high performance computing on graphics processing units: hgpu.org

hgpu.org » Applications » Image and Signal Processing » Image processing

Abundance Estimation Algorithms using NVIDIA CUDA Technology

David Gonzalez, Christian Sanchez, Ricardo Veguilla, Nayda G. Santiago, Samuel Rosario-Torres, Miguel Velez-Reyes

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX

January 5, 2012 by hgpu

Parallel Implementation of Compressive Sensing Based SAR Imaging with GPU

Tian Jihua, Sun Jinping, Zhang Yuxi, Najeeb Ahmad, Zhang Bingchen

View

Download (PDF)

Tags: Algorithms, Compression, CUDA, Image processing, nVidia, Sensing, Tesla C1060

January 4, 2012 by hgpu

Parallel Implementation Algorithm of Motion Estimation for GPU Applications

Tian Song, Masashi Koshino, Yuya Matsunohana, Takashi Shimamoto

View

Download (PDF)

Tags: Algorithms, CUDA, H.264/AVC, Image processing, nVidia, nVidia GeForce GTX 285

January 4, 2012 by hgpu

Parallelism, Patterns, and Performance in Iterative MRI Reconstruction

Mark Murphy

View

Download (PDF)

Source codes

Tags: Algorithms, Compression, CUDA, FFT, Image processing, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce GTX 580, Package, Thesis, Wavelet

December 29, 2011 by hgpu

Multilevel Tile Load Map on Massive Terrain Visualization

Junlan Nie, Dongliang Guo, Yanfen Wang, Lingfu Kong, Yong Tang

View

Download (PDF)

Tags: Algorithms, Computer science, GLSL, Image processing, nVidia, nVidia GeForce GT 240 M, OpenGL, Optimization, Rendering, Visualization

December 28, 2011 by hgpu

GPU-Parallel Implementation of Color based Medical Image Retrieval in Compressed Domain

Kuldeep Yadav, Avi Srivastava, M. A. Ansari

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT

December 25, 2011 by hgpu

Parallel Implementation of Shape based Image Retrieval Approach on CUDA in Compressed Domain

Kuldeep Yadav, Avi Srivastava, Ankush Mittal, M. A. Ansari

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT

December 25, 2011 by hgpu

A GPU-supported High-Level Programming Language for Image Processing

Ami Ono, Katsuhiko Kondo, Takafumi Inaba, Tomoaki Tsumura, Hiroshi Matsuo

View

Download (PDF)

Tags: CUDA, Data parallelism, High-level Languages, Image processing, nVidia, nVidia GeForce GTX 280

December 25, 2011 by hgpu

Image processing algorithm optimization with CUDA for Pure Data

Rudi Giot, Abilio Rodrigues e Sousa

View

Download (PDF)

Tags: Algorithm optimization, Algorithms, CUDA, Image processing, nVidia, Optimization

December 24, 2011 by hgpu

Improving the usability of hierarchical representations for interactively labeling large image data sets

Julia Moehrmann, Stefan Bernstein, Thomas Schlegel, Gunter Werner, Gunther Heidemann

View

Download (PDF)

Tags: ATI, ATI Mobility Radeon HD 4200, Clustering, Image processing, Image recognition, nVidia, nVidia GeForce 9600 M GT, Self-organizing map, Visualization

December 22, 2011 by hgpu

A GPU framework for parallel segmentation of volumetric images using discrete deformable model

Jerome Schmid, Jose A. Iglesias Guitian, Enrico Gobbetti, Nadia Magnenat-Thalmann

View

Download (PDF)

Tags: CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, Visualization

December 22, 2011 by hgpu

Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs

Linh Ha, Marcel Prastawa, Guido Gerig, John H. Gilmore, Claudio T. Silva, Sarang Joshi1

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, Image registration, Medicine, MRI, nVidia, nVidia GeForce GTX 260

December 21, 2011 by hgpu

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

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Abundance Estimation Algorithms using NVIDIA CUDA Technology

Parallel Implementation of Compressive Sensing Based SAR Imaging with GPU

Parallel Implementation Algorithm of Motion Estimation for GPU Applications

Parallelism, Patterns, and Performance in Iterative MRI Reconstruction

Multilevel Tile Load Map on Massive Terrain Visualization

GPU-Parallel Implementation of Color based Medical Image Retrieval in Compressed Domain

Parallel Implementation of Shape based Image Retrieval Approach on CUDA in Compressed Domain

A GPU-supported High-Level Programming Language for Image Processing

Image processing algorithm optimization with CUDA for Pure Data

Improving the usability of hierarchical representations for interactively labeling large image data sets

A GPU framework for parallel segmentation of volumetric images using discrete deformable model

Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs

Recent source codes

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

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Most viewed papers (last 30 days)