Zeyu Ji

Orcid: 0000-0003-0362-7506

According to our database1, Zeyu Ji authored at least 17 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
GroPipe: A Grouped Pipeline Hybrid Parallel Method for Accelerating DCNNs Training.
IEEE Trans. Computers, July, 2025

PRT: An Efficient Pipeline Reuse Technology for Large Models Training.
Proceedings of the IEEE International Conference on Cluster Computing, 2025

2024
Risk factors and prediction model for acute ischemic stroke after off-pump coronary artery bypass grafting based on Bayesian network.
BMC Medical Informatics Decis. Mak., December, 2024

LBB: load-balanced batching for efficient distributed learning on heterogeneous GPU cluster.
J. Supercomput., June, 2024

Revisit and Benchmarking of Automated Quantization Toward Fair Comparison.
IEEE Trans. Computers, January, 2024

MCDCNet: Multi-scale constrained deformable convolution network for apple leaf disease detection.
Comput. Electron. Agric., 2024

2023
Leader population learning rate schedule.
Inf. Sci., April, 2023

Corrections to "Multiple Mobile Charger Charging Strategy Based on Dual Partitioning Model for Wireless Rechargeable Sensor Networks".
IEEE Access, 2023

2022
EP4DDL: addressing straggler problem in heterogeneous distributed deep learning.
J. Supercomput., 2022

DPLRS: Distributed Population Learning Rate Schedule.
Future Gener. Comput. Syst., 2022

GARLSched: Generative adversarial deep reinforcement learning task scheduling optimization for large-scale high performance computing systems.
Future Gener. Comput. Syst., 2022

Multimobile Charger Charging Strategy Based on Dual Partitioning Model for Wireless Rechargeable Sensor Networks.
IEEE Access, 2022

BenQ: Benchmarking Automated Quantization on Deep Neural Network Accelerators.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2021
OKCM: improving parallel task scheduling in high-performance computing systems using online learning.
J. Supercomput., 2021

A tile-fusion method for accelerating Winograd convolutions.
Neurocomputing, 2021

Energy-aware task scheduling optimization with deep reinforcement learning for large-scale heterogeneous systems.
CCF Trans. High Perform. Comput., 2021

PANDA: Population Automatic Neural Distributed Algorithm for Deep Leaning.
Proceedings of the 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), New York City, NY, USA, September 30, 2021


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