Chengming Zhang

36 papers A* 6A 3B 4Journal 19Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Event-VStream: Event-Driven Real-Time Understanding for Long Video Streams.
CoRR
Zhenghui Guo, Yuanbin Man, Junyuan Sheng, Bowen Lin, Ahmed Ahmed, Bo Jiang, Boyuan Zhang, Miao Yin, Sian Jin, Omprakash Gnawal, Chengming Zhang
2025 A* conf
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction.
CVPR
Yuanbin Man, Ying Huang, Chengming Zhang, Bingzhe Li, Wei Niu, Miao Yin
2025 B conf
High-performance Visual Semantics Compression for AI-Driven Science.
PPoPP
Boyuan Zhang, Luanzheng Guo, Jiannan Tian, Jinyang Liu, Daoce Wang, Fanjiang Ye, Chengming Zhang, Jan Strube, Nathan R. Tallent, Dingwen Tao
2024 J jnl
AdaCM
CoRR
Yuanbin Man, Ying Huang, Chengming Zhang, Bingzhe Li, Wei Niu, Miao Yin
2024 J jnl
GFormer: Accelerating Large Language Models with Optimized Transformers on Gaudi Processors.
CoRR
Chengming Zhang, Xinheng Ding, Baixi Sun, Xiaodong Yu, Weijian Zheng, Zhen Xie, Dingwen Tao
2024 — conf
HRBP: Hardware-friendly Regrouping towards Block-based Pruning for Sparse CNN Training.
CPAL
Haoyu Ma, Chengming Zhang, Lizhi Xiang, Xiaolong Ma, Geng Yuan, Wenkai Zhang, Shiwei Liu, Tianlong Chen, Dingwen Tao, Yanzhi Wang, Zhangyang Wang, Xiaohui Xie
2024 A* conf
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training.
NeurIPS
Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao
2024 J jnl
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training.
CoRR
Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao
2024 J jnl
Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier.
CoRR
Aristeidis Tsaris, Chengming Zhang, Xiao Wang, Junqi Yin, Siyan Liu, Moetasim Ashfaq, Ming Fan, Jong-Youl Choi, Mohamed Wahib, Dan Lu, Prasanna Balaprakash, Fei-Yue Wang
2024 — conf
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.
IPDPS (Workshops)
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2024 A* conf
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.
PODC
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminadabi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2023 — conf
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors.
SC Workshops
Chengming Zhang, Baixi Sun, Xiaodong Yu, Zhen Xie, Weijian Zheng, Kamil A. Iskra, Pete Beckman, Dingwen Tao
2023 J jnl
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors.
CoRR
Chengming Zhang, Baixi Sun, Xiaodong Yu, Zhen Xie, Weijian Zheng, Kamil Iskra, Pete Beckman, Dingwen Tao
2023 J jnl
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.
CoRR
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2023 J jnl
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.
CoRR
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023 A* conf
HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks.
AAAI
Jinqi Xiao, Chengming Zhang, Yu Gong, Miao Yin, Yang Sui, Lizhi Xiang, Dingwen Tao, Bo Yuan
2023 J jnl
HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks.
CoRR
Jinqi Xiao, Chengming Zhang, Yu Gong, Miao Yin, Yang Sui, Lizhi Xiang, Dingwen Tao, Bo Yuan
2023 A conf
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs.
ICS
Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Leon Song, Yuxiong He, Dingwen Tao
2023 J jnl
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs.
CoRR
Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Leon Song, Yuxiong He, Dingwen Tao
2023 B conf
TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.
PPoPP
Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P. Sadayappan, Bo Yuan, Dingwen Tao
2022 A conf
CEAZ: accelerating parallel I/O via hardware-algorithm co-designed adaptive lossy compression.
ICS
Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao
2022 B conf
H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture.
FPL
Chengming Zhang, Tong Geng, Anqi Guo, Jiannan Tian, Martin C. Herbordt, Ang Li, Dingwen Tao
2022 J jnl
H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture.
CoRR
Chengming Zhang, Tong Geng, Anqi Guo, Jiannan Tian, Martin C. Herbordt, Ang Li, Dingwen Tao
2022 J jnl
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates.
CoRR
Baixi Sun, Xiaodong Yu, Chengming Zhang, Jiannan Tian, Sian Jin, Kamil Iskra, Tao Zhou, Tekin Bicer, Pete Beckman, Dingwen Tao
2022 J jnl
TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.
CoRR
Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P. Sadayappan, Bo Yuan, Dingwen Tao
2021 J jnl
CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression.
CoRR
Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao
2021 J jnl
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression.
CoRR
Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
2021 J jnl
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression.
Proc. VLDB Endow.
Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Song, Dingwen Tao
2021 A conf
ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning.
ICS
Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao
2021 — conf
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.
ISQED
Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang
2021 J jnl
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.
CoRR
Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang
2020 J jnl
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning.
CoRR
Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao
2020 A* conf
CurvaNet: Geometric Deep Learning based on Directional Curvature for 3D Shape Analysis.
KDD
Wenchong He, Zhe Jiang, Chengming Zhang, Arpan Man Sainju
2020 A* conf
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition.
DAC
Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, Dingwen Tao
2020 J jnl
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition.
CoRR
Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, Yanzhi Wang, Dingwen Tao
2020 B conf
waveSZ: a hardware-algorithm co-design of efficient lossy compression for scientific data.
PPoPP
Jiannan Tian, Sheng Di, Chengming Zhang, Xin Liang, Sian Jin, Dazhao Cheng, Dingwen Tao, Franck Cappello