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Rathijit Sen
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2020 – today
- 2024
- [c29]Rathijit Sen
:
Performance or Efficiency? A Tale of Two Cores for DB Workloads. DaMoN 2024: 12:1-12:5 - [i16]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
- [j13]Yiwen Zhu
Runtime Variation in Big Data Analytics. Proc. ACM Manag. Data 1(1): 67:1-67:20 (2023) - [j12]Zezhou Huang, Rathijit Sen, Jiaxiang Liu, Eugene Wu:
JoinBoost: Grow Trees Over Normalized Data Using Only SQL. Proc. VLDB Endow. 16(11): 3071-3084 (2023) - [j11]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): 4230-4239 (2023) - [j10]Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim:
GPU Database Systems Characterization and Optimization. Proc. VLDB Endow. 17(3): 441-454 (2023) - [c28]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 - [c27]Wei Cui
Query Processing on Gaming Consoles. DaMoN 2023: 86-88 - [c26]Zezhou Huang
Random Forests over normalized data in CPU-GPU DBMSes. DaMoN 2023: 98-101 - [c25]Rathijit Sen
Microarchitectural Analysis of Graph BI Queries on RDBMS. DaMoN 2023: 102-106 - [c24]Rathijit Sen, Abhishek Roy, Alekh Jindal:
Predictive Price-Performance Optimization for Serverless Query Processing. EDBT 2023: 118-130 - [c23]Yiwen Zhu
Towards Building Autonomous Data Services on Azure. SIGMOD Conference Companion 2023: 217-224 - [i15]Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim:
Revisiting Query Performance in GPU Database Systems. CoRR abs/2302.00734 (2023) - [i14]Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta:
Runtime Variation in Big Data Analytics. CoRR abs/2304.03424 (2023) - [i13]Zezhou Huang, Rathijit Sen, Jiaxiang Liu, Eugene Wu:
JoinBoost: Grow Trees Over Normalized Data Using Only SQL. CoRR abs/2307.00422 (2023) - 2022
- [j9]Dong He, Supun Chathuranga Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park
Query Processing on Tensor Computation Runtimes. Proc. VLDB Endow. 15(11): 2811-2825 (2022) - [j8]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): 3598-3601 (2022) - [c22]Anish Pimpley, Shuo Li, Rathijit Sen, Soundararajan Srinivasan, Alekh Jindal:
Towards Optimal Resource Allocation for Big Data Analytics. EDBT 2022: 2:338-2:350 - [c21]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: 1-16 - [c20]Hossein Golestani
Calipers: a criticality-aware framework for modeling processor performance. ICS 2022: 2:1-2:14 - [c19]Kwanghyun Park
End-to-end Optimization of Machine Learning Prediction Queries. SIGMOD Conference 2022: 587-601 - [i12]Hossein Golestani, Rathijit Sen, Vinson Young, Gagan Gupta:
Calipers: A Criticality-aware Framework for Modeling Processor Performance. CoRR abs/2201.05884 (2022) - [i11]Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park
Query Processing on Tensor Computation Runtimes. CoRR abs/2203.01877 (2022) - [i10]Kwanghyun Park
End-to-end Optimization of Machine Learning Prediction Queries. CoRR abs/2206.00136 (2022) - [i9]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 abs/2209.04579 (2022) - [i8]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 abs/2211.02753 (2022) - 2021
- [j7]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): 2855-2858 (2021) - [c18]Kan Wu, Zhihan Guo, Guanzhou Hu, Kaiwei Tu, Ramnatthan Alagappan
The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus. FAST 2021: 307-323 - [c17]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: 1044-1055 - [c16]Alekh Jindal, Shi Qiao, Rathijit Sen, Hiren Patel:
Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft. ICDE 2021: 2423-2434 - [c15]Aniket Anand Deshmukh, Ruihao Li
Performance Characterization of .NET Benchmarks. ISPASS 2021: 107-117 - [c14]Zahra Azad, Rathijit Sen, Kwanghyun Park
Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads? ISPASS 2021: 243-253 - [i7]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 abs/2107.08594 (2021) - [i6]Rathijit Sen, Abhishek Roy, Alekh Jindal:
Predictive Price-Performance Optimization for Serverless Query Processing. CoRR abs/2112.08572 (2021) - 2020
- [j6]Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao:
AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft. Proc. VLDB Endow. 13(12): 3326-3339 (2020) - [c13]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 - [c12]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 - [c11]Yinjun Wu, Kwanghyun Park
Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS. DaMoN 2020: 14:1-14:3 - [c10]Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi:
Automated tuning of query degree of parallelism via machine learning. aiDM@SIGMOD 2020: 2:1-2:4 - [i5]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) - [i4]Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi:
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism. CoRR abs/2005.08439 (2020)
2010 – 2019
- 2019
- [j5]Hossein Golestani
Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs. IEEE Comput. Archit. Lett. 18(1): 79-82 (2019) - [c9]Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan:
Peregrine: Workload Optimization for Cloud Query Engines. SoCC 2019: 416-427 - [c8]Kan Wu, Andrea C. Arpaci-Dusseau
Exploiting Intel Optane SSD for Microsoft SQL Server. DaMoN 2019: 15:1-15:3 - [i3]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) - [i2]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 abs/1911.00231 (2019) - 2018
- [c7]Rathijit Sen, Karthik Ramachandra:
Characterizing Resource Sensitivity of Database Workloads. HPCA 2018: 657-669 - 2017
- [j4]Rathijit Sen, David A. Wood:
Energy-Proportional Computing: A New Definition. Computer 50(8): 26-33 (2017) - [j3]Rathijit Sen, David A. Wood:
Pareto Governors for Energy-Optimal Computing. ACM Trans. Archit. Code Optim. 14(1): 6:1-6:25 (2017) - [c6]Rathijit Sen, Alan Halverson:
Frequency governors for cloud database OLTP workloads. ISLPED 2017: 1-6 - [i1]Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha:
ROSA: R Optimizations with Static Analysis. CoRR abs/1704.02996 (2017) - 2016
- [j2]Rathijit Sen, David A. Wood:
GPGPU Footprint Models to Estimate per-Core Power. IEEE Comput. Archit. Lett. 15(2): 97-100 (2016) - 2013
- [c5]Rathijit Sen, David A. Wood:
Reuse-based online models for caches. SIGMETRICS 2013: 279-292 - 2011
- [j1]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): 1-7 (2011)
2000 – 2009
- 2009
- [c4]Aditya V. Thakur, Rathijit Sen, Ben Liblit
Cooperative crug isolation. WODA 2009: 35-41 - [c3]Jan Reineke, Rathijit Sen:
Sound and Efficient WCET Analysis in the Presence of Timing Anomalies. WCET 2009 - 2007
- [c2]Rathijit Sen, Y. N. Srikant:
WCET estimation for executables in the presence of data caches. EMSOFT 2007: 203-212 - [c1]Rathijit Sen, Y. N. Srikant:
Executable Analysis using Abstract Interpretation with Circular Linear Progressions. MEMOCODE 2007: 39-48
Coauthor Index
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last updated on 2024-07-19 19:20 CEST by the dblp team
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