high performance computing on graphics processing units: hgpu.org

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Real-time colouring and filtering with graphics shaders

Dany Vohl, Christopher J. Fluke, David G. Barnes, Amr H. Hassan

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Tags: Algorithms, Astrophysics, Filtering, GLSL, Image processing, nVidia, nVidia GeForce GT 750 M, nVidia GeForce GTX Titan X, nVidia Grid K1, Package, Rendering

July 5, 2017 by hgpu

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

Andreas Palsson

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Tags: Algorithms, Android, Image processing, Java, OpenCL, RenderScript, Thesis

June 25, 2017 by hgpu

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

Lingyu Duan, Wei Sun, Xinfeng Zhang, Jie Chen, Jianxiong Yin, Simon See, Tiejun Huang, Alex C. Kot, Wen Gao

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Tags: Benchmarking, CUDA, Hybrid computing, Image processing, Neural networks, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, nVidia Tegra TX1, Tesla M40

June 1, 2017 by hgpu

Accelerating Discrete Wavelet Transforms on GPUs

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik

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Tags: ATI, ATI Radeon HD 6970, Computer science, Discrete Wavelet Transform, HLSL, Image processing, nVidia, nVidia GeForce GTX Titan X, OpenCL, Pixel shaders

May 24, 2017 by hgpu

Accelerating Discrete Wavelet Transforms on Parallel Architectures

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Discrete Wavelet Transform, Image processing, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenGL, Performance, Pixel shaders

April 30, 2017 by hgpu

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Takuya Matsumoto, Kiminori Matsuzaki

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Tags: Computer science, CUDA, Haskell, Image processing, MRI, nVidia, nVidia GeForce GTX 750 Ti

April 3, 2017 by hgpu

Large-scale image analysis using docker sandboxing

B. Sengupta, E. Vazquez, M. Sasdelli, Y. Qian, M. Peniak, L. Netherton, G. Delfino

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia Quadro M 6000

March 14, 2017 by hgpu

Speckle Reduction with Trained Nonlinear Diffusion Filtering

Wensen Feng, Yunjin Chen

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Tags: CNN, Computer vision, Filtering, Image processing, Matlab, nVidia, nVidia GeForce GXT 780 Ti, Package, SAR

February 28, 2017 by hgpu

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

Alex Sundstrom, Victor Ahdel

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Tags: Algorithms, AMD Radeon R9 280X, ATI, Computer science, Image processing, nVidia, nVidia GeForce GTX 960, OpenCL, Performance, Thesis

February 26, 2017 by hgpu

Improved Lossless Image Compression Model Using Coefficient Based Discrete Wavelet Transform

T. Velumani, S. Sukumaran

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Tags: Compression, Computational Complexity, Discrete Wavelet Transform, Image processing, OpenCL, Probability

February 14, 2017 by hgpu

GPU-Accelerated SVM Training Algorithm Based on PC and Mobile Device

Yi-Yan Nan, Quan-Zhe Li, Jin-Chun Piao, Shin-Dug Kim

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Tags: Algorithms, AMD Radeon R9 M200X, Android, ATI, Computer science, Image processing, Matrix multiplication, OpenCL, Pattern recognition

February 10, 2017 by hgpu

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Robert T. Kelly

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Tags: Computer science, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, Theano, Thesis, Torch

February 5, 2017 by hgpu

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ParTeCL: parallel testing using OpenCL

Snowflake: A Lightweight Portable Stencil DSL

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

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high performance computing on graphics processing units: hgpu.org

Real-time colouring and filtering with graphics shaders

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

Accelerating Discrete Wavelet Transforms on GPUs

Accelerating Discrete Wavelet Transforms on Parallel Architectures

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Large-scale image analysis using docker sandboxing

Speckle Reduction with Trained Nonlinear Diffusion Filtering

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

Improved Lossless Image Compression Model Using Coefficient Based Discrete Wavelet Transform

GPU-Accelerated SVM Training Algorithm Based on PC and Mobile Device

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Recent source codes

ParTeCL: parallel testing using OpenCL

DenseNet: Densely Connected Convolutional Networks

SVMbenchmark: CUDA and OpenCL SVM training benchmark

llvm2KITTeL

shwirl: Meaningful colouring of spectral cube data with volume rendering

QuadricCurvature

entropy-sgd: Lua implementation of Entropy-SGD

LightGBM-GPU: GPU Accelerated LightGBM for Histogram-based GBDT Training

Snowflake: A Lightweight Portable Stencil DSL

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

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International Conference on Intelligent Autonomous Systems (ICIAS), 2018

International Conference on Robotics and Intelligent System (ICRIS), 2018

International Conference on Image and Graphics Processing (ICIGP), 2018

8th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB), 2018

The 10th International Conference on Computer Modeling and Simulation (ICCMS), 2018