| Petuum: A new platform for distributed machine learning on big data EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng, P Xie, A Kumar, ... Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 660 | 2015 |
| Poseidon: An efficient communication architecture for distributed deep learning on {GPU} clusters H Zhang, Z Zheng, S Xu, W Dai, Q Ho, X Liang, Z Hu, J Wei, P Xie, ... 2017 {USENIX} Annual Technical Conference ({USENIX}{ATC} 17), 181-193, 2017 | 507* | 2017 |
| Lightlda: Big topic models on modest computer clusters J Yuan, F Gao, Q Ho, W Dai, J Wei, X Zheng, EP Xing, TY Liu, WY Ma Proceedings of the 24th International Conference on World Wide Web, 1351-1361, 2015 | 242 | 2015 |
| Exploiting bounded staleness to speed up big data analytics H Cui, J Cipar, Q Ho, JK Kim, S Lee, A Kumar, J Wei, W Dai, GR Ganger, ... 2014 USENIX Annual Technical Conference (USENIX ATC 14), 37-48, 2014 | 212 | 2014 |
| Priority-based parameter propagation for distributed DNN training A Jayarajan, J Wei, G Gibson, A Fedorova, G Pekhimenko Proceedings of the 2 nd SysML Conference, Palo Alto, CA, USA, 2019., 2019 | 195 | 2019 |
| High-performance distributed ML at scale through parameter server consistency models W Dai, A Kumar, J Wei, Q Ho, G Gibson, E Xing Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 170 | 2015 |
| Addressing the straggler problem for iterative convergent parallel ML A Harlap, H Cui, W Dai, J Wei, GR Ganger, PB Gibbons, GA Gibson, ... Proceedings of the Seventh ACM Symposium on Cloud Computing, 98-111, 2016 | 165 | 2016 |
| Dorylus: Affordable, Scalable, and Accurate {GNN} Training with Distributed {CPU} Servers and Serverless Threads J Thorpe, Y Qiao, J Eyolfson, S Teng, G Hu, Z Jia, J Wei, K Vora, ... 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2021 | 162 | 2021 |
| Managed communication and consistency for fast data-parallel iterative analytics J Wei, W Dai, A Qiao, Q Ho, H Cui, GR Ganger, PB Gibbons, GA Gibson, ... Proceedings of the Sixth ACM Symposium on Cloud Computing, 381-394, 2015 | 151 | 2015 |
| Overlap Communication with Dependent Computation via Decomposition in Large Deep Learning Models S Wang, J Wei, A Sabne, A Davis, B Ilbeyi, B Hechtman, D Chen, ... Proceedings of the 28th ACM International Conference on Architectural …, 2022 | 62 | 2022 |
| Exploiting iterative-ness for parallel ML computations H Cui, A Tumanov, J Wei, L Xu, W Dai, J Haber-Kucharsky, Q Ho, ... Proceedings of the ACM Symposium on Cloud Computing, 1-14, 2014 | 49 | 2014 |
| Petuum: A framework for iterative-convergent distributed ml W Dai, J Wei, X Zheng, JK Kim, S Lee, J Yin, Q Ho, EP Xing arXiv preprint arXiv:1312.7651 1 (2.1), 2013 | 43 | 2013 |
| Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory J Wei, G Gibson, P Gibbons, XP Eric EuroSys, 2019 | 12 | 2019 |
| Consistent bounded-asynchronous parameter servers for distributed ML J Wei, W Dai, A Kumar, X Zheng, Q Ho, EP Xing arXiv preprint arXiv:1312.7869, 2013 | 12 | 2013 |
| Benchmarking apache spark with machine learning applications J Wei, JK Kim, GA Gibson Parallel Data Lab., Carnegie Mellon Univ., Pittsburgh, PA, USA, 2016 | 9 | 2016 |
| Parallel implementation of expectation-maximization for fast convergence H Cui, J Wei, W Dai ACM proceedings, 2010 | 6 | 2010 |
| A software toolkit for visualizing enterprise routing design X Sun, J Wei, SG Rao, GG Xie 2011 4th Symposium on Configuration Analytics and Automation (SAFECONFIG), 1-8, 2011 | 3 | 2011 |
| Dynamic scheduling for dynamic control flow in deep learning systems J Wei, G Gibson, V Vasudevan, E Xing URL http://www. cs. cmu. edu/jinlianw/papers/dynamic_scheduling_nips18_sysml …, 0 | 3* | |
| Scheduling for Efficient Large-Scale Machine Learning Training J Wei Intel, 2019 | 1 | 2019 |
| Addressing the Long-Lineage Bottleneck in Apache Spark H Wang, J Wei, G Gibson | 1 | 2018 |
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon U在 cs.cmu.edu 的电子邮件经过验证