default search action
Arun Kejariwal
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c56]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: 12181-12189 - 2023
- [c55]Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna:
Characterization of Data Compression in Datacenters. ISPASS 2023: 1-12 - [c54]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 - [c53]Yuhao Li, Abhishek Gupta, Alex Yang, Peinan Chen, Joey Pinto, Brian Karrer, Mayank Pundir, Maximilian Balandat, Arun Kejariwal, Benjamin C. Lee:
HHVM Performance Optimization for Large Scale Web Services. ICPE 2023: 137-148 - [i11]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 abs/2305.01868 (2023) - 2022
- [c52]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: 48-58 - [c51]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: 221-223 - [c50]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: 227-229 - [c49]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: 4461-4471 - [c48]Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal:
Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) 2022: 504-516 - [c47]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 - [c46]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: 2256-2266 - [i10]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 abs/2201.07821 (2022) - [i9]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 abs/2208.06399 (2022) - [i8]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 abs/2209.01143 (2022) - [i7]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 abs/2210.02023 (2022) - 2021
- [c45]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: 1421-1428 - [c44]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: 2928-2936 - [i6]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 abs/2105.01064 (2021) - 2020
- [c43]Anurag Khandelwal, Arun Kejariwal, Karthikeyan Ramasamy:
Le Taureau: Deconstructing the Serverless Landscape & A Look Forward. SIGMOD Conference 2020: 2641-2650 - [i5]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 abs/2010.08655 (2020) - [i4]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 abs/2010.08899 (2020)
2010 – 2019
- 2017
- [i3]Jordan Hochenbaum, Owen S. Vallis, Arun Kejariwal:
Automatic Anomaly Detection in the Cloud Via Statistical Learning. CoRR abs/1704.07706 (2017) - [i2]Arun Kejariwal, Sanjeev Kulkarni, Karthik Ramasamy:
Real Time Analytics: Algorithms and Systems. CoRR abs/1708.02621 (2017) - [i1]Dhruv Choudhary, Arun Kejariwal, Francois Orsini:
On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data. CoRR abs/1710.04735 (2017) - 2016
- [c42]Nicholas A. James, Arun Kejariwal, David S. Matteson:
Leveraging cloud data to mitigate user experience from 'breaking bad'. IEEE BigData 2016: 3499-3508 - [c41]Arun Kejariwal, Francois Orsini:
On the Definition of Real-Time: Applications and Systems. Trustcom/BigDataSE/ISPA 2016: 2213-2220 - 2015
- [j6]Arun Kejariwal, Sanjeev Kulkarni, Karthik Ramasamy:
Real Time Analytics: Algorithms and Systems. Proc. VLDB Endow. 8(12): 2040-2041 (2015) - 2014
- [c40]Owen Vallis, Jordan Hochenbaum, Arun Kejariwal:
A Novel Technique for Long-Term Anomaly Detection in the Cloud. HotCloud 2014 - 2013
- [c39]Rosario Cammarota, Alexandru Nicolau, Alexander V. Veidenbaum, Arun Kejariwal, Debora Donato, Mukund Madhugiri:
On the Determination of Inlining Vectors for Program Optimization. CC 2013: 164-183 - [c38]Arun Kejariwal, Winston Lee, Owen Vallis, Jordan Hochenbaum, Bryce Yan:
Visual Analytics Framework for Cloud Infrastructure Data. CSE 2013: 886-893 - [c37]Arun Kejariwal:
A Tool for Practical Garbage Collection Analysis in the Cloud. IC2E 2013: 46-53 - [c36]Arun Kejariwal:
Techniques for Optimizing Cloud Footprint. IC2E 2013: 258-268 - [c35]Winston Lee, Arun Kejariwal, Bryce Yan:
Chiffchaff: Observability and analytics to achieve high availability. LDAV 2013: 119-120 - 2012
- [j5]Rohit Jalan, Arun Kejariwal:
Trin-Trin: Who's Calling? A Pin-Based Dynamic Call Graph Extraction Framework. Int. J. Parallel Program. 40(4): 410-442 (2012) - [c34]Rosario Cammarota, Arun Kejariwal, Debora Donato, Alexandru Nicolau, Alexander V. Veidenbaum:
Selective search of inlining vectors for program optimization. Conf. Computing Frontiers 2012: 257-260 - [c33]Arun Kejariwal:
Big Data Challenges: A Program Optimization Perspective. CGC 2012: 702-707 - 2011
- [c32]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: 4 - [r1]Arun Kejariwal, Alexandru Nicolau:
Modulo Scheduling and Loop Pipelining. Encyclopedia of Parallel Computing 2011: 1158-1173 - 2010
- [c31]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: 99-100 - [c30]Alexandru Nicolau, Arun Kejariwal:
How Many Threads to Spawn during Program Multithreading? LCPC 2010: 166-183 - [c29]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: 247-248
2000 – 2009
- 2009
- [j4]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): 10:1-10:34 (2009) - [c28]Arun Kejariwal, Alexandru Nicolau, Alexander V. Veidenbaum, Utpal Banerjee, Constantine D. Polychronopoulos:
Efficient Scheduling of Nested Parallel Loops on Multi-Core Systems. ICPP 2009: 74-83 - [c27]Alexandru Nicolau, Guangqiang Li, Alexander V. Veidenbaum, Arun Kejariwal:
Synchronization optimizations for efficient execution on multi-cores. ICS 2009: 169-180 - [c26]Alexandru Nicolau, Guangqiang Li, Arun Kejariwal:
Techniques for efficient placement of synchronization primitives. PPoPP 2009: 199-208 - [c25]Arun Kejariwal, Calin Cascaval:
Parallelization spectroscopy: analysis of thread-level parallelism in hpc programs. PPoPP 2009: 293-294 - [c24]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: 36-56 - [c23]Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Alexander V. Veidenbaum, Constantine D. Polychronopoulos:
Cache-aware partitioning of multi-dimensional iteration spaces. SYSTOR 2009: 15 - 2008
- [j3]Jelena Trajkovic, Alexander V. Veidenbaum, Arun Kejariwal:
Improving SDRAM access energy efficiency for low-power embedded systems. ACM Trans. Embed. Comput. Syst. 7(3): 24:1-24:21 (2008) - [c22]Peng Wu, Arun Kejariwal, Calin Cascaval:
Compiler-Driven Dependence Profiling to Guide Program Parallelization. LCPC 2008: 232-248 - [c21]Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Alexander V. Veidenbaum, Constantine D. Polychronopoulos:
Cache-aware iteration space partitioning. PPoPP 2008: 269-270 - [c20]Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau, Xinmin Tian, Milind Girkar, Hideki Saito, Utpal Banerjee:
Comparative architectural characterization of SPEC CPU2000 and CPU2006 benchmarks on the intel® CoreTM 2 Duo processor. ICSAMOS 2008: 132-141 - 2007
- [j2]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): 14 (2007) - [c19]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: 215-225 - [c18]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: 361-362 - 2006
- [j1]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): 625-636 (2006) - [c17]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: 173-180 - [c16]Milind Girkar, Arun Kejariwal, Xinmin Tian, Hideki Saito, Alexandru Nicolau, Alexander V. Veidenbaum, Constantine D. Polychronopoulos:
Probablistic Self-Scheduling. Euro-Par 2006: 253-264 - [c15]Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos:
History-aware Self-Scheduling. ICPP 2006: 185-192 - [c14]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: 24 - [c13]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: 361-371 - [c12]Basant Kumar Dwivedi, Arun Kejariwal, M. Balakrishnan, Anshul Kumar:
Rapid Resource-Constrained Hardware Performance Estimation. IEEE International Workshop on Rapid System Prototyping 2006: 40-46 - [c11]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: 49-58 - 2005
- [c10]Ana Azevedo, Arun Kejariwal, Alexander V. Veidenbaum, Alexandru Nicolau:
High performance annotation-aware JVM for Java cards. EMSOFT 2005: 52-61 - [c9]Arun Kejariwal, Sumit Gupta, Alexandru Nicolau, Nikil D. Dutt, Rajesh Gupta:
Energy Analysis of Multimedia Watermarking on Mobile Handheld Devices. ESTIMedia 2005: 33-38 - [c8]Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos:
Enhanced Loop Coalescing: A Compiler Technique for Transforming Non-uniform Iteration Spaces. ISHPC 2005: 17-32 - [c7]Arun Kejariwal, Alexandru Nicolau:
An Efficient Load Balancing Scheme for Grid-based High Performance Scientific Computing. ISPDC 2005: 217-225 - [c6]Arun Kejariwal, Alexandru Nicolau, Constantine D. Polychronopoulos:
An Efficient Approach for Self-scheduling Parallel Loops on Multiprogrammed Parallel Computers. LCPC 2005: 441-449 - [c5]Arun Kejariwal, Alexandru Nicolau, Utpal Banerjee, Constantine D. Polychronopoulos:
A novel approach for partitioning iteration spaces with variable densities. PPoPP 2005: 120-131 - 2004
- [c4]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: 556-561 - [c3]Arun Kejariwal, Paolo D'Alberto, Alexandru Nicolau, Constantine D. Polychronopoulos:
A Geometric Approach for Partitioning N-Dimensional Non-rectangular Iteration Spaces. LCPC 2004: 102-116 - [c2]Prabhat Mishra, Arun Kejariwal, Nikil D. Dutt:
Synthesis-driven Exploration of Pipelined Embedded Processors. VLSI Design 2004: 921-926 - 2003
- [c1]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: 226-232
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-25 21:12 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint