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Modeling the Resource Requirements of Convolutional Neural Networks on Mobile Devices

Zongqing Lu, Swati Rallapalli, Kevin Chan, Thomas La Porta

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson TK1, nVidia Tegra TX1

September 28, 2017 by hgpu

Memory-Efficient Implementation of DenseNets

Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger

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Tags: Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Tesla M40, Torch

July 25, 2017 by hgpu

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

Francesc Sastre Cabot

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, Tesla K80, Tesla M2090, Thesis

July 22, 2017 by hgpu

A Fast Method For Computing Principal Curvatures From Range Images

Andrew Spek, Wai Ho Li, Tom Drummond

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Tags: Computer science, Computer vision, CUDA, nVidia, Package, Tesla K40

July 5, 2017 by hgpu

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Yuechao Lu, Fumihiko Ino, Yasuyuki Matsushita

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Tags: Algorithms, Computer science, Computer vision, CUDA, Linear Algebra, Machine learning, nVidia, Tesla P100

June 25, 2017 by hgpu

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Priya Goyal, Piotr Dollar, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, Kaiming He

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla P100

June 10, 2017 by hgpu

Optimizing Memory Efficiency for Convolution Kernels on Kepler GPUs

Xiaoming Chen, Jianxu Chen, Danny Z. Chen, Xiaobo Sharon Hu

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Tesla K40

June 1, 2017 by hgpu

Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

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Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

Real-Time Adaptive Image Compression

Oren Rippel, Lubomir Bourdev

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Tags: Algorithms, Compression, Computer science, Computer vision, Machine learning, nVidia, nVidia GeForce GTX 980 Ti

May 18, 2017 by hgpu

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Xinyu Zhang, Srinjoy Das, Ojash Neopane, Ken Kreutz-Delgado

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Tags: Algorithms, Computer science, Computer vision, Deep learning, DSP, FPGA, Neural networks

May 11, 2017 by hgpu

Deep Learning in the Automotive Industry: Applications and Tools

Andre Luckow, Matthew Cook, Nathan Ashcraft, Edwin Weill, Emil Djerekarov, Bennie Vorster

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Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia GRID K520, Performance

May 2, 2017 by hgpu

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia

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

April 30, 2017 by hgpu

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Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

GPGPU-Treewidth: A GPU implementation for computing the treewidth of a graph

Computing Treewidth on the GPU

containers-benchs: Just a bunch of method and scripts to test performances with containers

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

OpenCL Actors - Adding Data Parallelism to Actor-based Programming with CAF

OpenCL Actors – Adding Data Parallelism to Actor-based Programming with CAF

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

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high performance computing on graphics processing units: hgpu.org

Modeling the Resource Requirements of Convolutional Neural Networks on Mobile Devices

Memory-Efficient Implementation of DenseNets

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

A Fast Method For Computing Principal Curvatures From Range Images

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Optimizing Memory Efficiency for Convolution Kernels on Kepler GPUs

Implementing Efficient, Portable Computations for Machine Learning

Real-Time Adaptive Image Compression

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Recent source codes

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

GPGPU-Treewidth: A GPU implementation for computing the treewidth of a graph

containers-benchs: Just a bunch of method and scripts to test performances with containers

OpenCL Actors - Adding Data Parallelism to Actor-based Programming with CAF

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

CCSQCDSolverBench: CCS QCD Solver benchmark program (MIC(KNC) version)

TuneBench: Simple tunable OpenCL kernels for many-core accelerators

ZZGemmOoc: GPU GEMM out-of-core solvers

styletransfer: Real-time neural style transfer via meta networks

Most viewed papers (last 30 days)

Featured events

6th International Workshop on OpenCL (IWOCL), 2018

The 2nd International Conference on Machine Learning and Soft Computing (ICMLSC), 2018

10th International Conference on Computer and Automation Engineering (ICCAE), 2018

The 2nd International Conference on Mechanical, Aeronautical and Automotive Engineering (ICMAA), 2018

The 2nd International Conference on Cryptography, Security and Privacy (ICCSP), 2018