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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

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Sriram Kankatala

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Tags: Computer science, CUDA, Data mining, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 550 Ti, Pattern recognition, Pthreads, Thesis

March 5, 2016 by hgpu

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 2015 by hgpu

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Yi Hou, Hong Zhang, Shilin Zhou

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia Quadro K4200, Pattern recognition, Robotics

April 23, 2015 by hgpu

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

David Markvica

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Tags: Algorithms, Biology, Computational biology, Computer science, Heterogeneous systems, Metaheuristics, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Optimization, Pattern recognition, Thesis

October 27, 2014 by hgpu

Caffe: Convolutional Architecture for Fast Feature Embedding

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

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Tags: Cloud, Computer science, CUDA, Neural networks, nVidia, Package, Pattern recognition, Python

August 23, 2014 by hgpu

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

Youssef S. G. Nashed

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTS 450, Pattern recognition, Thesis

August 23, 2014 by hgpu

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Ken Chatfield, Karen Simonyan, Andrew Zisserman

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan, Pattern recognition

July 18, 2014 by hgpu

A Parallel Algorithm of PCA-SIFT Based on CUDA

Ping Zhang, Yongqi Sun, Hao Shen, Rui Zhang

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 240, OpenCV, Pattern recognition, SIFT

June 15, 2014 by hgpu

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Charles J. Gala

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Pattern recognition, Tesla C2050, Thesis

June 3, 2014 by hgpu

GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform

Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R Saniat, Aminur Rahman

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Tags: Algorithms, Compression, Computer vision, CUDA, Image processing, nVidia, Pattern recognition

April 6, 2014 by hgpu

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Integer sorting on multicore

A study of integer sorting on multicores

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10-12

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International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018

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high performance computing on graphics processing units: hgpu.org

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

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

A Parallel Algorithm of PCA-SIFT Based on CUDA

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform

Recent source codes

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Integer sorting on multicore

Most viewed papers (last 30 days)

Featured events

International Conference on Image, Video and Signal Processing (IVSP), 2019

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018