Brian Kroth

Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud

Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur

SIGMOD | June 2024

to appear

Publication

VASIM: Vertical Autoscaling Simulator Toolkit

Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez

IEEE International Conference on Data Engineering (ICDE 2024) | May 2024

Publication

Performance Roulette: How Cloud Weather Affects ML-Based System Optimization

Brian Kroth, Konstantinos Karanasos, Shivaram Venkataraman, Johannes Freischuetz

ML for Systems Workshop at NeurIPS 2023 | December 2023

Publication

Towards Building Autonomous Data Services on Azure

Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A 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 C. 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

ACM SIGMOD | June 2023

Publication Publication

VIP Hashing — Adapting to Skew in Popularity of Data on the Fly

Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park

VLDB 2022 | June 2022

Preprint DOI

Data Science Through the Looking Glass

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | June 2022, Vol 51(2): pp. 30-37

Publication DOI

LlamaTune: Sample-Efficient DBMS Configuration Tuning

Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman

VLDB 2022 | March 2022

Preprint DOI

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | March 2022

Publication

Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS

Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do

2020 Data Management on New Hardware | June 2020

Publication Publication

MLOS: An Infrastructure for Automated Software Performance Engineering

Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

DEEM 2020 | June 2020

Publication

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

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

Conference on Innovative Data Systems Research (CIDR) | January 2020

PDF

Optimizing databases by learning hidden parameters of solid state drives

Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth

Proceedings of VLDB | December 2019

Publication DOI PDF Publication

Performance Roulette: How Cloud Weather Affects ML-Based System Optimization

Brian Kroth, Konstantinos Karanasos, Shivaram Venkataraman, Johannes Freischuetz

ML for Systems Workshop at NeurIPS 2023 | December 2023

Publication

Towards Building Autonomous Data Services on Azure

Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A 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 C. 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

ACM SIGMOD | June 2023

Publication Publication

Data Science Through the Looking Glass

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | June 2022, Vol 51(2): pp. 30-37

Publication DOI

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | March 2022

Publication

MLOS: An Infrastructure for Automated Software Performance Engineering

Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

DEEM 2020 | June 2020

Publication

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

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

Conference on Innovative Data Systems Research (CIDR) | January 2020

PDF

Performance Roulette: How Cloud Weather Affects ML-Based System Optimization

Brian Kroth, Konstantinos Karanasos, Shivaram Venkataraman, Johannes Freischuetz

ML for Systems Workshop at NeurIPS 2023 | December 2023

Publication

Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS

Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do

2020 Data Management on New Hardware | June 2020

Publication Publication

Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud

Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur

SIGMOD | June 2024

to appear

Publication

VASIM: Vertical Autoscaling Simulator Toolkit

Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez

IEEE International Conference on Data Engineering (ICDE 2024) | May 2024

Publication

Towards Building Autonomous Data Services on Azure

Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A 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 C. 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

ACM SIGMOD | June 2023

Publication Publication

VIP Hashing — Adapting to Skew in Popularity of Data on the Fly

Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park

VLDB 2022 | June 2022

Preprint DOI

Data Science Through the Looking Glass

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | June 2022, Vol 51(2): pp. 30-37

Publication DOI

LlamaTune: Sample-Efficient DBMS Configuration Tuning

Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman

VLDB 2022 | March 2022

Preprint DOI

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | March 2022

Publication

Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS

Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do

2020 Data Management on New Hardware | June 2020

Publication Publication

MLOS: An Infrastructure for Automated Software Performance Engineering

Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

DEEM 2020 | June 2020

Publication

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

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

Conference on Innovative Data Systems Research (CIDR) | January 2020

PDF

Optimizing databases by learning hidden parameters of solid state drives

Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth

Proceedings of VLDB | December 2019

Publication DOI PDF Publication

VASIM: Vertical Autoscaling Simulator Toolkit

Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez

IEEE International Conference on Data Engineering (ICDE 2024) | May 2024

Publication

Data Science Through the Looking Glass

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | June 2022, Vol 51(2): pp. 30-37

Publication DOI

MLOS: An Infrastructure for Automated Software Performance Engineering

Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

DEEM 2020 | June 2020

Publication

Optimizing databases by learning hidden parameters of solid state drives

Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth

Proceedings of VLDB | December 2019

Publication DOI PDF Publication

Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud

Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jesús Camacho-Rodríguez, Karla Saur

SIGMOD | June 2024

to appear

Publication

VASIM: Vertical Autoscaling Simulator Toolkit

Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jesús Camacho-Rodríguez

IEEE International Conference on Data Engineering (ICDE 2024) | May 2024

Publication

Performance Roulette: How Cloud Weather Affects ML-Based System Optimization

Brian Kroth, Konstantinos Karanasos, Shivaram Venkataraman, Johannes Freischuetz

ML for Systems Workshop at NeurIPS 2023 | December 2023

Publication

Towards Building Autonomous Data Services on Azure

Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin A 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 C. 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

ACM SIGMOD | June 2023

Publication Publication

VIP Hashing — Adapting to Skew in Popularity of Data on the Fly

Aarati Kakaraparthy, Jignesh M. Patel, Brian Kroth, Kwanghyun Park

VLDB 2022 | June 2022

Preprint DOI

LlamaTune: Sample-Efficient DBMS Configuration Tuning

Konstantinos Kanellis, Cong Ding, Brian Kroth, Andreas C. Müller, Carlo Curino, Shivaram Venkataraman

VLDB 2022 | March 2022

Preprint DOI

Lessons learned from the early performance evaluation of Intel Optane DC persistent memory in DBMS

Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jae Young Do

2020 Data Management on New Hardware | June 2020

Publication Publication

MLOS: An Infrastructure for Automated Software Performance Engineering

Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu

DEEM 2020 | June 2020

Publication

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

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

Conference on Innovative Data Systems Research (CIDR) | January 2020

PDF

Optimizing databases by learning hidden parameters of solid state drives

Aarati Kakaraparthy, Jignesh M. Patel, Kwanghyun Park, Brian Kroth

Proceedings of VLDB | December 2019

Publication DOI PDF Publication

Data Science Through the Looking Glass

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | June 2022, Vol 51(2): pp. 30-37

Publication DOI

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines

Fotis Psallidas, Yiwen Zhu, Bojan Karlaš, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos

SIGMOD Record | March 2022

Publication