Wei Gao

According to our database, Wei Gao authored at least 18 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism.

Tenghui Ma, Jihu Guo, Wei Gao, Sitian Lu, Zhisheng Ye, Hanjing Wang, Dahua Lin

CoRR, May, 2026

PromptTuner: SLO-Aware Elastic System for LLM Prompt Tuning.

Wei Gao, Peng Sun, Dmitrii Ustiugov, Tianwei Zhang, Yonggang Wen

CoRR, March, 2026

2025

AdaPtis: Reducing Pipeline Bubbles with Adaptive Pipeline Parallelism on Heterogeneous Models.

Jihu Guo, Tenghui Ma, Wei Gao, Peng Sun, Jiaxing Li, Xun Chen, Yuyang Jin, Dahua Lin

CoRR, September, 2025

IceFrog: A Layer-Elastic Scheduling System for Deep Learning Training in GPU Clusters.

Wei Gao, Zhuoyuan Ouyang, Peng Sun, Tianwei Zhang, Yonggang Wen

IEEE Trans. Parallel Distributed Syst., June, 2025

SPPO:Efficient Long-sequence LLM Training via Adaptive Sequence Pipeline Parallel Offloading.

Qiaoling Chen, Shenggui Li, Wei Gao, Peng Sun, Yonggang Wen, Tianwei Zhang

CoRR, March, 2025

Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving.

Wei Gao, Xinyu Zhou, Peng Sun, Tianwei Zhang, Yonggang Wen

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

2024

UniSched: A Unified Scheduler for Deep Learning Training Jobs With Different User Demands.

Wei Gao, Zhisheng Ye, Peng Sun, Tianwei Zhang, Yonggang Wen

IEEE Trans. Computers, June, 2024

Deep Learning Workload Scheduling in GPU Datacenters: A Survey.

Zhisheng Ye, Wei Gao, Qinghao Hu, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

ACM Comput. Surv., June, 2024

A Layer-Elastic Scheduling System for DLT in GPU Clusters.

Wei Gao

Dataset, May, 2024

Ymir: A Scheduler for Foundation Model Fine-tuning Workloads in Datacenters.

Wei Gao, Weiming Zhuang, Minghao Li, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 38th ACM International Conference on Supercomputing, 2024

AutoSched: An Adaptive Self-configured Framework for Scheduling Deep Learning Training Workloads.

Wei Gao, Xu Zhang, Shan Huang, Shangwei Guo, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 38th ACM International Conference on Supercomputing, 2024

2023

Automatic Transformation Search Against Deep Leakage From Gradients.

Wei Gao, Xu Zhang, Shangwei Guo, Tianwei Zhang, Tao Xiang, Han Qiu, Yonggang Wen, Yang Liu

IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

2022

Astraea: A Fair Deep Learning Scheduler for Multi-Tenant GPU Clusters.

Zhisheng Ye, Peng Sun, Wei Gao, Tianwei Zhang, Xiaolin Wang, Shengen Yan, Yingwei Luo

IEEE Trans. Parallel Distributed Syst., 2022

Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision.

Wei Gao, Qinghao Hu, Zhisheng Ye, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

CoRR, 2022

Titan: a scheduler for foundation model fine-tuning workloads.

Wei Gao, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

2021

Improving Transferability of Adversarial Patches on Face Recognition With Generative Models.

Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Privacy-Preserving Collaborative Learning With Automatic Transformation Search.

Wei Gao, Shangwei Guo, Tianwei Zhang, Han Qiu, Yonggang Wen, Yang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Chronus: A Novel Deadline-aware Scheduler for Deep Learning Training Jobs.

Wei Gao, Zhisheng Ye, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021