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
Rathijit Sen
Senior Scientist
Publications
Publications by Year
-
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
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
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
-
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, Vol 15(12): pp. 3598-3601
Best demo award
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
End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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
-
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
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
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
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
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
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
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
-
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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
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
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
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
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
-
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
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
Hossein Golestani, Gagan Gupta, Rathijit Sen
IEEE Computer Architecture Letters | April 2019, Vol 18(1): pp. 79-82
-
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
-
Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, Vol 50(8): pp. 26-33
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, Vol 14(1): pp. 6
Publications by Research Area
-
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
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
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
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
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, Vol 15(12): pp. 3598-3601
Best demo award
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
End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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
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
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
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
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
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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
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
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
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
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
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
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, Vol 14(1): pp. 6
-
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
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
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
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, Vol 15(12): pp. 3598-3601
Best demo award
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
End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020
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
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
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
-
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
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
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
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, Vol 50(8): pp. 26-33
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, Vol 14(1): pp. 6
-
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
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
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
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
Hossein Golestani, Gagan Gupta, Rathijit Sen
IEEE Computer Architecture Letters | April 2019, Vol 18(1): pp. 79-82
-
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
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
-
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
Hossein Golestani, Gagan Gupta, Rathijit Sen
IEEE Computer Architecture Letters | April 2019, Vol 18(1): pp. 79-82
Publications by Type
-
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
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
Runtime Variation in Big Data Analytics
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
ACM SIGMOD | May 2023
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
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
End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
SIGMOD | June 2022
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
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
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
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
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
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
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
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
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
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
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
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
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
Exploiting Intel Optane SSD for Microsoft SQL Server
Kan Wu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
DaMoN 2019 | July 2019
Characterizing Resource Sensitivity of Database Workloads
Rathijit Sen, Karthik Ramachandra
High-Performance Computer Architecture | January 2018
Frequency governors for cloud database OLTP workloads
Rathijit Sen, Alan Halverson
International Symposium on Low Power Electronics and Design | July 2017
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
RIOT 2017 | July 2017
-
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, Vol 15(12): pp. 3598-3601
Best demo award
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs
Hossein Golestani, Gagan Gupta, Rathijit Sen
IEEE Computer Architecture Letters | April 2019, Vol 18(1): pp. 79-82
Energy-Proportional Computing: A New Definition
Rathijit Sen, David A. Wood
IEEE Computer | July 2017, Vol 50(8): pp. 26-33
Pareto Governors for Energy-Optimal Computing
Rathijit Sen, David A. Wood
ACM Transactions on Architecture and Code Optimization | April 2017, Vol 14(1): pp. 6
-
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
-
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism.
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
May 2020