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Brian Kroth
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2020 – today
- 2024
- [j5]Brian Kroth, Sergiy Matusevych, Rana Alotaibi, Yiwen Zhu, Anja Gruenheid, Yuanyuan Tian:
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud. Proc. VLDB Endow. 17(12): 4269-4272 (2024) - [c7]Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez:
VASIM: Vertical Autoscaling Simulator Toolkit. ICDE 2024: 5413-5416 - [c6]Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur:
Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud. SIGMOD Conference Companion 2024: 241-254 - [i7]Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan:
Towards Building Autonomous Data Services on Azure. CoRR abs/2405.01813 (2024) - 2023
- [c5]Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan:
Towards Building Autonomous Data Services on Azure. SIGMOD Conference Companion 2023: 217-224 - 2022
- [j4]Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park:
VIP Hashing - Adapting to Skew in Popularity of Data on the Fly. Proc. VLDB Endow. 15(10): 1978-1990 (2022) - [j3]Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas Müller, Carlo Curino, Shivaram Venkataraman:
LlamaTune: Sample-Efficient DBMS Configuration Tuning. Proc. VLDB Endow. 15(11): 2953-2965 (2022) - [j2]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos:
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. 51(2): 30-37 (2022) - [i6]Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas Müller, Carlo Curino, Shivaram Venkataraman:
LlamaTune: Sample-Efficient DBMS Configuration Tuning. CoRR abs/2203.05128 (2022) - [i5]Aarati Kakaraparthy, Jignesh M. Patel, Brian P. Kroth, Kwanghyun Park:
VIP Hashing - Adapting to Skew in Popularity of Data on the Fly (extended version). CoRR abs/2206.12380 (2022) - 2020
- [c4]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. CIDR 2020 - [c3]Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jaeyoung Do:
Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS. DaMoN 2020: 14:1-14:3 - [c2]Yifan Dai, Yien Xu, Aishwarya Ganesan, Ramnatthan Alagappan, Brian Kroth, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau:
From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees. OSDI 2020: 155-171 - [c1]Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu:
MLOS: An Infrastructure for Automated Software Performance Engineering. DEEM@SIGMOD 2020: 3:1-3:5 - [i4]Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jaeyoung Do:
Lessons learned from the early performance evaluation of Intel Optane DC Persistent Memory in DBMS. CoRR abs/2005.07658 (2020) - [i3]Yifan Dai, Yien Xu, Aishwarya Ganesan, Ramnatthan Alagappan, Brian Kroth, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau:
Learning How To Learn Within An LSM-based Key-Value Store. CoRR abs/2005.14213 (2020) - [i2]Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu:
MLOS: An Infrastructure for Automated Software Performance Engineering. CoRR abs/2006.02155 (2020)
2010 – 2019
- 2019
- [j1]Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth:
Optimizing Databases by Learning Hidden Parameters of Solid State Drives. Proc. VLDB Endow. 13(4): 519-532 (2019) - [i1]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR abs/1909.00084 (2019)
Coauthor Index
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