Xiaowen Chu

AutoML: A Survey of the State-of-the-Art

Deep learning has penetrated all aspects of our lives and brought us gre...
08/02/2019 ∙ by Xin He, et al. ∙ 257 ∙ share

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Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models

Skin disease is one of the most common types of human diseases, which ma...
11/20/2019 ∙ by Xin He, et al. ∙ 18 ∙ share

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IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation

Indoor robotics localization, navigation and interaction heavily rely on...
12/20/2019 ∙ by Qiang Wang, et al. ∙ 2 ∙ share

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Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Deep learning frameworks have been widely deployed on GPU servers for de...
11/16/2017 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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GPGPU Performance Estimation with Core and Memory Frequency Scaling

Graphics Processing Units (GPUs) support dynamic voltage and frequency s...
01/19/2017 ∙ by Qiang Wang, et al. ∙ 0 ∙ share

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Modeling and Evaluation of Synchronous Stochastic Gradient Descent in Distributed Deep Learning on Multiple GPUs

With huge amounts of training data, deep learning has made great breakth...
05/10/2018 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

Synchronized stochastic gradient descent (SGD) optimizers with data para...
07/30/2018 ∙ by Xianyan Jia, et al. ∙ 0 ∙ share

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MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms

Distributed synchronous stochastic gradient descent has been widely used...
11/27/2018 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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Performance Evaluation of Deep Learning Tools in Docker Containers

With the success of deep learning techniques in a broad range of applica...
11/09/2017 ∙ by Pengfei Xu, et al. ∙ 0 ∙ share

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Measurement and Analysis of the Bitcoin Networks: A View from Mining Pools

Mining pools, the main components of the Bitcoin network, dominate the c...
02/20/2019 ∙ by Canhui Wang, et al. ∙ 0 ∙ share

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A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks

Distributed synchronous stochastic gradient descent (S-SGD) with data pa...
01/14/2019 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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GPU Accelerated Keccak (SHA3) Algorithm

Hash functions like SHA-1 or MD5 are one of the most important cryptogra...
02/14/2019 ∙ by Canhui Wang, et al. ∙ 0 ∙ share

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GPU Accelerated AES Algorithm

It has been widely accepted that Graphics Processing Units (GPU) is one ...
02/14/2019 ∙ by Canhui Wang, et al. ∙ 0 ∙ share

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Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Deep neural networks (DNNs) have become widely used in many AI applicati...
09/15/2019 ∙ by Yuxin Wang, et al. ∙ 0 ∙ share

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Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees

To reduce the long training time of large deep neural network (DNN) mode...
11/20/2019 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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Understanding Top-k Sparsification in Distributed Deep Learning

Distributed stochastic gradient descent (SGD) algorithms are widely depl...
11/20/2019 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study

Over the past years, great progress has been made in improving the compu...
05/27/2019 ∙ by Zhenheng Tang, et al. ∙ 0 ∙ share

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MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning

Distributed synchronous stochastic gradient descent has been widely used...
12/18/2019 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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A Survey of Deep Learning Techniques for Neural Machine Translation

In recent years, natural language processing (NLP) has got great develop...
02/18/2020 ∙ by Shuoheng Yang, et al. ∙ 0 ∙ share

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Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs

Distributed Deep Learning (DDL) has rapidly grown its popularity since i...
02/24/2020 ∙ by Qiang Wang, et al. ∙ 0 ∙ share

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FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC

Promising federated learning coupled with Mobile Edge Computing (MEC) is...
02/22/2020 ∙ by Rongfei Zeng, et al. ∙ 0 ∙ share

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Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection

Distributed learning techniques such as federated learning have enabled ...
02/22/2020 ∙ by Zhenheng Tang, et al. ∙ 0 ∙ share

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Xiaowen Chu

Featured Co-authors

Bo Li

Xiaoming Liu

Qiang Wang

Xin He

Shaohuai Shi

Wei He

Pengfei Xu

Simon See

Jiaqi Wang

Yuxin Wang

Xiaofeng Zhang

AutoML: A Survey of the State-of-the-Art

Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models

IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

GPGPU Performance Estimation with Core and Memory Frequency Scaling

Modeling and Evaluation of Synchronous Stochastic Gradient Descent in Distributed Deep Learning on Multiple GPUs

Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms

Performance Evaluation of Deep Learning Tools in Docker Containers

Measurement and Analysis of the Bitcoin Networks: A View from Mining Pools

A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks

GPU Accelerated Keccak (SHA3) Algorithm

GPU Accelerated AES Algorithm

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees

Understanding Top-k Sparsification in Distributed Deep Learning

The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study

MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning

A Survey of Deep Learning Techniques for Neural Machine Translation

Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs

FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC

Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection