high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science » Computer vision

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Patrick Wieschollek, Oliver Wang, Alexander Sorkine-Hornung, Hendrik P.A. Lensch

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Tags: Computer science, Computer vision, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, Vector quantization

February 22, 2017 by hgpu

Backpropagation Training for Fisher Vectors within Neural Networks

Patrick Wieschollek, Fabian Groh, Hendrik P.A. Lensch

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

February 10, 2017 by hgpu

Efficient Neural Network Acceleration on GPGPU using Content Addressable Memory

Mohsen Imani, Daniel Peroni, Yeseong Kim, Abbas Rahimi, Tajana Rosing

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Computer vision, Image processing, Neural networks, OpenCL

February 2, 2017 by hgpu

Deep Convolutional Network evaluation on the Intel Xeon Phi: Where Subword Parallelism meets Many-Core

Gaurav Raina

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Tags: Computer science, Computer vision, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Thesis

January 26, 2017 by hgpu

An OpenCL(TM) Deep Learning Accelerator on Arria 10

Utku Aydonat, Shane O'Connell, Davor Capalija, Andrew C. Ling, Gordon R. Chiu

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Tags: CNN, Computer science, Computer vision, Deep learning, FPGA, OpenCL, Performance

January 16, 2017 by hgpu

Streaming GPU Singular Value and Dynamic Mode Decompositions

Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton

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Tags: Algorithms, Computer vision, CUDA, Mathematics, Matrix multiplication, Numerical Analysis, nVidia, Sparse matrix, Tesla K40

December 26, 2016 by hgpu

Deep, Dense, and Low-Rank Gaussian Conditional Random Fields

Siddhartha Chandra, Iasonas Kokkinos

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Tags: Caffe, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1080

November 30, 2016 by hgpu

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

Matthew W. Moskewicz, Ali Jannesari, Kurt Keutzer

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Tags: AMD R9 Nano, ARM, ATI, Code generation, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

November 23, 2016 by hgpu

Diplomat: Mapping of multi-kernel applications using a static dataflow abstraction

Bruno Bodin, Luigi Nardi, Paul H. J. Kelly, Michael F. P. O'Boyle

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Tags: ARM, Computer science, Computer vision, Heterogeneous systems, OpenCL

November 3, 2016 by hgpu

Programming Heterogeneous Systems from an Image Processing DSL

Jing Pu, Steven Bell, Xuan Yang, Jeff Setter, Stephen Richardson, Jonathan Ragan-Kelley, Mark Horowitz

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Tags: ARM, Computer science, Computer vision, CUDA, DSL, FPGA, Image processing, nVidia, nVidia Jetson TK1, OpenGL, Package

November 1, 2016 by hgpu

GPU-accelerated real-time stixel computation

Daniel Hernandez-Juarez, Antonio Espinosa, David Vazquez, Antonio Manuel Lopez, Juan Carlos Moure

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Package

October 15, 2016 by hgpu

Embedded real-time stereo estimation via Semi-Global Matching on the GPU

Daniel Hernandez-Juarez, Alejandro Chacon, Antonio Espinosa, David Vazquez, Juan Carlos Moure, Antonio Manuel Lopez

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Package

October 15, 2016 by hgpu

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qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

Simulating Quantum Computers Using OpenCL

hStreams-benchmark: The benchmark of Intel hStreams

Auto-tuning Streamed Applications on Intel Xeon Phi

Parabix

Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework

HLS4ML

Fast inference of deep neural networks in FPGAs for particle physics

cytonRL: reinforcement learning, deep Q-network, double DQN, dueling DQN, prioritized experience replay

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

DLL: A Blazing Fast Deep Neural Network Library

See all packages

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2018

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Osaka, Japan

International Conference on Biomedicine & Pharmacotherapy, 2018

2018

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28-30

Bangkok

8th International Workshop on Computer Science and Engineering (WCSE’18), 2018

2018

October

15-16

Helsinki, Finland

International Conference on Robotics, Artificial Intelligence, Automation and Mechatronics, 2018

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27-29

No.2 Chong Wen Road, Nan An District, Chongqing 400065, P. R. China

The 3rd IEEE International Conference on Image, Vision and Computing (ICIVC), 2018

2018

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23-25

Room 301, 2nd Floor, No.2 Teaching Building, West Area of the campus, No. 388 Lumo Road,Wuhan, P.R. China

The 2th International Conference on Robotics and Automation Sciences (ICRAS), 2018

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high performance computing on graphics processing units: hgpu.org

Applications

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Backpropagation Training for Fisher Vectors within Neural Networks

Efficient Neural Network Acceleration on GPGPU using Content Addressable Memory

Deep Convolutional Network evaluation on the Intel Xeon Phi: Where Subword Parallelism meets Many-Core

An OpenCL(TM) Deep Learning Accelerator on Arria 10

Streaming GPU Singular Value and Dynamic Mode Decompositions

Deep, Dense, and Low-Rank Gaussian Conditional Random Fields

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

Diplomat: Mapping of multi-kernel applications using a static dataflow abstraction

Programming Heterogeneous Systems from an Image Processing DSL

GPU-accelerated real-time stixel computation

Embedded real-time stereo estimation via Semi-Global Matching on the GPU

Recent source codes

glow: Compiler for Neural Network hardware accelerators

GENESYS: GPU system calls from on ROCm

SR-NMT: Implementation in pytorch of SR-NMT

dlbench: Benchmarking State-of-the-Art Deep Learning Software Tools

qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

hStreams-benchmark: The benchmark of Intel hStreams

Parabix

HLS4ML

cytonRL: reinforcement learning, deep Q-network, double DQN, dueling DQN, prioritized experience replay

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

Most viewed papers (last 30 days)

Featured events

International Conference on Biomedicine & Pharmacotherapy, 2018

8th International Workshop on Computer Science and Engineering (WCSE’18), 2018

International Conference on Robotics, Artificial Intelligence, Automation and Mechatronics, 2018

The 3rd IEEE International Conference on Image, Vision and Computing (ICIVC), 2018

The 2th International Conference on Robotics and Automation Sciences (ICRAS), 2018