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09/18/2023
Stochastic Performance Analysis of Phase Decomposition in Hyperledger Fabric
Hyperledger Fabric is one of the most popular permissioned blockchain pl...
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09/03/2023
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs
The rapid growth of memory and computation requirements of large languag...
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08/30/2023
EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning
Car-following models have made significant contributions to our understa...
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08/07/2023
LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models Fine-tuning
The low-rank adaptation (LoRA) method can largely reduce the amount of t...
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06/15/2023
Evaluation and Optimization of Gradient Compression for Distributed Deep Learning
To accelerate distributed training, many gradient compression methods ha...
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03/03/2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
Federated Learning (FL) enables collaborations among clients for train m...
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02/24/2023
Decoupling the All-Reduce Primitive for Accelerating Distributed Deep Learning
Communication scheduling has been shown to be effective in accelerating ...
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11/30/2022
Rethinking Disparity: A Depth Range Free Multi-View Stereo Based on Disparity
Existing learning-based multi-view stereo (MVS) methods rely on the dept...
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11/23/2022
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
One-shot neural architecture search (NAS) substantially improves the sea...
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08/29/2022
SphereDepth: Panorama Depth Estimation from Spherical Domain
The panorama image can simultaneously demonstrate complete information o...
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07/20/2022
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching
Recent advanced studies have spent considerable human efforts on optimiz...
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06/06/2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
In federated learning (FL), model performance typically suffers from cli...
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05/30/2022
Learning Adaptive Propagation for Knowledge Graph Reasoning
Due to the success of Graph Neural Networks (GNNs) in learning from grap...
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11/30/2021
EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs
Generative Adversarial Networks (GANs) have been proven hugely successfu...
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11/22/2021
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
Federated Learning (FL) is a distributed learning paradigm that can lear...
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10/12/2021
Embracing Structure in Data for Billion-Scale Semantic Product Search
We present principled approaches to train and deploy dyadic neural embed...
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10/06/2021
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
Deep neural networks (DNNs) have achieved great success in the area of c...
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06/27/2021
A Comprehensive Survey of Incentive Mechanism for Federated Learning
Federated learning utilizes various resources provided by participants t...
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04/01/2021
Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters
Energy conservation of large data centers for high-performance computing...
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01/26/2021
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...
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01/24/2021
BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing
The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecede...
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01/14/2021
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...
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10/20/2020
Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters
Distributed training techniques have been widely deployed in large-scale...
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08/13/2020
Performance Characterization and Bottleneck Analysis of Hyperledger Fabric
Hyperledger Fabric is a popular open-source project for deploying permis...
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05/29/2020
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...
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05/27/2020
Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges
In recent years, distributed deep learning techniques are widely deploye...
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03/24/2020
FADNet: A Fast and Accurate Network for Disparity Estimation
Deep neural networks (DNNs) have achieved great success in the area of c...
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03/10/2020
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey
Distributed deep learning becomes very common to reduce the overall trai...
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02/24/2020
Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs
Distributed Deep Learning (DDL) has rapidly grown its popularity since i...
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02/22/2020
FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC
Promising federated learning coupled with Mobile Edge Computing (MEC) is...
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02/22/2020
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection
Distributed learning techniques such as federated learning have enabled ...
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02/18/2020
A Survey of Deep Learning Techniques for Neural Machine Translation
In recent years, natural language processing (NLP) has got great develop...
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12/20/2019
IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation
Indoor robotics localization, navigation and interaction heavily rely on...
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12/18/2019
MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning
Distributed synchronous stochastic gradient descent has been widely used...
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11/20/2019
Understanding Top-k Sparsification in Distributed Deep Learning
Distributed stochastic gradient descent (SGD) algorithms are widely depl...
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11/20/2019
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...
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11/20/2019
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...
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09/15/2019
Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models
Deep neural networks (DNNs) have become widely used in many AI applicati...
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08/02/2019
AutoML: A Survey of the State-of-the-Art
Deep learning has penetrated all aspects of our lives and brought us gre...
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05/27/2019
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...
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02/20/2019
Measurement and Analysis of the Bitcoin Networks: A View from Mining Pools
Mining pools, the main components of the Bitcoin network, dominate the c...
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02/14/2019
GPU Accelerated Keccak (SHA3) Algorithm
Hash functions like SHA-1 or MD5 are one of the most important cryptogra...
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02/14/2019
GPU Accelerated AES Algorithm
It has been widely accepted that Graphics Processing Units (GPU) is one ...
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01/14/2019
A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks
Distributed synchronous stochastic gradient descent (S-SGD) with data pa...
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11/27/2018
MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms
Distributed synchronous stochastic gradient descent has been widely used...
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07/30/2018
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
Synchronized stochastic gradient descent (SGD) optimizers with data para...
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05/10/2018
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...
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11/16/2017
Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs
Deep learning frameworks have been widely deployed on GPU servers for de...
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11/09/2017
Performance Evaluation of Deep Learning Tools in Docker Containers
With the success of deep learning techniques in a broad range of applica...
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01/19/2017