high performance computing on graphics processing units: hgpu.org

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AES Encryption Implementation and Analysis on Commodity Graphics Processing Units

Owen Harrison, John Waldron

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Tags: Computer science, nVidia, nVidia GeForce 6600 GT, nVidia GeForce 7900 GT, OpenGL, Security

December 6, 2010 by hgpu

Multi-fragment effects on the GPU using the k-buffer

Louis Bavoil, Steven P. Callahan, Aaron Lefohn, Ao, Claudio T. Silva

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Tags: Computer science, GLSL, Image generation, nVidia, nVidia GeForce 7900 GTX, OpenGL, Rendering

December 6, 2010 by hgpu

Dynamic deformation textures: GPU-accelerated simulation of deformable models in contact

Nico Galoppo, Miguel A. Otaduy, Paul Mecklenburg, Markus Gross, Ming C. Lin

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 7800

December 6, 2010 by hgpu

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 physics

Mark Harris

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

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

Voice Command Recognition with Dynamic Time Warping (DTW) using Graphics Processing Units (GPU) with Compute Unified Device Architecture (CUDA)

Gustavo Poli, Joao F. Mari, Hiroki, Alexandre L. Levada

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

December 5, 2010 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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high performance computing on graphics processing units: hgpu.org

AES Encryption Implementation and Analysis on Commodity Graphics Processing Units

Multi-fragment effects on the GPU using the k-buffer

Dynamic deformation textures: GPU-accelerated simulation of deformable models in contact

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 physics

Fast continuous collision detection among deformable models using graphics processors

Cache-efficient numerical algorithms using graphics hardware

Voice Command Recognition with Dynamic Time Warping (DTW) using Graphics Processing Units (GPU) with Compute Unified Device Architecture (CUDA)

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torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

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