Arun Kejariwal

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 27

Top Topics

Recommender Systems

Transfer Learning

Data Compression

Recommendation Systems

Top Venues

Proc. VLDB Endow.

Publications

Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu
Layer Compression of Deep Networks with Straight Flows. AAAI (2024)
Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. CoRR (2023)
Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. MLSys (2023)
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
Characterization of Data Compression in Datacenters. ISPASS (2023)
Yuhao Li, Abhishek Gupta, Alex Yang, Peinan Chen, Joey Pinto, Brian Karrer, Mayank Pundir, Maximilian Balandat, Arun Kejariwal, Benjamin Lee
HHVM Performance Optimization for Large Scale Web Services. ICPE (2023)
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
Understanding Data Compression in Warehouse-Scale Datacenter Services. ISPASS (2022)
Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD (2022)
Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal
Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) (2022)
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. ISPASS (2022)
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. CoRR (2022)
Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. UAI (2022)
Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems. CoRR (2022)
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. CoRR (2022)
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. HIPC (2022)
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. NeurIPS (2022)
Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR (2022)
Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. KDD (2021)
Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. CoRR (2021)
Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. ICMLA (2021)
Anurag Khandelwal, Arun Kejariwal, Karthikeyan Ramasamy
Le Taureau: Deconstructing the Serverless Landscape & A Look Forward. SIGMOD Conference (2020)
Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. CoRR (2020)
Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. CoRR (2020)
Dhruv Choudhary, Arun Kejariwal, Francois Orsini
On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data. CoRR (2017)
Arun Kejariwal, Sanjeev Kulkarni, Karthik Ramasamy
Real Time Analytics: Algorithms and Systems. CoRR (2017)
Jordan Hochenbaum, Owen S. Vallis, Arun Kejariwal
Automatic Anomaly Detection in the Cloud Via Statistical Learning. CoRR (2017)
Nicholas A. James, Arun Kejariwal, David S. Matteson
Leveraging cloud data to mitigate user experience from 'breaking bad'. IEEE BigData (2016)
Arun Kejariwal, Francois Orsini
On the Definition of Real-Time: Applications and Systems. Trustcom/BigDataSE/ISPA (2016)
Arun Kejariwal, Sanjeev Kulkarni, Karthik Ramasamy
Real Time Analytics: Algorithms and Systems. Proc. VLDB Endow. 8 (12) (2015)
Owen Vallis, Jordan Hochenbaum, Arun Kejariwal
A Novel Technique for Long-Term Anomaly Detection in the Cloud. HotCloud (2014)
Winston Lee, Arun Kejariwal, Bryce Yan
Chiffchaff: Observability and analytics to achieve high availability. LDAV (2013)
Arun Kejariwal, Winston Lee, Owen Vallis, Jordan Hochenbaum, Bryce Yan
Visual Analytics Framework for Cloud Infrastructure Data. CSE (2013)
Arun Kejariwal
Techniques for Optimizing Cloud Footprint. IC2E (2013)
Arun Kejariwal
A Tool for Practical Garbage Collection Analysis in the Cloud. IC2E (2013)
Rosario Cammarota, Alexandru Nicolau, Alexander V. Veidenbaum, Arun Kejariwal, Debora Donato, Mukund Madhugiri
On the Determination of Inlining Vectors for Program Optimization. CC (2013)
Rosario Cammarota, Arun Kejariwal, Debora Donato, Alexandru Nicolau, Alexander V. Veidenbaum
Selective search of inlining vectors for program optimization. Conf. Computing Frontiers (2012)
Arun Kejariwal
Big Data Challenges: A Program Optimization Perspective. CGC (2012)
Rohit Jalan, Arun Kejariwal
Trin-Trin: Who's Calling? A Pin-Based Dynamic Call Graph Extraction Framework. Int. J. Parallel Program. 40 (4) (2012)
Rosario Cammarota, Arun Kejariwal, Paolo D'Alberto, Sapan Panigrahi, Alexander V. Veidenbaum, Alexandru Nicolau
Pruning hardware evaluation space via correlation-driven application similarity analysis. Conf. Computing Frontiers (2011)
Alexandru Nicolau, Arun Kejariwal
How Many Threads to Spawn during Program Multithreading? LCPC (2010)
Arun Kejariwal, Milind Girkar, Xinmin Tian, Hideki Saito, Alexandru Nicolau, Alexander V. Veidenbaum, Utpal Banerjee, Constantine D. Polychronopoulos
On the efficacy of call graph-level thread-level speculation. WOSP/SIPEW (2010)
Arun Kejariwal, Milind Girkar, Xinmin Tian, Hideki Saito, Alexandru Nicolau, Alexander V. Veidenbaum, Utpal Banerjee, Constantine D. Polychronopoulos
Exploitation of nested thread-level speculative parallelism on multi-core systems. Conf. Computing Frontiers (2010)
Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau, Milind Girkar, Xinmin Tian, Hideki Saito
On the exploitation of loop-level parallelism in embedded applications. ACM Trans. Embed. Comput. Syst. 8 (2) (2009)
Alexandru Nicolau, Guangqiang Li, Arun Kejariwal
Techniques for efficient placement of synchronization primitives. PPOPP (2009)
Arun Kejariwal, Alexandru Nicolau, Alexander V. Veidenbaum, Utpal Banerjee, Constantine D. Polychronopoulos
Efficient Scheduling of Nested Parallel Loops on Multi-Core Systems. ICPP (2009)
Alexandru Nicolau, Guangqiang Li, Alexander V. Veidenbaum, Arun Kejariwal
Synchronization optimizations for efficient execution on multi-cores. ICS (2009)
Arun Kejariwal, Calin Cascaval
Parallelization spectroscopy: analysis of thread-level parallelism in hpc programs. PPOPP (2009)
Darshan Desai, Gerolf Hoflehner, Arun Kejariwal, Daniel M. Lavery, Alexandru Nicolau, Alexander V. Veidenbaum, Cameron McNairy
Performance Characterization of Itanium® 2-Based Montecito Processor. SPEC Benchmark Workshop (2009)
Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Alexander V. Veidenbaum, Constantine D. Polychronopoulos
Cache-aware partitioning of multi-dimensional iteration spaces. SYSTOR (2009)
Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau, Xinmin Tian, Milind Girkar, Hideki Saito, Utpal Banerjee
2 Duo processor. ICSAMOS (2008)
Jelena Trajkovic, Alexander V. Veidenbaum, Arun Kejariwal
Improving SDRAM access energy efficiency for low-power embedded systems. ACM Trans. Embed. Comput. Syst. 7 (3) (2008)
Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Alexander V. Veidenbaum, Constantine D. Polychronopoulos
Cache-aware iteration space partitioning. PPOPP (2008)
Peng Wu, Arun Kejariwal, Calin Cascaval
Compiler-Driven Dependence Profiling to Guide Program Parallelization. LCPC (2008)
Arun Kejariwal, Xinmin Tian, Milind Girkar, Wei Li, Sergey Kozhukhov, Utpal Banerjee, Alexandru Nicolau, Alexander V. Veidenbaum, Constantine D. Polychronopoulos
Tight analysis of the performance potential of thread speculation using spec CPU 2006. PPOPP (2007)
Weiyu Tang, Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau
A predictive decode filter cache for reducing power consumption in embedded processors. ACM Trans. Design Autom. Electr. Syst. 12 (2) (2007)
Arun Kejariwal, Gerolf Hoflehner, Darshan Desai, Daniel M. Lavery, Alexandru Nicolau, Alexander V. Veidenbaum
Comparative characterization of SPEC CPU2000 and CPU2006 on Itanium architecture. SIGMETRICS (2007)
Basant Kumar Dwivedi, Arun Kejariwal, M. Balakrishnan, Anshul Kumar
Rapid Resource-Constrained Hardware Performance Estimation. IEEE International Workshop on Rapid System Prototyping (2006)
Milind Girkar, Arun Kejariwal, Xinmin Tian, Hideki Saito, Alexandru Nicolau, Alexander V. Veidenbaum, Constantine D. Polychronopoulos
Probablistic Self-Scheduling. Euro-Par (2006)
Arun Kejariwal, Hideki Saito, Xinmin Tian, Milind Girkar, Wei Li, Utpal Banerjee, Alexandru Nicolau, Constantine D. Polychronopoulos
Lightweight lock-free synchronization methods for multithreading. ICS (2006)
Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau, Milind Girkar, Xinmin Tian, Hideki Saito
Challenges in exploitation of loop parallelism in embedded applications. CODES+ISSS (2006)
Arun Kejariwal, Xinmin Tian, Wei Li, Milind Girkar, Sergey Kozhukhov, Hideki Saito, Utpal Banerjee, Alexandru Nicolau, Alexander V. Veidenbaum, Constantine D. Polychronopoulos
On the performance potential of different types of speculative thread-level parallelism: The DL version of this paper includes corrections that were not made available in the printed proceedings. ICS (2006)
Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos
History-aware Self-Scheduling. ICPP (2006)
Arun Kejariwal, Sumit Gupta, Alexandru Nicolau, Nikil D. Dutt, Rajesh K. Gupta
Energy efficient watermarking on mobile devices using proxy-based partitioning. IEEE Trans. Very Large Scale Integr. Syst. 14 (6) (2006)
Arun Kejariwal, Alexandru Nicolau, Hideki Saito, Xinmin Tian, Milind Girkar, Utpal Banerjee, Constantine D. Polychronopoulos
A general approach for partitioning N-dimensional parallel nested loops with conditionals. SPAA (2006)
Arun Kejariwal, Alexandru Nicolau
An Efficient Load Balancing Scheme for Grid-based High Performance Scientific Computing. ISPDC (2005)
Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Constantine D. Polychronopoulos
A novel approach for partitioning iteration spaces with variable densities. PPOPP (2005)
Ana Azevedo, Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau
High performance annotation-aware JVM for Java cards. EMSOFT (2005)
Arun Kejariwal, Sumit Gupta, Alexandru Nicolau, Nikil D. Dutt, Rajesh Gupta
Energy Analysis of Multimedia Watermarking on Mobile Handheld Devices. ESTIMedia (2005)
Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos
An Efficient Approach for Self-scheduling Parallel Loops on Multiprogrammed Parallel Computers. LCPC (2005)
Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos
Enhanced Loop Coalescing: A Compiler Technique for Transforming Non-uniform Iteration Spaces. ISHPC (2005)
Prabhat Mishra, Arun Kejariwal, Nikil D. Dutt
Synthesis-driven Exploration of Pipelined Embedded Processors. VLSI Design (2004)
Arun Kejariwal, Paolo D'Alberto, Alexandru Nicolau, Constantine D. Polychronopoulos
A Geometric Approach for Partitioning N-Dimensional Non-rectangular Iteration Spaces. LCPC (2004)
Arun Kejariwal, Sumit Gupta, Alexandru Nicolau, Nikil D. Dutt, Rajesh Gupta
Proxy-based task partitioning of watermarking algorithms for reducing energy consumption in mobile devices. DAC (2004)
Prabhat Mishra, Arun Kejariwal, Nikil D. Dutt
Rapid Exploration of Pipelined Processors through Automatic Generation of Synthesizable RTL Models. IEEE International Workshop on Rapid System Prototyping (2003)