high performance computing on graphics processing units: hgpu.org

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Towards multi-GPU support for visualization

John D. Owens

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Tags: Computer science, CUDA, nVidia, Visualization

December 6, 2010 by hgpu

A Duality Based Approach for Realtime TV-L1 Optical Flow

C. Zach, T. Pock, H. Bischof

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Tags: Cg, Image processing, nVidia, nVidia GeForce 7800 GTS, nVidia GeForce 7900 GTX, OpenGL, Optical flow

December 6, 2010 by hgpu

Real Time Capture of Audio Images and their Use with Video

Adam O'Donovan, Ramani Duraiswami, Nail A. Gumerov

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Tags: CUDA, nVidia, nVidia GeForce 8800 GTX, Signal processing

December 6, 2010 by hgpu

Using Graphics Hardware for Enhancing Edge and Circle Detection

Antonio Ruiz, Manuel Ujaldon, Nicolas Guil

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Tags: Cg, Computer vision, Image processing, nVidia, nVidia GeForce 7950 GX2, OpenGL

December 5, 2010 by hgpu

Optical Flow Computation on Compute Unified Device Architecture

Yoshiki Mizukami, Katsumi Tadamura

Tags: CUDA, Image processing, nVidia

December 5, 2010 by hgpu

GPU architecture overview

John Owens

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Tags: Computer science, Hardware, Presentation, Review

December 5, 2010 by hgpu

Visibility Sampling on GPU and Applications

Eisemann, Elmar, Decoret, Xavier

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Tags: Algorithms, Computer science, Visualization

December 5, 2010 by hgpu

Simulation and interaction of fluid dynamics

Enhua Wu, Hongbin Zhu, Xuehui Liu, Youquan Liu

Tags: Fluid dynamics, Navier-Stokes equations, NSEs

December 5, 2010 by hgpu

GPU physics

Mark Harris

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Tags: Computer science, CUDA, nVidia, OpenGL, Presentation, Review

December 5, 2010 by hgpu

Algorithmic Differentiation: Application to Variational Problems in Computer Vision

Thomas Pock, Michael Pock, Horst Bischof

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Tags: Algorithms, Computer vision, Image processing

December 5, 2010 by hgpu

Fast continuous collision detection among deformable models using graphics processors

Naga K. Govindaraju, Ilknur Kabul, Ming C. Lin, Dinesh Manocha

Tags: Collision detection, Computer science, nVidia, nVidia GeForce 7800

December 5, 2010 by hgpu

Cache-efficient numerical algorithms using graphics hardware

Naga K. Govindaraju, Dinesh Manocha

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Tags: Computer science, Memory model, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7900 GTX, nVidia GeForce 8800 GTX, OpenGL

December 5, 2010 by hgpu

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

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high performance computing on graphics processing units: hgpu.org

Applications

Towards multi-GPU support for visualization

A Duality Based Approach for Realtime TV-L1 Optical Flow

Real Time Capture of Audio Images and their Use with Video

Using Graphics Hardware for Enhancing Edge and Circle Detection

Optical Flow Computation on Compute Unified Device Architecture

GPU architecture overview

Visibility Sampling on GPU and Applications

Simulation and interaction of fluid dynamics

GPU physics

Algorithmic Differentiation: Application to Variational Problems in Computer Vision

Fast continuous collision detection among deformable models using graphics processors

Cache-efficient numerical algorithms using graphics hardware

Recent source codes

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

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