Ping Gong

According to our database, Ping Gong authored at least 13 papers between 2021 and 2026.

Collaborative distances:

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

2026

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation.

Haoyue Tan, Shengnan Wang, Yulin Qiao, Juncheng Zhang, Youhui Bai, Ping Gong, Zewen Jin, Cheng Li

CoRR, April, 2026

GLPilot: Efficient Distributed GNN Training With Learnable Embeddings.

Chengru Yang, Chaoyi Ruan, Chengjie Tang, Ping Gong, Shiyi Wang, Xiang Song, Cheng Li

IEEE Trans. Parallel Distributed Syst., February, 2026

Lagom: Unleashing the Power of Communication and Computation Overlapping for Distributed LLM Training.

Guanbin Xu, ZhenGuo Xu, Yuzhe Li, Youhui Bai, Ping Gong, Chaoyi Ruan, Cheng Li

CoRR, February, 2026

SMIDT: High-Performance Inference Framework for MoE Models with Dynamic Top-K Routing.

Zewen Jin, Shen Fu, Chengjie Tang, Youhui Bai, Shengnan Wang, Jiaan Zhu, Chizheng Fang, Ping Gong, Cheng Li

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

CLO: Efficient LLM Inference System with CPU-Light KVCache Offloading via Algorithm-System Co-Design.

Jiawei Yi, Ping Gong, Youhui Bai, Jiaqi Ruan, Shengnan Wang, Pengcheng Wang, Haibo Wang, Weiguang Wang, Xia Zhu, Feng Wu, Cheng Li

CoRR, November, 2025

Efficient Long-Context LLM Inference via KV Cache Clustering.

Jie Hu, Shengnan Wang, Yutong He, Ping Gong, Jiawei Yi, Juncheng Zhang, Youhui Bai, Renhai Chen, Gong Zhang, Cheng Li, Kun Yuan

CoRR, June, 2025

Understanding Data Preprocessing for Effective End-to-End Training of DNN.

Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma, Sam H. Noh

Proceedings of the Advanced Parallel Processing Technologies, 2025

HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference.

Ping Gong, Jiawei Yi, Shengnan Wang, Juncheng Zhang, Zewen Jin, Ouxiang Zhou, Ruibo Liu, Guanbin Xu, Youhui Bai, Bowen Ye, Kun Yuan, Tong Yang, Gong Zhang, Renhai Chen, Feng Wu, Cheng Li

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Eliminating Data Processing Bottlenecks in GNN Training over Large Graphs via Two-level Feature Compression.

Yuxin Ma, Ping Gong, Tianming Wu, Jiawei Yi, Chengru Yang, Cheng Li, Qirong Peng, Guiming Xie, Yongcheng Bao, Haifeng Liu, Yinlong Xu

Proc. VLDB Endow., July, 2024

2023

Understand Data Preprocessing for Effective End-to-End Training of Deep Neural Networks.

Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma, Sam H. Noh

CoRR, 2023

gSampler: General and Efficient GPU-based Graph Sampling for Graph Learning.

Ping Gong, Renjie Liu, Zunyao Mao, Zhenkun Cai, Xiao Yan, Cheng Li, Minjie Wang, Zhuozhao Li

Proceedings of the 29th Symposium on Operating Systems Principles, 2023

2022

BiFeat: Supercharge GNN Training via Graph Feature Quantization.

Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Minjie Wang, Cheng Li, Yuxiong He, Feng Yan

CoRR, 2022

2021

Gradient Compression Supercharged High-Performance Data Parallel DNN Training.

Youhui Bai, Cheng Li, Quan Zhou, Jun Yi, Ping Gong, Feng Yan, Ruichuan Chen, Yinlong Xu

Proceedings of the SOSP '21: ACM SIGOPS 28th Symposium on Operating Systems Principles, 2021