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NNS: The Case For Neural Network-based Sorting

Xiao-ke Zhu, Tai-ning Chen, Jing He, Wei Zhou

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Sorting, TensorFlow

July 28, 2019 by hgpu

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

Ander Biguri, Reuben Lindroos, Robert Bryll, Hossein Towsyfyan, Hans Deyhle, Richard Boardman, Mark Mavrogordato, Manjit Dosanjh, Steven Hancock, Thomas Blumensath

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Tags: Algorithms, Computed tomography, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, Package

May 12, 2019 by hgpu

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Sangkyun Lee, Jeonghyun Lee

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Tags: Algorithms, ARM, Compression, Computer science, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Package

May 5, 2019 by hgpu

Wasserstein-Fisher-Rao Document Distance

Zihao Wang, Datong Zhou, Yong Zhang, Hao Wu, Chenglong Bao

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Tags: Computer science, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 1080 Ti

April 28, 2019 by hgpu

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

Ao Ren, Tianyun Zhang, Shaokai Ye, Jiayu Li, Wenyao Xu, Xuehai Qian, Xue Lin, Yanzhi Wang

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Tags: Caffe, Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla P100

January 6, 2019 by hgpu

A Study on the Acceleration of Arrival Curve Construction and Regular Specification Mining using GPUs

Nirmal Joshi Benann Rajendra

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Tags: AMD Radeon R9 390X, ATI, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080 Ti, OpenCL, Thesis

December 30, 2018 by hgpu

Performance Analysis of a Stereo Matching Implementation in OpenCL

Stephan Rotheneder

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 750 Ti, nVidia Quadro 1000 M, OpenCL, Stereo vision

December 16, 2018 by hgpu

A Framework for Fast and Efficient Neural Network Compression

Hyeji Kim, Muhammad Umar Karim, Chong-Min Kyung

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Tags: ARM, Caffe, Compression, Computational Complexity, Computer science, Computer vision, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti

December 9, 2018 by hgpu

Accelerating Low-End Edge Computing with Cross-Kernel Functionality Abstraction

Chao Wu, Yaoxue Zhang, Yuezhi Zhou, Qiushi Li

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance

November 18, 2018 by hgpu

A Comparative Measurement Study of Deep Learning as a Service Framework

Yanzhao Wu, Ling Liu, Calton Pu, Wenqi Cao, Semih Sahin, Wenqi Wei, Qi Zhang

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Tags: Caffe, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Tesla M60, Theano

November 3, 2018 by hgpu

OpenCL Performance Prediction using Architecture-Independent Features

Beau Johnston, Greg Falzon, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon R9 290X, AMD Radeon R9 295X2, AMD Radeon RX 480, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, OpenCL, Package, performance portability, Tesla K20, Tesla K40

November 3, 2018 by hgpu

Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms

Andreea Anghel, Nikolaos Papandreou, Thomas Parnell, Alessandro De Palma, Haralampos Pozidis

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Tags: Algorithms, Bayesian, Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti

September 16, 2018 by hgpu

Mass_Flow_Estimation: Semi-supervised implementation of a DNN for mass prediction from sparsely labeled images

Mass Estimation from Images using Deep Neural Network and Sparse Ground Truth

KNN: k-Nearest Neighbours algorithm

High Performance Computing via High Level Synthesis

SODECL: library of ordinary differential equation (ODE) and stochastic differential equation (SDE) solvers in OpenCL

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

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7th International Workshop on OpenCL, 2019

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Boston, MA, USA

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Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

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International Conference on Frontiers of Neural Networks (ICFNN), 2019

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Rome, Italy

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high performance computing on graphics processing units: hgpu.org

NNS: The Case For Neural Network-based Sorting

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Wasserstein-Fisher-Rao Document Distance

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

A Study on the Acceleration of Arrival Curve Construction and Regular Specification Mining using GPUs

Performance Analysis of a Stereo Matching Implementation in OpenCL

A Framework for Fast and Efficient Neural Network Compression

Accelerating Low-End Edge Computing with Cross-Kernel Functionality Abstraction

A Comparative Measurement Study of Deep Learning as a Service Framework

OpenCL Performance Prediction using Architecture-Independent Features

Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms

Recent source codes

Mass_Flow_Estimation: Semi-supervised implementation of a DNN for mass prediction from sparsely labeled images

KNN: k-Nearest Neighbours algorithm

SODECL: library of ordinary differential equation (ODE) and stochastic differential equation (SDE) solvers in OpenCL

sisph: Simple Iterative Incompressible Smoothed Particle Hydrodynamics

GraphBLAST: High-Performance Linear Algebra-based Graph Primitives on GPUs

FAST: Framework for Heterogeneous Medical Image Computing and Visualization

ESBMC-GPU

FBLAS: BLAS implementation for Intel FPGA

CuLE: A CUDA port of the Atari Learning Environment (ALE)

MagmaDNN

Most viewed papers (last 30 days)

Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019