| Multi-core real-time scheduling for generalized parallel task models A Saifullah, J Li, K Agrawal, C Lu, C Gill Real-Time Systems (RTS) 49 (4), 404-435, 2013 | 436 | 2013 |
| Analysis of federated and global scheduling for parallel real-time tasks J Li, JJ Chen, K Agrawal, C Lu, C Gill, A Saifullah The 26th Euromicro Conference on Real-Time Systems (ECRTS), 85-96, 2014 | 302 | 2014 |
| Parallel real-time scheduling of DAGs A Saifullah, D Ferry, J Li, K Agrawal, C Lu, CD Gill IEEE Transactions on Parallel and Distributed Systems (TPDS) 25 (12), 3242-3252, 2014 | 230 | 2014 |
| Analysis of global edf for parallel tasks J Li, K Agrawal, C Lu, C Gill The 25th Euromicro Conference on Real-Time Systems (ECRTS), 3-13, 2013 | 179* | 2013 |
| Mixed-criticality federated scheduling for parallel real-time tasks J Li, D Ferry, S Ahuja, K Agrawal, C Gill, C Lu Real-Time Systems (RTS) 53 (5), 760-811, 2017 | 88 | 2017 |
| A real-time scheduling service for parallel tasks D Ferry, J Li, M Mahadevan, K Agrawal, C Gill, C Lu The 19th IEEE Real-Time and Embedded Technology and Applications Symposium …, 2013 | 82 | 2013 |
| Global EDF scheduling for parallel real-time tasks J Li, Z Luo, D Ferry, K Agrawal, C Gill, C Lu Real-Time Systems (RTS) 51 (4), 395-439, 2015 | 72 | 2015 |
| Machine Learning in Real-Time Internet of Things (IoT) Systems: A Survey J Bian, A Al Arafat, H Xiong, J Li, L Li, H Chen, J Wang, D Dou, Z Guo IEEE Internet of Things Journal 9 (11), 8364-8386, 2022 | 69 | 2022 |
| Work stealing for interactive services to meet target latency J Li, K Agrawal, S Elnikety, Y He, I Lee, C Lu, KS McKinley The 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel …, 2016 | 66 | 2016 |
| Reservation-based federated scheduling for parallel real-time tasks N Ueter, G von der Brüggen, JJ Chen, J Li, K Agrawal IEEE Real-Time Systems Symposium (RTSS), 482-494, 2018 | 52 | 2018 |
| Scheduling parallel DAG jobs online to minimize average flow time K Agrawal, J Li, K Lu, B Moseley The 27th ACM-SIAM Symposium on Discrete Algorithms (SODA), 176-189, 2016 | 46 | 2016 |
| SafeLight: A Reinforcement Learning Method toward Collision-free Traffic Signal Control W Du, J Ye, J Gu, J Li, H Wei, G Wang The 37th AAAI Conference on Artificial Intelligence (AAAI), 2023 | 35 | 2023 |
| Tvshowguess: Character comprehension in stories as speaker guessing Y Sang, X Mou, M Yu, S Yao, J Li, J Stanton Conference of the North American Chapter of the Association for …, 2022 | 33 | 2022 |
| Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning X Ni, J Li, M Yu, W Zhou, KL Wu The 34th AAAI Conference on Artificial Intelligence (AAAI) 34 (01), 857-864, 2020 | 32 | 2020 |
| Blocking Analysis for Spin Locks in Real-Time Parallel Tasks S Dinh, J Li, K Agrawal, C Gill, C Lu IEEE Transactions on Parallel and Distributed Systems (TPDS) 29 (4), 789-802, 2018 | 29 | 2018 |
| Randomized work stealing for large scale soft real-time systems J Li, S Dinh, K Kieselbach, K Agrawal, C Gill, C Lu IEEE Real-Time Systems Symposium (RTSS), 203-214, 2016 | 29 | 2016 |
| Can large language models play text games well? current state-of-the-art and open questions CF Tsai, X Zhou, SS Liu, J Li, M Yu, H Mei arXiv preprint arXiv:2304.02868, 2023 | 28 | 2023 |
| RTGPU: Real-time GPU scheduling of hard deadline parallel tasks with fine-grain utilization A Zou, J Li, CD Gill, X Zhang IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023 | 26 | 2023 |
| Federated scheduling for stochastic parallel real-time tasks J Li, K Agrawal, C Gill, C Lu The 20th IEEE International Conference on Embedded and Real-Time Computing …, 2014 | 23 | 2014 |
| Scheduling Parallelizable Jobs Online to Minimize the Maximum Flow Time K Agrawal, J Li, K Lu, B Moseley The 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA …, 2016 | 20 | 2016 |
Kunal AgrawalAssociate Professor of Computer Science and Engineering, Washington University in St Louiswustl.edu의 이메일 확인됨