high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Image and Signal Processing

Efficient Detection of Sunspots with GPU Acceleration Through CUDA

Kenny May

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Tags: Astrophysics, CUDA, Image processing, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 470, Tesla C2050

March 2, 2013 by hgpu

Full Covariance Gaussian Mixture Models Evaluation on GPU

Jan Vanek, Jan Trmal, Josef V. Psutka, Josef Psutka

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5470, ATI Radeon HD 5670, ATI Radeon HD 5870, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 580, nVidia Quadro FX 770 M, OpenCL, Signal processing, Speech recognition

March 2, 2013 by hgpu

Multi-GPU based on multicriteria optimization for motion estimation system

Carlos Garcia, Guillermo Botella, Fermin Ayuso, Manuel Prieto, Francisco Tirado

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Tags: Algorithms, Computer vision, CUDA, Data parallelism, nVidia, Optical flow, Signal processing, Tesla C1060, Tesla M2070

February 27, 2013 by hgpu

Advanced Video Coding on CPUs and GPUs: Parallelization and RD Analysis

Svetislav Momcilovic, Aleksandar Ilic, Nuno Roma, Leonel Sousa

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Tags: Algorithms, Compression, CUDA, H.264/AVC, Image processing, nVidia, Signal processing, Video encoding

February 25, 2013 by hgpu

Investigating performance variations of an optimized GPU-ported granulometry algorithm

Vincent Boulos, Vincent Fristot, Dominique Houzet, Luc Salvo, Pierre Lhuissier

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Tags: Algorithm optimization, Algorithms, CUDA, FEM, Finite element method, Image processing, Materials Science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia Quadro FX 4000

February 22, 2013 by hgpu

Using High Performance Computing to Improve Image Guided Cancer Treatment

Dante Gama Dessavre

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Tags: CUDA, Image processing, Medicine, nVidia, Radiotherapy, Tesla C2050, Thesis

February 18, 2013 by hgpu

MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

The Implement of Common Beam Forming Using GPU

Jing-hong Jiang, Qi-xiang Han, Hui-zhi Cai, Wei-min Hou

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Tags: CUDA, nVidia, nVidia GeForce GTX 285, Signal processing

February 12, 2013 by hgpu

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Stephen Won

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Tags: Computer vision, CUDA, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, SIFT, Signal processing, Thesis

February 12, 2013 by hgpu

A volume segmentation approach based on GrabCut

Esmitt Ramirez J., Pablo Temoche, Rhadames Carmona

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 470

February 12, 2013 by hgpu

Distributed multi-node, multi-GPU, heterogeneous system for 3D image reconstruction in Electrical Capacitance Tomography – network performance and application analysis

Pawel Kapusta, Michal Majchrowicz, Dominik Sankowski, Lidia Jackowska-Strumillo, Robert Banasiak

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Tags: ATI, ATI Radeon HD 5970, FEM, Finite element method, Heterogeneous systems, Image processing, Image reconstruction, Linear Algebra, Medicine, nVidia, Tesla C2070, Tesla S1070, Tomography

February 9, 2013 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

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high performance computing on graphics processing units: hgpu.org

Applications

Efficient Detection of Sunspots with GPU Acceleration Through CUDA

Full Covariance Gaussian Mixture Models Evaluation on GPU

Multi-GPU based on multicriteria optimization for motion estimation system

Advanced Video Coding on CPUs and GPUs: Parallelization and RD Analysis

Investigating performance variations of an optimized GPU-ported granulometry algorithm

Using High Performance Computing to Improve Image Guided Cancer Treatment

MATLAB and Python for GPU Computing

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

The Implement of Common Beam Forming Using GPU

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

A volume segmentation approach based on GrabCut

Distributed multi-node, multi-GPU, heterogeneous system for 3D image reconstruction in Electrical Capacitance Tomography – network performance and application analysis

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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