| From {WiscKey} to bourbon: A learned index for {Log-Structured} merge trees Y Dai, Y Xu, A Ganesan, R Alagappan, B Kroth, A Arpaci-Dusseau, ... 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 127 | 2020 |
| Data science through the looking glass: Analysis of millions of github notebooks and ml. net pipelines F Psallidas, Y Zhu, B Karlas, J Henkel, M Interlandi, S Krishnan, B Kroth, ... ACM SIGMOD Record 51 (2), 30-37, 2022 | 67 | 2022 |
| LlamaTune: sample-efficient DBMS configuration tuning K Kanellis, C Ding, B Kroth, A Müller, C Curino, S Venkataraman arXiv preprint arXiv:2203.05128, 2022 | 51 | 2022 |
| Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS Y Wu, K Park, R Sen, B Kroth, J Do Proceedings of the 16th International Workshop on Data Management on New …, 2020 | 45 | 2020 |
| Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML A Agrawal, R Chatterjee, C Curino, A Floratou, N Gowdal, M Interlandi, ... arXiv preprint arXiv:1909.00084, 2019 | 39 | 2019 |
| Optimizing databases by learning hidden parameters of solid state drives A Kakaraparthy, JM Patel, K Park, BP Kroth Proceedings of the VLDB Endowment 13 (4), 519-532, 2019 | 12 | 2019 |
| VIP hashing: adapting to skew in popularity of data on the fly A Kakaraparthy, JM Patel, BP Kroth, K Park Proceedings of the VLDB Endowment 15 (10), 1978-1990, 2022 | 8 | 2022 |
| MLOS: An infrastructure for automated software performance engineering C Curino, N Godwal, B Kroth, S Kuryata, G Lapinski, S Liu, S Oks, ... Proceedings of the Fourth International Workshop on Data Management for End …, 2020 | 8 | 2020 |
| Thayer, et al. 2020. MLOS: An infrastructure for automated software performance engineering C Curino, N Godwal, B Kroth, S Kuryata, G Lapinski, S Liu, S Oks, ... Proceedings of the Fourth International Workshop on Data Management for End …, 0 | 7 | |
| Notebook for navigating code using machine learning and flow analysis BP Kroth, JJ Henkel US Patent 11,816,456, 2023 | 6 | 2023 |
| Towards building autonomous data services on azure Y Zhu, Y Tian, J Cahoon, S Krishnan, A Agarwal, R Alotaibi, ... Companion of the 2023 International Conference on Management of Data, 217-224, 2023 | 5 | 2023 |
| Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud A Pavlenko, J Cahoon, Y Zhu, B Kroth, M Nelson, A Carter, D Liao, ... Companion of the 2024 International Conference on Management of Data, 241-254, 2024 | 3 | 2024 |
| MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud B Kroth, S Matusevych, R Alotaibi, Y Zhu, A Gruenheid, Y Tian Proceedings of the VLDB Endowment 17 (12), 4269-4272, 2024 | 2 | 2024 |
| Performance Roulette: How Cloud Weather Affects ML-Based System Optimization J Freischuetz, K Kanellis, B Kroth, S Venkataraman ML for Systems Workshop at NeurIPS, 2023 | 2 | 2023 |
| VASIM: Vertical Autoscaling Simulator Toolkit A Pavlenko, K Saur, Y Zhu, B Kroth, J Cahoon, J Camacho-Rodríguez 2024 IEEE 40th International Conference on Data Engineering (ICDE), 5413-5416, 2024 | 1 | 2024 |
| VIP Hashing--Adapting to Skew in Popularity of Data on the Fly (extended version) A Kakaraparthy, JM Patel, BP Kroth, K Park arXiv preprint arXiv:2206.12380, 2022 | 1 | 2022 |
| CS764 Project Report: Adventures in Moodle Performance Analysis B Kroth | 1 | 2014 |
| Checksumming RAID B Kroth, S Yang unpublished, 2010 | 1 | 2010 |
| VERTICAL SCALING OF COMPUTE CONTAINERS KJ Saur, JY Cahoon, Y Zhu, A Pavlenko, J Camacho Rodriguez, BP Kroth, ... US Patent App. 18/472,947, 2024 | | 2024 |
| Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? R Alotaibi, Y Tian, S Grafberger, J Camacho-Rodríguez, N Bruno, B Kroth, ... arXiv preprint arXiv:2411.13704, 2024 | | 2024 |