Shenggan Cheng

According to our database, Shenggan Cheng authored at least 27 papers between 2020 and 2026.

Collaborative distances:

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

2026

Transforming the Use of Earth Observation Data: Exascale Training of a Generative Compression Model with Historical Priors for up to 10,000x Data Reduction.

Jinxiao Zhang, Runmin Dong, Xiyong Wu, Xihan Huang, Shenggan Cheng, Yunkai Yang, Zheng Zhou, Yunpu Xu, Zhaoyang Luo, Miao Yang, Fan Wei, Mengxuan Chen, Yang You, Juepeng Zheng, Weijia Li, Yutong Lu, Haohuan Fu

CoRR, May, 2026

DiT-HC: Enabling Efficient Training of Visual Generation Model DiT on HPC-oriented CPU Cluster.

Jinxiao Zhang, Yunpu Xu, Xiyong Wu, Runmin Dong, Shenggan Cheng, Yi Zhao, Mengxuan Chen, Qinrui Zheng, Jianting Liu, Haohuan Fu

CoRR, January, 2026

HelixPipe: Efficient Distributed Training of Long Sequence Transformers with Attention Parallel Pipeline Parallelism.

Geng Zhang, Shenggan Cheng, Xuanlei Zhao, Ziming Liu, Yang You

Proceedings of the 31st ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2026

MixCache: Mixture-of-Cache for Video Diffusion Transformer Acceleration.

Yuanxin Wei, Lansong Diao, Bujiao Chen, Shenggan Cheng, Zhengping Qian, Wenyuan Yu, Nong Xiao, Wei Lin, Jiangsu Du

Proceedings of the 2026 International Conference on Multimedia Retrieval, 2026

2025

Expert-as-a-Service: Towards Efficient, Scalable, and Robust Large-scale MoE Serving.

Ziming Liu, Boyu Tian, Guoteng Wang, Zhen Jiang, Peng Sun, Zhenhua Han, Tian Tang, Xiaohe Hu, Yanmin Jia, Yan Zhang, He Liu, Mingjun Zhang, Yiqi Zhang, Qiaoling Chen, Shenggan Cheng, Mingyu Gao, Yang You, Siyuan Feng

CoRR, September, 2025

SRDiffusion: Accelerate Video Diffusion Inference via Sketching-Rendering Cooperation.

Shenggan Cheng, Yuanxin Wei, Lansong Diao, Yong Liu, Bujiao Chen, Lianghua Huang, Yu Liu, Wenyuan Yu, Jiangsu Du, Wei Lin, Yang You

CoRR, May, 2025

StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training.

Ziming Liu, Shaoyu Wang, Shenggan Cheng, Zhongkai Zhao, Kai Wang, Xuanlei Zhao, James Demmel, Yang You

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

ElasticMM: Efficient Multimodal LLMs Serving with Elastic Multimodal Parallelism.

Zedong Liu, Shenggan Cheng, Guangming Tan, Yang You, Dingwen Tao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers.

Xuanlei Zhao, Shenggan Cheng, Chang Chen, Zangwei Zheng, Ziming Liu, Zheming Yang, Yang You

Proceedings of the Forty-second International Conference on Machine Learning, 2025

SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning.

Yong Liu, Di Fu, Shenggan Cheng, Zirui Zhu, Yang Luo, Minhao Cheng, Cho-Jui Hsieh, Yang You

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Concerto: Automatic Communication Optimization and Scheduling for Large-Scale Deep Learning.

Shenggan Cheng, Shengjie Lin, Lansong Diao, Hao Wu, Siyu Wang, Chang Si, Ziming Liu, Xuanlei Zhao, Jiangsu Du, Wei Lin, Yang You

Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025

2024

WallFacer: Guiding Transformer Model Training Out of the Long-Context Dark Forest with N-body Problem.

Ziming Liu, Shaoyu Wang, Shenggan Cheng, Zhongkai Zhao, Xuanlei Zhao, James Demmel, Yang You

CoRR, 2024

DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers.

Xuanlei Zhao, Shenggan Cheng, Zangwei Zheng, Zheming Yang, Ziming Liu, Yang You

CoRR, 2024

HeteGen: Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices.

Xuanlei Zhao, Bin Jia, Haotian Zhou, Ziming Liu, Shenggan Cheng, Yang You

CoRR, 2024

AutoChunk: Automated Activation Chunk for Memory-Efficient Long Sequence Inference.

Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Jiarui Fang, Haotian Zhou, Bin Jia, Ziming Liu, Yang You

CoRR, 2024

Liger: Interleaving Intra- and Inter-Operator Parallelism for Distributed Large Model Inference.

Jiangsu Du, Jinhui Wei, Jiazhi Jiang, Shenggan Cheng, Dan Huang, Zhiguang Chen, Yutong Lu

Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2024

FastFold: Optimizing AlphaFold Training and Inference on GPU Clusters.

Shenggan Cheng, Xuanlei Zhao, Guangyang Lu, Jiarui Fang, Tian Zheng, Ruidong Wu, Xiwen Zhang, Jian Peng, Yang You

Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2024

HeteGen: Efficient Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices.

Xuanlei Zhao, Bin Jia, Haotian Zhou, Ziming Liu, Shenggan Cheng, Yang You

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference.

Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Haotian Zhou, Bin Jia, Yang You

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

ATP: Adaptive Tensor Parallelism for Foundation Models.

Shenggan Cheng, Ziming Liu, Jiangsu Du, Yang You

CoRR, 2023

Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency.

Ziming Liu, Shenggan Cheng, Haotian Zhou, Yang You

Proceedings of the International Conference for High Performance Computing, 2023

2022

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours.

Shenggan Cheng, Ruidong Wu, Zhongming Yu, Bin-Rui Li, Xiwen Zhang, Jian Peng, Yang You

CoRR, 2022

2021

tcFFT: Accelerating Half-Precision FFT through Tensor Cores.

Bin-Rui Li, Shenggan Cheng, James Lin

CoRR, 2021

tcFFT: A Fast Half-Precision FFT Library for NVIDIA Tensor Cores.

Bin-Rui Li, Shenggan Cheng, James Lin

Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020

HMS-Net: Hierarchical Multi-Scale Sparsity-Invariant Network for Sparse Depth Completion.

Zixuan Huang, Junming Fan, Shenggan Cheng, Shuai Yi, Xiaogang Wang, Hongsheng Li

IEEE Trans. Image Process., 2020

FTL: A Universal Framework for Training Low-Bit DNNs via Feature Transfer.

Kunyuan Du, Ya Zhang, Haibing Guan, Qi Tian, Yanfeng Wang, Shenggan Cheng, James Lin

Proceedings of the Computer Vision - ECCV 2020, 2020

CUBE - Towards an Optimal Scaling of Cosmological N-body Simulations.

Shenggan Cheng, Hao-Ran Yu, Derek Inman, Qiucheng Liao, Qiaoya Wu, James Lin

Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020