high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Automatic Optimization of In-Flight Memory Transactions for GPU Accelerators based on a Domain-Specific Language for Medical Imaging

Richard Membarth, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: Code generation, CUDA, Image processing, nVidia, OpenCL, Optimization, Package, Tesla C2050

July 3, 2012 by hgpu

Two Stage Data Mining Technique for Fast Monsoon Onset Prediction

Dinu John, K. K. Sindhu, B. B. Meshram

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Tags: CUDA, Data mining, Earth and Space Sciences, Image processing, nVidia, Weather prediction

July 3, 2012 by hgpu

API-Compiling for Image Hardware Accelerators

Fabien Coelho, Francois Irigoin

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Tags: Code generation, Image processing, nVidia, nVidia GeForce 9300 GE, OpenCL

July 2, 2012 by hgpu

CUDA-accelerated Hierarchical K-means

Che-Chun Lee, Kuan-Yu Chu

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Tags: Clustering, CUDA, Image processing, nVidia, Tesla C1060

July 1, 2012 by hgpu

A Parallel Image Segmentation Algorithm on GPUs

P. N. Happ, R. Q. Feitosa, C. Bentes, R. Farias

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Tags: CUDA, Image processing, nVidia, nVidia GeForce 9600 GT, Tesla C1060

June 29, 2012 by hgpu

GPU Computing: Image Convolution

Jan Novak, Anton Kaplanyan, Gabor Liktor, Carsten Dachsbacher

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Tags: Education, Image processing, OpenCL, Package

June 20, 2012 by hgpu

Point to point processing of digital images using parallel computing

Eric Olmedo, Jorge de la Calleja, Antonio Benitez, Ma. Auxilio Medina

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GT 430

June 10, 2012 by hgpu

Fast Morphological Image Processing Open-Source Extensions for GPU processing with CUDA

Matthew J. Thurley, Victor Danell

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 470, Package, Signal processing

June 9, 2012 by hgpu

Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines

Jonathan Ragan-Kelley, Andrew Adams, Sylvain Paris, Marc Levoy, Saman Amarasinghe, Fredo Durand

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Tags: Algorithms, CUDA, Filtering, Image processing, nVidia, Tesla C2070

June 8, 2012 by hgpu

Generating Device-specific GPU code for Local Operators in Medical Imaging

Richard Membarth, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Code generation, CUDA, Image processing, Medicine, nVidia, nVidia Quadro FX 5800, OpenCL, RapidMind, Tesla C2050

June 1, 2012 by hgpu

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Matthew Sellitto

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Tags: Algorithms, Heterogeneous systems, Image processing, nVidia, OpenCL, Optimization, Sensing, Tesla M2070, Thesis

May 30, 2012 by hgpu

Performance-Analysis-Based Acceleration of Image Quality Assessment

Thien Phan, Sohum Sohoni, Damon M. Chandler, Eric C. Larson

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 560 Ti

May 29, 2012 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Automatic Optimization of In-Flight Memory Transactions for GPU Accelerators based on a Domain-Specific Language for Medical Imaging

Two Stage Data Mining Technique for Fast Monsoon Onset Prediction

API-Compiling for Image Hardware Accelerators

CUDA-accelerated Hierarchical K-means

A Parallel Image Segmentation Algorithm on GPUs

GPU Computing: Image Convolution

Point to point processing of digital images using parallel computing

Fast Morphological Image Processing Open-Source Extensions for GPU processing with CUDA

Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines

Generating Device-specific GPU code for Local Operators in Medical Imaging

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Performance-Analysis-Based Acceleration of Image Quality Assessment

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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