Rathijit Sen

Principal Scientist

出版物

表示方法:

- Terabyte-Scale Analytics in the Blink of an Eye
  
  Bowen Wu, Wei Cui, Carlo Curino, Matteo Interlandi, Rathijit Sen
  
  VLDB 2026 | January 2026
  
  DOI Publication Publication
- Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries
  
  Hyunjoon Kim, Chaerim Lim, Hyeonjun An, Rathijit Sen, Kwanghyun Park
  
  December 2025
  
  Publication
- Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
  
  Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
  
  Companion of the 2025 International Conference on Management of Data | June 2025
  
  DOI Publication
- Optimizing Data Pipelines for Machine Learning in Feature Stores
  
  Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
  
  Proc. VLDB Endow. | August 2023, 巻16: pp. 4230-4239
  
  DOI PDF
- Query Processing on Gaming Consoles
  
  Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
  
  June 2023
  
  DOI 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
- Runtime Variation in Big Data Analytics
  
  Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
  
  ACM SIGMOD | May 2023
  
  Publication
- The Tensor Data Platform: Towards an AI-centric Database System
  
  Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
  
  CIDR | January 2023
  
  Publication
- Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
  
  Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
  
  VLDB | September 2022, 巻15(12): pp. 3598-3601
  
  Best demo award
  
  Publication
- Query Processing on Tensor Computation Runtimes
  
  Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
  
  VLDB 2022 | September 2022
  
  Publication
- End-to-end Optimization of Machine Learning Prediction Queries
  
  Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
  
  SIGMOD | June 2022
  
  Publication
- NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
  
  Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  20th USENIX Conference on File and Storage Technologies | February 2022
  
  Publication
- AutoExecutor: Predictive Parallelism for Spark SQL Queries
  
  Rathijit Sen, Abhishek Roy, Alekh Jindal, Rui Fang, Jeff Zheng, Xiaolei Liu, Ruiping Li
  
  VLDB | August 2021
  
  Best Demonstration Award
  
  Publication
- Optimal Resource Allocation for Serverless Queries
  
  Anish Pimpley, Shuo Li, Anubha Srivastava, Vishal Rohra, Yi Zhu, Soundararajan Srinivasan, Alekh Jindal, Hiren Patel, Shi Qiao, Rathijit Sen
  
  July 2021
  
  Publication
- Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
  
  Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
  
  2021 International Conference on Data Engineering | April 2021
  
  DOI Publication Publication プロジェクト
- FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
  
  Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
  
  International Conference on Data Engineering (ICDE) | April 2021
  
  Publication
- Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
  
  Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- Performance Characterization of .NET Benchmarks
  
  Aniket Deshmukh, Ruihao Li, Rathijit Sen, Robert R, Henry, Monica Beckwith, Gagan Gupta
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
  
  Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  19th USENIX Conference on File and Storage Technologies | February 2021
  
  PDF Publication
- AutoToken: predicting peak parallelism for big data analytics at Microsoft
  
  Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
  
  Very Large Data Bases | July 2020
  
  DOI PDF Publication プロジェクトプロジェクト
- 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
- Automated Tuning of Query Degree of Parallelism via Machine Learning
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  2020 International Conference on Management of Data | June 2020
  
  Publication
- A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  May 2020
  
  PDF 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
- Extending Relational Query Processing with ML Inference
  
  Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
  
  Conference on Innovative Data Systems Research (CIDR) | January 2020
  
  Publication
- Peregrine: Workload Optimization for Cloud Query Engines
  
  Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
  
  Symposium on Cloud Computing | November 2019
  
  DOI Publication プロジェクト
- Exploiting Intel Optane SSD for Microsoft SQL Server
  
  Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
  
  DaMoN 2019 | July 2019
  
  Publication
- Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
  
  Hossein Golestani, Gagan Gupta, Rathijit Sen
  
  IEEE Computer Architecture Letters | April 2019, 巻18(1): pp. 79-82
  
  Publication
- Characterizing Resource Sensitivity of Database Workloads
  
  Rathijit Sen, Karthik Ramachandra
  
  High-Performance Computer Architecture | January 2018
  
  Publication
- Energy-Proportional Computing: A New Definition
  
  Rathijit Sen, David A. Wood
  
  IEEE Computer | July 2017, 巻50(8): pp. 26-33
  
  Publication
- Frequency governors for cloud database OLTP workloads
  
  Rathijit Sen, Alan Halverson
  
  International Symposium on Low Power Electronics and Design | July 2017
  
  Publication
- ROSA: R Optimizations with Static Analysis
  
  Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
  
  RIOT 2017 | July 2017
  
  PDF Publication
- Pareto Governors for Energy-Optimal Computing
  
  Rathijit Sen, David A. Wood
  
  ACM Transactions on Architecture and Code Optimization | April 2017, 巻14(1): pp. 6
  
  Publication

- Terabyte-Scale Analytics in the Blink of an Eye
  
  Bowen Wu, Wei Cui, Carlo Curino, Matteo Interlandi, Rathijit Sen
  
  VLDB 2026 | January 2026
  
  DOI Publication Publication
- NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
  
  Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  20th USENIX Conference on File and Storage Technologies | February 2022
  
  Publication
- The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
  
  Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  19th USENIX Conference on File and Storage Technologies | February 2021
  
  PDF 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
- Exploiting Intel Optane SSD for Microsoft SQL Server
  
  Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
  
  DaMoN 2019 | July 2019
  
  Publication
- Characterizing Resource Sensitivity of Database Workloads
  
  Rathijit Sen, Karthik Ramachandra
  
  High-Performance Computer Architecture | January 2018
  
  Publication
- Energy-Proportional Computing: A New Definition
  
  Rathijit Sen, David A. Wood
  
  IEEE Computer | July 2017, 巻50(8): pp. 26-33
  
  Publication
- Frequency governors for cloud database OLTP workloads
  
  Rathijit Sen, Alan Halverson
  
  International Symposium on Low Power Electronics and Design | July 2017
  
  Publication
- Pareto Governors for Energy-Optimal Computing
  
  Rathijit Sen, David A. Wood
  
  ACM Transactions on Architecture and Code Optimization | April 2017, 巻14(1): pp. 6
  
  Publication
- Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries
  
  Hyunjoon Kim, Chaerim Lim, Hyeonjun An, Rathijit Sen, Kwanghyun Park
  
  December 2025
  
  Publication
- Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
  
  Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
  
  Companion of the 2025 International Conference on Management of Data | June 2025
  
  DOI 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
- Runtime Variation in Big Data Analytics
  
  Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
  
  ACM SIGMOD | May 2023
  
  Publication
- The Tensor Data Platform: Towards an AI-centric Database System
  
  Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
  
  CIDR | January 2023
  
  Publication
- Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
  
  Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
  
  VLDB | September 2022, 巻15(12): pp. 3598-3601
  
  Best demo award
  
  Publication
- Query Processing on Tensor Computation Runtimes
  
  Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
  
  VLDB 2022 | September 2022
  
  Publication
- End-to-end Optimization of Machine Learning Prediction Queries
  
  Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
  
  SIGMOD | June 2022
  
  Publication
- AutoToken: predicting peak parallelism for big data analytics at Microsoft
  
  Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
  
  Very Large Data Bases | July 2020
  
  DOI PDF Publication プロジェクトプロジェクト
- Automated Tuning of Query Degree of Parallelism via Machine Learning
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  2020 International Conference on Management of Data | June 2020
  
  Publication
- A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  May 2020
  
  PDF 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
- Extending Relational Query Processing with ML Inference
  
  Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
  
  Conference on Innovative Data Systems Research (CIDR) | January 2020
  
  Publication
- Peregrine: Workload Optimization for Cloud Query Engines
  
  Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
  
  Symposium on Cloud Computing | November 2019
  
  DOI Publication プロジェクト
- Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
  
  Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
  
  Companion of the 2025 International Conference on Management of Data | June 2025
  
  DOI Publication
- Optimizing Data Pipelines for Machine Learning in Feature Stores
  
  Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
  
  Proc. VLDB Endow. | August 2023, 巻16: pp. 4230-4239
  
  DOI PDF
- Query Processing on Gaming Consoles
  
  Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
  
  June 2023
  
  DOI 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
- Runtime Variation in Big Data Analytics
  
  Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
  
  ACM SIGMOD | May 2023
  
  Publication
- The Tensor Data Platform: Towards an AI-centric Database System
  
  Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
  
  CIDR | January 2023
  
  Publication
- Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
  
  Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
  
  VLDB | September 2022, 巻15(12): pp. 3598-3601
  
  Best demo award
  
  Publication
- Query Processing on Tensor Computation Runtimes
  
  Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
  
  VLDB 2022 | September 2022
  
  Publication
- End-to-end Optimization of Machine Learning Prediction Queries
  
  Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
  
  SIGMOD | June 2022
  
  Publication
- AutoExecutor: Predictive Parallelism for Spark SQL Queries
  
  Rathijit Sen, Abhishek Roy, Alekh Jindal, Rui Fang, Jeff Zheng, Xiaolei Liu, Ruiping Li
  
  VLDB | August 2021
  
  Best Demonstration Award
  
  Publication
- Optimal Resource Allocation for Serverless Queries
  
  Anish Pimpley, Shuo Li, Anubha Srivastava, Vishal Rohra, Yi Zhu, Soundararajan Srinivasan, Alekh Jindal, Hiren Patel, Shi Qiao, Rathijit Sen
  
  July 2021
  
  Publication
- Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
  
  Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
  
  2021 International Conference on Data Engineering | April 2021
  
  DOI Publication Publication プロジェクト
- FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
  
  Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
  
  International Conference on Data Engineering (ICDE) | April 2021
  
  Publication
- Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
  
  Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- AutoToken: predicting peak parallelism for big data analytics at Microsoft
  
  Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
  
  Very Large Data Bases | July 2020
  
  DOI PDF Publication プロジェクトプロジェクト
- 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
- Automated Tuning of Query Degree of Parallelism via Machine Learning
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  2020 International Conference on Management of Data | June 2020
  
  Publication
- A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  May 2020
  
  PDF 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
- Extending Relational Query Processing with ML Inference
  
  Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
  
  Conference on Innovative Data Systems Research (CIDR) | January 2020
  
  Publication
- Peregrine: Workload Optimization for Cloud Query Engines
  
  Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
  
  Symposium on Cloud Computing | November 2019
  
  DOI Publication プロジェクト
- Exploiting Intel Optane SSD for Microsoft SQL Server
  
  Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
  
  DaMoN 2019 | July 2019
  
  Publication
- Characterizing Resource Sensitivity of Database Workloads
  
  Rathijit Sen, Karthik Ramachandra
  
  High-Performance Computer Architecture | January 2018
  
  Publication
- Frequency governors for cloud database OLTP workloads
  
  Rathijit Sen, Alan Halverson
  
  International Symposium on Low Power Electronics and Design | July 2017
  
  Publication
- ROSA: R Optimizations with Static Analysis
  
  Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
  
  RIOT 2017 | July 2017
  
  PDF Publication
- Pareto Governors for Energy-Optimal Computing
  
  Rathijit Sen, David A. Wood
  
  ACM Transactions on Architecture and Code Optimization | April 2017, 巻14(1): pp. 6
  
  Publication
- FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
  
  Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
  
  International Conference on Data Engineering (ICDE) | April 2021
  
  Publication
- Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
  
  Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- Performance Characterization of .NET Benchmarks
  
  Aniket Deshmukh, Ruihao Li, Rathijit Sen, Robert R, Henry, Monica Beckwith, Gagan Gupta
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
  
  Hossein Golestani, Gagan Gupta, Rathijit Sen
  
  IEEE Computer Architecture Letters | April 2019, 巻18(1): pp. 79-82
  
  Publication
- Performance Characterization of .NET Benchmarks
  
  Aniket Deshmukh, Ruihao Li, Rathijit Sen, Robert R, Henry, Monica Beckwith, Gagan Gupta
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- ROSA: R Optimizations with Static Analysis
  
  Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
  
  RIOT 2017 | July 2017
  
  PDF Publication
- Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
  
  Hossein Golestani, Gagan Gupta, Rathijit Sen
  
  IEEE Computer Architecture Letters | April 2019, 巻18(1): pp. 79-82
  
  Publication

- Terabyte-Scale Analytics in the Blink of an Eye
  
  Bowen Wu, Wei Cui, Carlo Curino, Matteo Interlandi, Rathijit Sen
  
  VLDB 2026 | January 2026
  
  DOI Publication Publication
- Query Processing on Gaming Consoles
  
  Wei Cui, Qianxi Zhang, Jesús Camacho-Rodríguez, Spyros Blanas, Brandon Haynes, Yinan Li, Peng Cheng, Ravishankar Ramamurthy, Rathijit Sen, Matteo Interlandi
  
  June 2023
  
  DOI 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
- Runtime Variation in Big Data Analytics
  
  Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
  
  ACM SIGMOD | May 2023
  
  Publication
- The Tensor Data Platform: Towards an AI-centric Database System
  
  Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
  
  CIDR | January 2023
  
  Publication
- Query Processing on Tensor Computation Runtimes
  
  Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
  
  VLDB 2022 | September 2022
  
  Publication
- End-to-end Optimization of Machine Learning Prediction Queries
  
  Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
  
  SIGMOD | June 2022
  
  Publication
- NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
  
  Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  20th USENIX Conference on File and Storage Technologies | February 2022
  
  Publication
- AutoExecutor: Predictive Parallelism for Spark SQL Queries
  
  Rathijit Sen, Abhishek Roy, Alekh Jindal, Rui Fang, Jeff Zheng, Xiaolei Liu, Ruiping Li
  
  VLDB | August 2021
  
  Best Demonstration Award
  
  Publication
- Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
  
  Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
  
  2021 International Conference on Data Engineering | April 2021
  
  DOI Publication Publication プロジェクト
- FPGA for Aggregate Processing: The Good, The Bad, and The Ugly
  
  Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
  
  International Conference on Data Engineering (ICDE) | April 2021
  
  Publication
- Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
  
  Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- Performance Characterization of .NET Benchmarks
  
  Aniket Deshmukh, Ruihao Li, Rathijit Sen, Robert R, Henry, Monica Beckwith, Gagan Gupta
  
  International Symposium on Performance Analysis of Systems and Software (ISPASS) | March 2021
  
  Publication
- The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus
  
  Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
  
  19th USENIX Conference on File and Storage Technologies | February 2021
  
  PDF Publication
- AutoToken: predicting peak parallelism for big data analytics at Microsoft
  
  Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
  
  Very Large Data Bases | July 2020
  
  DOI PDF Publication プロジェクトプロジェクト
- 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
- Automated Tuning of Query Degree of Parallelism via Machine Learning
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  2020 International Conference on Management of Data | 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
- Extending Relational Query Processing with ML Inference
  
  Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
  
  Conference on Innovative Data Systems Research (CIDR) | January 2020
  
  Publication
- Peregrine: Workload Optimization for Cloud Query Engines
  
  Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
  
  Symposium on Cloud Computing | November 2019
  
  DOI Publication プロジェクト
- Exploiting Intel Optane SSD for Microsoft SQL Server
  
  Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
  
  DaMoN 2019 | July 2019
  
  Publication
- Characterizing Resource Sensitivity of Database Workloads
  
  Rathijit Sen, Karthik Ramachandra
  
  High-Performance Computer Architecture | January 2018
  
  Publication
- Frequency governors for cloud database OLTP workloads
  
  Rathijit Sen, Alan Halverson
  
  International Symposium on Low Power Electronics and Design | July 2017
  
  Publication
- ROSA: R Optimizations with Static Analysis
  
  Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
  
  RIOT 2017 | July 2017
  
  PDF Publication
- Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries
  
  Hyunjoon Kim, Chaerim Lim, Hyeonjun An, Rathijit Sen, Kwanghyun Park
  
  December 2025
  
  Publication
- Optimal Resource Allocation for Serverless Queries
  
  Anish Pimpley, Shuo Li, Anubha Srivastava, Vishal Rohra, Yi Zhu, Soundararajan Srinivasan, Alekh Jindal, Hiren Patel, Shi Qiao, Rathijit Sen
  
  July 2021
  
  Publication
- Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment
  
  Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan
  
  Companion of the 2025 International Conference on Management of Data | June 2025
  
  DOI Publication
- Optimizing Data Pipelines for Machine Learning in Feature Stores
  
  Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
  
  Proc. VLDB Endow. | August 2023, 巻16: pp. 4230-4239
  
  DOI PDF
- Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
  
  Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
  
  VLDB | September 2022, 巻15(12): pp. 3598-3601
  
  Best demo award
  
  Publication
- Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
  
  Hossein Golestani, Gagan Gupta, Rathijit Sen
  
  IEEE Computer Architecture Letters | April 2019, 巻18(1): pp. 79-82
  
  Publication
- Energy-Proportional Computing: A New Definition
  
  Rathijit Sen, David A. Wood
  
  IEEE Computer | July 2017, 巻50(8): pp. 26-33
  
  Publication
- Pareto Governors for Energy-Optimal Computing
  
  Rathijit Sen, David A. Wood
  
  ACM Transactions on Architecture and Code Optimization | April 2017, 巻14(1): pp. 6
  
  Publication
- A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
  
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
  
  May 2020
  
  PDF Publication

Rathijit Sen

出版物

Terabyte-Scale Analytics in the Blink of an Eye

Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries

Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment

Optimizing Data Pipelines for Machine Learning in Feature Stores

Query Processing on Gaming Consoles

Towards Building Autonomous Data Services on Azure

Runtime Variation in Big Data Analytics

The Tensor Data Platform: Towards an AI-centric Database System

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

Query Processing on Tensor Computation Runtimes

End-to-end Optimization of Machine Learning Prediction Queries

NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching

AutoExecutor: Predictive Parallelism for Spark SQL Queries

Optimal Resource Allocation for Serverless Queries

Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft

FPGA for Aggregate Processing: The Good, The Bad, and The Ugly

Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?

Performance Characterization of .NET Benchmarks

The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus

AutoToken: predicting peak parallelism for big data analytics at Microsoft

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

Automated Tuning of Query Degree of Parallelism via Machine Learning

A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.

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

Extending Relational Query Processing with ML Inference

Peregrine: Workload Optimization for Cloud Query Engines

Exploiting Intel Optane SSD for Microsoft SQL Server

Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs

Characterizing Resource Sensitivity of Database Workloads

Energy-Proportional Computing: A New Definition

Frequency governors for cloud database OLTP workloads

ROSA: R Optimizations with Static Analysis

Pareto Governors for Energy-Optimal Computing

Terabyte-Scale Analytics in the Blink of an Eye

NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching

The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus

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

Exploiting Intel Optane SSD for Microsoft SQL Server

Characterizing Resource Sensitivity of Database Workloads

Energy-Proportional Computing: A New Definition

Frequency governors for cloud database OLTP workloads

Pareto Governors for Energy-Optimal Computing

Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries

Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment

Towards Building Autonomous Data Services on Azure

Runtime Variation in Big Data Analytics

The Tensor Data Platform: Towards an AI-centric Database System

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

Query Processing on Tensor Computation Runtimes

End-to-end Optimization of Machine Learning Prediction Queries

AutoToken: predicting peak parallelism for big data analytics at Microsoft

Automated Tuning of Query Degree of Parallelism via Machine Learning

A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.

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

Extending Relational Query Processing with ML Inference

Peregrine: Workload Optimization for Cloud Query Engines

Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment

Optimizing Data Pipelines for Machine Learning in Feature Stores

Query Processing on Gaming Consoles

Towards Building Autonomous Data Services on Azure

Runtime Variation in Big Data Analytics

The Tensor Data Platform: Towards an AI-centric Database System

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

Query Processing on Tensor Computation Runtimes

End-to-end Optimization of Machine Learning Prediction Queries

AutoExecutor: Predictive Parallelism for Spark SQL Queries

Optimal Resource Allocation for Serverless Queries

Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft

FPGA for Aggregate Processing: The Good, The Bad, and The Ugly

Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?

AutoToken: predicting peak parallelism for big data analytics at Microsoft

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

Automated Tuning of Query Degree of Parallelism via Machine Learning

A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.

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

Extending Relational Query Processing with ML Inference

Peregrine: Workload Optimization for Cloud Query Engines

Exploiting Intel Optane SSD for Microsoft SQL Server