high performance computing on graphics processing units: hgpu.org

hgpu.org » Applications

GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision

Yannick Allusse, Patrick Horain, Ankit Agarwal, Cindula Saipriyadarshan

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Tags: Computer science, Computer vision, CUDA, GLSL, Image processing, nVidia, nVidia GeForce GTX 280, OpenGL, Package

October 28, 2010 by hgpu

A hybrid condensed finite element model with GPU acceleration for interactive 3D soft tissue cutting

Wen Wu, Pheng A. Heng

Tags: Computer science, Finite element method, Medicine, Surgical simulation

October 28, 2010 by hgpu

A Generic and Scalable Pipeline for GPU Tetrahedral Grid Rendering

J. Georgii, R. Westermann

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 7900 GTX, Rendering

October 28, 2010 by hgpu

Radial Basis Function Networks GPU-Based Implementation

A. Brandstetter, A. Artusi

Tags: Computer science, Neural networks

October 28, 2010 by hgpu

GIST: an interactive, GPU-based level set segmentation tool for 3D medical images

Joshua E. Cates, Aaron E. Lefohn, Ross T. Whitaker

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Tags: ATI, ATI Radeon 9700 Pro, Computer science, Image processing, Medicine

October 28, 2010 by hgpu

Adapting a message-driven parallel application to GPU-accelerated clusters

James C. Phillips, John E. Stone, Klaus Schulten

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Tags: Computer science, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia Quadro FX 5600

October 28, 2010 by hgpu

Advanced illumination techniques for GPU volume raycasting

Markus Hadwiger, Patric Ljung, Christof R. Salama, Timo Ropinski

Tags: 3D Graphics and Realism, Computer science, Numerical simulation, Raytracing, Rendering

October 28, 2010 by hgpu

GPU-Based Monte-Carlo Volume Raycasting

C. R. Salama

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 8800 GTX, OpenGL, Raytracing, Rendering

October 28, 2010 by hgpu

Parallel Algorithm for GPU Processing; for use in High Speed Machine Vision Sensing of Cotton Lint Trash

Mathew Pelletier

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Tags: Computer science, Computer vision, Cotton, Image processing, nVidia, nVidia GeForce 8800 Ultra, Sensing

October 28, 2010 by hgpu

GPU support for batch oriented workloads

Lauro B. Costa, Samer Al-Kiswany, Matei Ripeanu

Tags: Bloom filter, Computer science

October 28, 2010 by hgpu

The gputools package enables GPU computing in R

Joshua Buckner, Justin Wilson, Mark Seligman, Brian Athey, Stanley Watson, Fan Meng

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Tags: Computer science, CUBLAS, CUDA, nVidia, Package

October 28, 2010 by hgpu

Accelerating Large Graph Algorithms on the GPU Using CUDA

Pawan Harish, P. Narayanan

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

Applications

GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision

A hybrid condensed finite element model with GPU acceleration for interactive 3D soft tissue cutting

A Generic and Scalable Pipeline for GPU Tetrahedral Grid Rendering

Radial Basis Function Networks GPU-Based Implementation

GIST: an interactive, GPU-based level set segmentation tool for 3D medical images

Adapting a message-driven parallel application to GPU-accelerated clusters

Advanced illumination techniques for GPU volume raycasting

GPU-Based Monte-Carlo Volume Raycasting

Parallel Algorithm for GPU Processing; for use in High Speed Machine Vision Sensing of Cotton Lint Trash

GPU support for batch oriented workloads

The gputools package enables GPU computing in R

Accelerating Large Graph Algorithms on the GPU Using CUDA

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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