Rathijit Sen

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 53

Top Topics

Optimal Resource Allocation

Query Processing

Top Venues

Proc. VLDB Endow.

Publications

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 (2024)
Rathijit Sen
Performance or Efficiency? A Tale of Two Cores for DB Workloads. DaMoN (2024)
Zezhou Huang, Rathijit Sen, Jiaxiang Liu, Eugene Wu
JoinBoost: Grow Trees Over Normalized Data Using Only SQL. Proc. VLDB Endow. 16 (11) (2023)
Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim
GPU Database Systems Characterization and Optimization. Proc. VLDB Endow. 17 (3) (2023)
Yiwen Zhu, Rathijit Sen, Robert Horton, John-Mark Agosta
Runtime Variation in Big Data Analytics. CoRR (2023)
Rathijit Sen, Yuanyuan Tian
Microarchitectural Analysis of Graph BI Queries on RDBMS. DaMoN (2023)
Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta
Runtime Variation in Big Data Analytics. Proc. ACM Manag. Data 1 (1) (2023)
Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
Optimizing Data Pipelines for Machine Learning in Feature Stores. Proc. VLDB Endow. 16 (13) (2023)
Wei Cui, Qianxi Zhang, Spyros Blanas, Jesús Camacho-Rodríguez, Brandon Haynes, Yinan Li, Ravi Ramamurthy, Peng Cheng, Rathijit Sen, Matteo Interlandi
Query Processing on Gaming Consoles. DaMoN (2023)
Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim
Revisiting Query Performance in GPU Database Systems. CoRR (2023)
Zezhou Huang, Rathijit Sen, Jiaxiang Liu, Eugene Wu
JoinBoost: Grow Trees Over Normalized Data Using Only SQL. CoRR (2023)
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
The Tensor Data Platform: Towards an AI-centric Database System. CIDR (2023)
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 Mueller, 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)
Zezhou Huang, Pavan Kalyan Damalapati, Rathijit Sen, Eugene Wu
Random Forests over normalized data in CPU-GPU DBMSes. DaMoN (2023)
Rathijit Sen, Abhishek Roy, Alekh Jindal
Predictive Price-Performance Optimization for Serverless Query Processing. EDBT (2023)
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. Proc. VLDB Endow. 15 (12) (2022)
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
End-to-end Optimization of Machine Learning Prediction Queries. CoRR (2022)
Kan Wu, Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching. FAST (2022)
Hossein Golestani, Rathijit Sen, Vinson Young, Gagan Gupta
Calipers: A Criticality-aware Framework for Modeling Processor Performance. CoRR (2022)
Anish Pimpley, Shuo Li, Rathijit Sen, Soundararajan Srinivasan, Alekh Jindal
Towards Optimal Resource Allocation for Big Data Analytics. EDBT (2022)
Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
End-to-end Optimization of Machine Learning Prediction Queries. SIGMOD Conference (2022)
Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. CoRR (2022)
Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
The Tensor Data Platform: Towards an AI-centric Database System. CoRR (2022)
Hossein Golestani, Rathijit Sen, Vinson Young, Gagan Gupta
Calipers: a criticality-aware framework for modeling processor performance. ICS (2022)
Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
Query Processing on Tensor Computation Runtimes. CoRR (2022)
Dong He, Supun Chathuranga Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
Query Processing on Tensor Computation Runtimes. Proc. VLDB Endow. 15 (11) (2022)
Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel
Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft. ICDE (2021)
Rathijit Sen, Abhishek Roy, Alekh Jindal, Rui Fang, Jeff Zheng, Xiaolei Liu, Ruiping Li
AutoExecutor: Predictive Parallelism for Spark SQL Queries. Proc. VLDB Endow. 14 (12) (2021)
Zahra Azad, Rathijit Sen, Kwanghyun Park, Ajay Joshi
Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads? ISPASS (2021)
Zubeyr F. Eryilmaz, Aarati Kakaraparthy, Jignesh M. Patel, Rathijit Sen, Kwanghyun Park
FPGA for Aggregate Processing: The Good, The Bad, and The Ugly. ICDE (2021)
Rathijit Sen, Abhishek Roy, Alekh Jindal
Predictive Price-Performance Optimization for Serverless Query Processing. CoRR (2021)
Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan, Rathijit Sen, Kwanghyun Park, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus. FAST (2021)
Anish Pimpley, Shuo Li, Anubha Srivastava, Vishal Rohra, Yi Zhu, Soundararajan Srinivasan, Alekh Jindal, Hiren Patel, Shi Qiao, Rathijit Sen
Optimal Resource Allocation for Serverless Queries. CoRR (2021)
Aniket Deshmukh, Ruihao Li, Rathijit Sen, Robert R. Henry, Monica Beckwith, Gagan Gupta
Performance Characterization of .NET Benchmarks. ISPASS (2021)
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft. Proc. VLDB Endow. 13 (12) (2020)
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism. CoRR (2020)
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)
Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi
Automated tuning of query degree of parallelism via machine learning. aiDM@SIGMOD (2020)
Konstantinos Karanasos, Matteo Interlandi, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Doris Xin, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Extending Relational Query Processing with ML Inference. CIDR (2020)
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)
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 (2020)
Hossein Golestani, Gagan Gupta, Rathijit Sen
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs. IEEE Comput. Archit. Lett. 18 (1) (2019)
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 (2019)
Kan Wu, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, Rathijit Sen, Kwanghyun Park
Exploiting Intel Optane SSD for Microsoft SQL Server. DaMoN (2019)
Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
Peregrine: Workload Optimization for Cloud Query Engines. SoCC (2019)
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
Extending Relational Query Processing with ML Inference. CoRR (2019)
Hiren Patel, Alekh Jindal, Subru Krishnan, Rathijit Sen, Shi Qiao, Abhishek Roy, Zhicheng Yin
Peregrine: Workload Optimization for Cloud Query Engines. SoCC (2019)
Rathijit Sen, Karthik Ramachandra
Characterizing Resource Sensitivity of Database Workloads. HPCA (2018)
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha
ROSA: R Optimizations with Static Analysis. CoRR (2017)
Rathijit Sen, David A. Wood
Energy-Proportional Computing: A New Definition. Computer 50 (8) (2017)
Rathijit Sen, Alan Halverson
Frequency governors for cloud database OLTP workloads. ISLPED (2017)
Rathijit Sen, David A. Wood
Pareto Governors for Energy-Optimal Computing. ACM Trans. Archit. Code Optim. 14 (1) (2017)
Rathijit Sen, David A. Wood
GPGPU Footprint Models to Estimate per-Core Power. IEEE Comput. Archit. Lett. 15 (2) (2016)
Rathijit Sen, David A. Wood
Reuse-based online models for caches. SIGMETRICS (2013)
Nathan L. Binkert, Bradford M. Beckmann, Gabriel Black, Steven K. Reinhardt, Ali G. Saidi, Arkaprava Basu, Joel Hestness, Derek Hower, Tushar Krishna, Somayeh Sardashti, Rathijit Sen, Korey Sewell, Muhammad Shoaib Bin Altaf, Nilay Vaish, Mark D. Hill, David A. Wood
The gem5 simulator. SIGARCH Comput. Archit. News 39 (2) (2011)
Aditya V. Thakur, Rathijit Sen, Ben Liblit, Shan Lu
Cooperative crug isolation. WODA (2009)
Jan Reineke, Rathijit Sen
Sound and Efficient WCET Analysis in the Presence of Timing Anomalies. WCET (2009)
Rathijit Sen, Y. N. Srikant
WCET estimation for executables in the presence of data caches. EMSOFT (2007)
Rathijit Sen, Y. N. Srikant
Executable Analysis using Abstract Interpretation with Circular Linear Progressions. MEMOCODE (2007)