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Hybrid Electrical/Optical Switch Architectures for Training Distributed Deep Learning in Large-Scale

IEICE Transactions on Information and Systems, 2021/08/01, Vol.E104.D(8), pp.1332-1339

2021

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Layout-Conscious Expandable Topology for Low-Degree Interconnection Networks

IEICE Transactions on Information and Systems, 2016/05/01, Vol.E99.D(5), pp.1275-1284

2016

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Efficient MPI‐AllReduce for large‐scale deep learning on GPU‐clusters

Concurrency and computation, 2021-06, Vol.33 (12), p.n/a

2021

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High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion

PloS one, 2023-09, Vol.18 (9), p.e0291865-e0291865

2023

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Impact of future climate change on river discharge and groundwater recharge: a case study of Ho Chi Minh City, Vietnam

Journal of water and climate change, 2022-03, Vol.13 (3), p.1313-1325

2022

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Fuzzy Q-Learning-Based Opportunistic Communication for MEC-Enhanced Vehicular Crowdsensing

IEEE eTransactions on network and service management, 2022-12, Vol.19 (4), p.5021-5033

2022

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IEEE_Xplore

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource-Constrained Devices Using Divide and Collaborative Training

IEEE eTransactions on network and service management, 2024-02, Vol.21 (1), p.418-436

2024

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Spatial-temporal Coverage Maximization in Vehicle-based Mobile Crowdsensing for Air Quality Monitoring

2022 IEEE Wireless Communications and Networking Conference (WCNC), 2022, p.1449-1454

2022

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IEEE_Xplore

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

Proceedings of the 51st International Conference on Parallel Processing, 2022, p.1-11

2022

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On the Feasibility of Hybrid Electrical/Optical Switch Architecture for Large-Scale Training of Distributed Deep Learning

2019 IEEE/ACM Workshop on Photonics-Optics Technology Oriented Networking, Information and Computing Systems (PHOTONICS), 2019, p.7-14

2019

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Hierarchical Distributed-Memory Multi-Leader MPI-Allreduce for Deep Learning Workloads

2018 Sixth International Symposium on Computing and Networking Workshops (CANDARW), 2018, p.216-222

2018

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IEEE_Xplore

Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning

2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022, p.1085-1096

2022

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IEEE_Xplore

Effective switchless inter-FPGA memory networks

Journal of parallel and distributed computing, 2023-09, Vol.179, p.104713, Article 104713

2023

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Topology-aware Sparse Allreduce for Large-scale Deep Learning

2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC), 2019, p.1-8

2019

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A data-driven approach for high accurate spatiotemporal precipitation estimation

Neural computing & applications, 2024-04, Vol.36 (11), p.6099-6118

2024

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Scalable Low-Latency Inter-FPGA Networks

2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022, p.234-245

2022

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IEEE_Xplore

Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA

SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, 2020, p.1-15

2020

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Simeuro: A Hybrid CPU-GPU Parallel Simulator for Neuromorphic Computing Chips

IEEE transactions on parallel and distributed systems, 2023-10, Vol.34 (10), p.1-16

2023

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IEEE_Xplore

Q-learning-based Opportunistic Communication for Real-time Mobile Air Quality Monitoring Systems

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), 2021, p.1-7

2021

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Deep Reinforcement Learning-based Charging Algorithm for Target Coverage and Connectivity in WRSNs

2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2022, p.1178-1184

2022

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High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion

PloS one, 2023-01, Vol.18 (9), p.e0291865

2023

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Combating Quality Distortion in Federated Learning with Collaborative Data Selection

Advances in Knowledge Discovery and Data Mining, p.182-193

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Low-Reliable Low-Latency Networks Optimized for HPC Parallel Applications

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), 2018, p.1-10

2018

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IEEE_Xplore

Cable-geometric error-prone approach for low-latency interconnection networks

2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2017, p.699-702

2017

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A diagonal cabling approach to data center and HPC systems

Proceedings of the Seventh Symposium on Information and Communication Technology, 2016, p.265-271

2016

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Hybrid Electrical/Optical Switch Architectures for Training Distributed Deep Learning in Large-Scale

Layout-Conscious Expandable Topology for Low-Degree Interconnection Networks

Efficient MPI‐AllReduce for large‐scale deep learning on GPU‐clusters

High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion

Impact of future climate change on river discharge and groundwater recharge: a case study of Ho Chi Minh City, Vietnam

Fuzzy Q-Learning-Based Opportunistic Communication for MEC-Enhanced Vehicular Crowdsensing

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource-Constrained Devices Using Divide and Collaborative Training

Spatial-temporal Coverage Maximization in Vehicle-based Mobile Crowdsensing for Air Quality Monitoring

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

On the Feasibility of Hybrid Electrical/Optical Switch Architecture for Large-Scale Training of Distributed Deep Learning

Hierarchical Distributed-Memory Multi-Leader MPI-Allreduce for Deep Learning Workloads

Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning

Effective switchless inter-FPGA memory networks

Topology-aware Sparse Allreduce for Large-scale Deep Learning

A data-driven approach for high accurate spatiotemporal precipitation estimation

Scalable Low-Latency Inter-FPGA Networks

Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA

Simeuro: A Hybrid CPU-GPU Parallel Simulator for Neuromorphic Computing Chips

Q-learning-based Opportunistic Communication for Real-time Mobile Air Quality Monitoring Systems

Deep Reinforcement Learning-based Charging Algorithm for Target Coverage and Connectivity in WRSNs

High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion

Combating Quality Distortion in Federated Learning with Collaborative Data Selection

Low-Reliable Low-Latency Networks Optimized for HPC Parallel Applications

Cable-geometric error-prone approach for low-latency interconnection networks

A diagonal cabling approach to data center and HPC systems

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