b'Xiaowen Chu'

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

Energy conservation of large data centers for high-performance computing...
04/01/2021 ∙ by Xinxin Mei, et al. ∙ 0 ∙ share

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Efficient Multi-objective Evolutionary 3D Neural Architecture Search for COVID-19 Detection with Chest CT Scans

COVID-19 pandemic has spread globally for months. Due to its long incuba...
01/26/2021 ∙ by Xin He, et al. ∙ 0 ∙ share

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BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecede...
01/24/2021 ∙ by Zhe Peng, et al. ∙ 0 ∙ share

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Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

The COVID-19 pandemic has spread globally for several months. Because it...
01/14/2021 ∙ by Xin He, et al. ∙ 0 ∙ share

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Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters

Distributed training techniques have been widely deployed in large-scale...
10/20/2020 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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Performance Characterization and Bottleneck Analysis of Hyperledger Fabric

Hyperledger Fabric is a popular open-source project for deploying permis...
08/13/2020 ∙ by Canhui Wang, et al. ∙ 0 ∙ share

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Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Multiplication of a sparse matrix to a dense matrix (SpDM) is widely use...
05/29/2020 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges

In recent years, distributed deep learning techniques are widely deploye...
05/27/2020 ∙ by Shaohuai Shi, et al. ∙ 0 ∙ share

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FADNet: A Fast and Accurate Network for Disparity Estimation

Deep neural networks (DNNs) have achieved great success in the area of c...
03/24/2020 ∙ by Qiang Wang, et al. ∙ 13 ∙ share

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Communication-Efficient Distributed Deep Learning: A Comprehensive Survey

Distributed deep learning becomes very common to reduce the overall trai...
03/10/2020 ∙ by Zhenheng Tang, 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Xiaowen Chu

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