2011 by hgpu

Multi Agent Navigation on the GPU

Avi Bleiweiss

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Tags: Artificial intelligence, Computer science, CUDA, Games, Hashing, nVidia, nVidia GeForce GTX 280, Search strategies

March 11, 2011 by hgpu

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Real-Time Image Segmentation on a GPU

A Quantitative Performance Analysis Model for GPU Architectures

GPU Octrees and Optimized Search

Acceleration of a CFD Code with a GPU

Empowering Visual Categorization With the GPU

GPU Computing with Orientation Maps for Extracting Local Invariant Features

GEMM on a GPU

To GPU Synchronize or Not GPU Synchronize?

Stereo depth with a Unified Architecture GPU

GPU-Accelerated Text Mining

Interactive SPH Simulation and Rendering on the GPU

Multi Agent Navigation on the GPU

Recent source codes

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

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