| MODIST: Transparent model checking of unmodified distributed systems J Yang, T Chen, M Wu, Z Xu, X Liu, H Lin, M Yang, F Long, L Zhang, ... NSDI 2009, 213-228, 2009 | 332 | 2009 |
| GraM: scaling graph computation to the trillions M Wu, F Yang, J Xue, W Xiao, Y Miao, L Wei, H Lin, Y Dai, L Zhou Proceedings of the Sixth ACM Symposium on Cloud Computing, 408-421, 2015 | 165 | 2015 |
| Estimating gpu memory consumption of deep learning models Y Gao, Y Liu, H Zhang, Z Li, Y Zhu, H Lin, M Yang Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020 | 152 | 2020 |
| An empirical study on program failures of deep learning jobs R Zhang, W Xiao, H Zhang, Y Liu, H Lin, M Yang Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 114* | 2020 |
| Optimizing Data Shuffling in Data-Parallel Computation by Understanding User-Defined Functions J Zhang, H Zhou, R Chen, X Fan, Z Guo, H Lin, JY Li, W Lin, J Zhou, ... 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI 12 …, 2012 | 109 | 2012 |
| An empirical study on quality issues of production big data platform H Zhou, JG Lou, H Zhang, H Lin, H Lin, T Qin 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 2 …, 2015 | 61 | 2015 |
| Runtime performance prediction for deep learning models with graph neural network Y Gao, X Gu, H Zhang, H Lin, M Yang 2023 IEEE/ACM 45th International Conference on Software Engineering …, 2023 | 55 | 2023 |
| A characteristic study on failures of production distributed data-parallel programs S Li, H Zhou, H Lin, T Xiao, H Lin, W Lin, T Xie 2013 35th International Conference on Software Engineering (ICSE), 963-972, 2013 | 51 | 2013 |
| Enhancing the interoperability between deep learning frameworks by model conversion Y Liu, C Chen, R Zhang, T Qin, X Ji, H Lin, M Yang Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020 | 47 | 2020 |
| Data-parallel computation management J Zhang, H Zhou, Z Guo, H Lin, L Zhou US Patent 9,383,982, 2016 | 46 | 2016 |
| G2: A graph processing system for diagnosing distributed systems Z Guo, D Zhou, H Lin, M Yang, F Long, C Deng, C Liu, L Zhou 2011 USENIX Annual Technical Conference (USENIX ATC 11), 2011 | 42 | 2011 |
| Hang analysis: fighting responsiveness bugs X Wang, Z Guo, X Liu, Z Xu, H Lin, X Wang, Z Zhang ACM SIGOPS Operating Systems Review 42 (4), 177-190, 2008 | 36 | 2008 |
| Analysis and detection of soft hang responsiveness program errors H Lin, XI Wang, Z Guo, X Liu, Z Zhang US Patent 8,166,464, 2012 | 32 | 2012 |
| Language-based replay via data flow cut M Wu, F Long, X Wang, Z Xu, H Lin, X Liu, Z Guo, H Guo, L Zhou, Z Zhang Proceedings of the eighteenth ACM SIGSOFT international symposium on …, 2010 | 21 | 2010 |
| Automatic Program Partition For Targeted Replay M Wu, F Long, Z Xu, X Liu, H Lin, Z Guo, Z Zhang, L Zhou US Patent App. 12/951,253, 2012 | 17 | 2012 |
| Resource-Guided Configuration Space Reduction for Deep Learning Models Y Gao, Y Zhu, H Zhang, H Lin, M Yang 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 15 | 2021 |
| An Empirical Study on Quality Issues of Deep Learning Platform Y Gao, X Shi, H Lin, H Zhang, H Wu, R Li, M Yang 2023 IEEE/ACM 45th International Conference on Software Engineering …, 2023 | 6 | 2023 |
| Refty: Refinement Types for Valid Deep Learning Models Y Gao, Z Li, H Lin, H Zhang, M Wu, M Yang 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE …, 2022 | 6 | 2022 |
| GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network H Mei, H Qu, J Sun, Y Gao, H Lin, G Sun 2023 IEEE International Conference on Cluster Computing (CLUSTER), 318-329, 2023 | 5 | 2023 |
| An Empirical Study on Low GPU Utilization of Deep Learning Jobs Y Gao, Y He, X Li, B Zhao, H Lin, Y Liang, J Zhong, H Zhang, J Wang, ... 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE …, 2024 | 4 | 2024 |
Mao YangMicrosoft Research Asiaยืนยันอีเมลแล้วที่ microsoft.com