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2020 – today
- 2024
[j5]Kaihao Ma
, Zhenkun Cai, Xiao Yan, Yang Zhang, Zhi Liu, Yihui Feng, Chao Li, Wei Lin, James Cheng:
PPS: Fair and efficient black-box scheduling for multi-tenant GPU clusters. Parallel Comput. 120: 103082 (2024)- [c8]Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. VLDB Workshops 2024 - [i6]Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs. CoRR abs/2404.18209 (2024) - [i5]Renjie Liu, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, Haitian Jiang, Bo Tang, Jinyang Li:
DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training. CoRR abs/2405.05231 (2024) - 2023
- [j4]Kaihao Ma, Xiao Yan, Zhenkun Cai, Yuzhen Huang, Yidi Wu, James Cheng:
FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication. Proc. ACM Manag. Data 1(2): 165:1-165:21 (2023) - [c7]Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang:
DGI: An Easy and Efficient Framework for GNN Model Evaluation. KDD 2023: 5439-5450 - [c6]Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis:
DSP: Efficient GNN Training with Multiple GPUs. PPoPP 2023: 392-404 - [c5]Ping Gong, Renjie Liu, Zunyao Mao, Zhenkun Cai, Xiao Yan, Cheng Li, Minjie Wang, Zhuozhao Li:
gSampler: General and Efficient GPU-based Graph Sampling for Graph Learning. SOSP 2023: 562-578 - [i4]Haitian Jiang, Renjie Liu, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf:
MuseGNN: Interpretable and Convergent Graph Neural Network Layers at Scale. CoRR abs/2310.12457 (2023) - 2022
- [j3]Yidi Wu, Kaihao Ma, Xiao Yan, Zhi Liu, Zhenkun Cai, Yuzhen Huang, James Cheng, Han Yuan, Fan Yu:
Elastic Deep Learning in Multi-Tenant GPU Clusters. IEEE Trans. Parallel Distributed Syst. 33(1): 144-158 (2022) - [j2]Zhenkun Cai, Xiao Yan, Kaihao Ma, Yidi Wu, Yuzhen Huang, James Cheng, Teng Su, Fan Yu:
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training With Auto-Parallelism. IEEE Trans. Parallel Distributed Syst. 33(8): 1967-1981 (2022) - [i3]Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang:
DGI: Easy and Efficient Inference for GNNs. CoRR abs/2211.15082 (2022) - 2021
- [c4]Zhenkun Cai, Xiao Yan, Yidi Wu, Kaihao Ma, James Cheng, Fan Yu:
DGCL: an efficient communication library for distributed GNN training. EuroSys 2021: 130-144 - [c3]Yidi Wu, Kaihao Ma, Zhenkun Cai, Tatiana Jin, Boyang Li, Chengguang Zheng, James Cheng, Fan Yu:
Seastar: vertex-centric programming for graph neural networks. EuroSys 2021: 359-375 - 2020
- [c2]Tatiana Jin, Zhenkun Cai, Boyang Li, Chengguang Zheng, Guanxian Jiang, James Cheng:
Improving resource utilization by timely fine-grained scheduling. EuroSys 2020: 20:1-20:16 - [i2]Zhenkun Cai, Kaihao Ma, Xiao Yan, Yidi Wu, Yuzhen Huang, James Cheng, Teng Su, Fan Yu:
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism. CoRR abs/2004.10856 (2020)
2010 – 2019
- 2018
- [j1]Yuzhen Huang, Tatiana Jin, Yidi Wu, Zhenkun Cai, Xiao Yan, Fan Yang, Jinfeng Li, Yuying Guo, James Cheng:
FlexPS: Flexible Parallelism Control in Parameter Server Architecture. Proc. VLDB Endow. 11(5): 566-579 (2018) - [c1]Da Yan, Hongzhi Chen, James Cheng, Zhenkun Cai, Bin Shao:
Scalable De Novo Genome Assembly Using Pregel. ICDE 2018: 1216-1219 - [i1]Da Yan, Hongzhi Chen, James Cheng, Zhenkun Cai, Bin Shao:
Scalable De Novo Genome Assembly Using Pregel. CoRR abs/1801.04453 (2018)
Coauthor Index
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last updated on 2024-11-08 21:33 CET by the dblp team
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