| Trade-off between prediction accuracy and underestimation rate in job runtime estimates Y Fan, P Rich, WE Allcock, ME Papka, Z Lan 2017 IEEE International Conference on Cluster Computing (CLUSTER), 530-540, 2017 | 62 | 2017 |
| Scheduling beyond CPUs for HPC Y Fan, Z Lan, P Rich, WE Allcock, ME Papka, B Austin, D Paul Proceedings of the 28th International Symposium on High-Performance Parallel …, 2019 | 54 | 2019 |
| Deep reinforcement agent for scheduling in HPC Y Fan, Z Lan, T Childers, P Rich, W Allcock, ME Papka 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 51 | 2021 |
| Experience and Practice of Batch Scheduling on Leadership Supercomputers at Argonne W Allcock, P Rich, Y Fan, Z Lan Workshop on Job Scheduling Strategies for Parallel Processing, 2017 | 45 | 2017 |
| The effect of system utilization on application performance variability B Li, S Chunduri, K Harms, Y Fan, Z Lan Proceedings of the 9th International Workshop on Runtime and Operating …, 2019 | 30 | 2019 |
| Hybrid workload scheduling on HPC systems Y Fan, Z Lan, P Rich, W Allcock, ME Papka 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022 | 22 | 2022 |
| Joint effects of application communication pattern, job placement and network routing on fat-tree systems P Qiao, X Wang, X Yang, Y Fan, Z Lan Workshop Proceedings of the 47th International Conference on Parallel …, 2018 | 22 | 2018 |
| Job scheduling in high performance computing Y Fan arXiv preprint arXiv:2109.09269, 2021 | 21 | 2021 |
| Preliminary interference study about job placement and routing algorithms in the fat-tree topology for HPC applications P Qiao, X Wang, X Yang, Y Fan, Z Lan 2017 IEEE International Conference on Cluster Computing (CLUSTER), 641-642, 2017 | 21 | 2017 |
| DRAS-CQSim: A reinforcement learning based framework for HPC cluster scheduling Y Fan, Z Lan Software Impacts 8, 100077, 2021 | 20 | 2021 |
| System-wide trade-off modeling of performance, power, and resilience on petascale systems L Yu, Z Zhou, Y Fan, ME Papka, Z Lan The Journal of Supercomputing 74, 3168-3192, 2018 | 20 | 2018 |
| Exploiting multi-resource scheduling for HPC Y Fan, Z Lan SC Poster, 2019 | 18 | 2019 |
| ROME: A Multi-Resource Job Scheduling Framework for Exascale HPC Systems Y Fan, P Rich, WE Allcock, ME Papka, Z Lan 32nd IEEE International Parallel & Distributed Processing Symposium …, 2018 | 16 | 2018 |
| Application Checkpoint and Power Study on Large Scale Systems Y Fan arXiv preprint arXiv:2109.01943, 2021 | 11 | 2021 |
| Dras: Deep reinforcement learning for cluster scheduling in high performance computing Y Fan, B Li, D Favorite, N Singh, T Childers, P Rich, W Allcock, ME Papka, ... IEEE Transactions on Parallel and Distributed Systems 33 (12), 4903-4917, 2022 | 9 | 2022 |
| Intelligent Job Scheduling for Next Generation HPC Systems Y Fan, Z Lan, M Papka SC Doctoral Showcase, 2021 | 6 | 2021 |
| Intelligent Job Scheduling on High Performance Computing Systems Y Fan Illinois Institute of Technology, 2021 | 5 | 2021 |
| Mrsch: Multi-resource scheduling for hpc B Li, Y Fan, M Dearing, Z Lan, P Rich, W Allcock, M Papka 2022 IEEE International Conference on Cluster Computing (CLUSTER), 47-57, 2022 | 3 | 2022 |
| Encoding for reinforcement learning driven scheduling B Li, Y Fan, ME Papka, Z Lan Workshop on Job Scheduling Strategies for Parallel Processing, 68-87, 2022 | 3 | 2022 |
| Exploring Machine Learning to Adjust Job Runtime Estimate for High-Performance Computing Y Fan, P Rich, WE Allcock, ME Papka, Z Lan Greater Chicago Area System Research Workshop, Research Poster, 2017 | 3 | 2017 |
