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Krishnakumar Nair
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2020 – today
- 2024
- [i7]Pingyi Huo, Anusha Devulapally, Hasan Al Maruf, Minseo Park, Krishnakumar Nair, Meena Arunachalam, Gulsum Gudukbay Akbulut, Mahmut Taylan Kandemir, Vijaykrishnan Narayanan:
PIFS-Rec: Process-In-Fabric-Switch for Large-Scale Recommendation System Inferences. CoRR abs/2409.16633 (2024) - 2023
- [c11]Amin Firoozshahian, Joel Coburn, Roman Levenstein, Rakesh Nattoji, Ashwin Kamath, Olívia Wu, Gurdeepak Grewal, Harish Aepala, Bhasker Jakka, Bob Dreyer, Adam Hutchin, Utku Diril, Krishnakumar Nair, Ehsan K. Ardestani, Martin Schatz, Yuchen Hao, Rakesh Komuravelli, Kunming Ho, Sameer Abu Asal, Joe Shajrawi, Kevin Quinn, Nagesh Sreedhara, Pankaj Kansal, Willie Wei, Dheepak Jayaraman, Linda Cheng, Pritam Chopda, Eric Wang, Ajay Bikumandla, Arun Karthik Sengottuvel, Krishna Thottempudi, Ashwin Narasimha, Brian Dodds, Cao Gao, Jiyuan Zhang, Mohammed Al-Sanabani, Ana Zehtabioskuie, Jordan Fix, Hangchen Yu, Richard Li, Kaustubh Gondkar, Jack Montgomery, Mike Tsai, Saritha Dwarakapuram, Sanjay Desai, Nili Avidan, Poorvaja Ramani, Karthik Narayanan, Ajit Mathews, Sethu Gopal, Maxim Naumov, Vijay Rao, Krishna Noru, Harikrishna Reddy, Prahlad Venkatapuram, Alexis Bjorlin:
MTIA: First Generation Silicon Targeting Meta's Recommendation Systems. ISCA 2023: 80:1-80:13 - [c10]Hyoukjun Kwon, Krishnakumar Nair, Jamin Seo, Jason Yik, Debabrata Mohapatra, Dongyuan Zhan, Jinook Song, Peter Capak, Peizhao Zhang, Peter Vajda, Colby R. Banbury, Mark Mazumder, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. MLSys 2023 - 2022
- [j4]Nikhil Valsan Kulangareth, Karl Magtibay, Stéphane Massé, Krishnakumar Nair, Paul Dorian, Kumaraswamy Nanthakumar, Karthikeyan Umapathy:
An In-Silico model for evaluating the directional shock vectors in terminating and modulating rotors. Comput. Biol. Medicine 146: 105665 (2022) - [c9]Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Jens Axboe, Valmiki Rampersad, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Dheevatsa Mudigere, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Krishnakumar Nair, Maxim Naumov, Chris Petersen, Mikhail Smelyanskiy, Vijay Rao:
Supporting Massive DLRM Inference through Software Defined Memory. ICDCS 2022: 302-312 - [c8]Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao:
Software-hardware co-design for fast and scalable training of deep learning recommendation models. ISCA 2022: 993-1011 - [c7]Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Krishnakumar Nair, Misha Smelyanskiy, Murali Annavaram:
Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models. NSDI 2022: 929-943 - [i6]Benjamin Ghaemmaghami, Mustafa Ozdal, Rakesh Komuravelli, Dmitriy Korchev, Dheevatsa Mudigere, Krishnakumar Nair, Maxim Naumov:
Learning to Collide: Recommendation System Model Compression with Learned Hash Functions. CoRR abs/2203.15837 (2022) - [i5]Hyoukjun Kwon, Krishnakumar Nair, Jamin Seo, Jason Yik, Debabrata Mohapatra, Dongyuan Zhan, Jinook Song, Peter Capak, Peizhao Zhang, Peter Vajda, Colby R. Banbury, Mark Mazumder, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. CoRR abs/2211.08675 (2022) - 2021
- [i4]Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao:
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. CoRR abs/2104.05158 (2021) - [i3]Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Valmiki Rampersad, Jens Axboe, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Dheevatsa Mudigere, Krishnakumar Nair, Maxim Naumov, Chris Peterson, Mikhail Smelyanskiy, Vijay Rao:
Supporting Massive DLRM Inference Through Software Defined Memory. CoRR abs/2110.11489 (2021) - 2020
- [c6]Saeed Rashidi, Pallavi Shurpali, Srinivas Sridharan, Naader Hassani, Dheevatsa Mudigere, Krishnakumar Nair, Misha Smelyanski, Tushar Krishna:
Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transport. Hot Interconnects 2020: 33-42 - [i2]Maxim Naumov, John Kim, Dheevatsa Mudigere, Srinivas Sridharan, Xiaodong Wang, Whitney Zhao, Serhat Yilmaz, Changkyu Kim, Hector Yuen, Mustafa Ozdal, Krishnakumar Nair, Isabel Gao, Bor-Yiing Su, Jiyan Yang, Mikhail Smelyanskiy:
Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems. CoRR abs/2003.09518 (2020) - [i1]Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Murali Annavaram, Krishnakumar Nair, Misha Smelyanskiy:
Check-N-Run: A Checkpointing System for Training Recommendation Models. CoRR abs/2010.08679 (2020)
2010 – 2019
- 2019
- [j3]Matthew Hotradat, Krishnanand Balasundaram, Stéphane Massé, Krishnakumar Nair, Kumaraswamy Nanthakumar, Karthikeyan Umapathy:
Empirical mode decomposition based ECG features in classifying and tracking ventricular arrhythmias. Comput. Biol. Medicine 112 (2019) - 2018
- [c5]Matthew Hotradat, Krishnanand Balasundaram, Stéphane Massé, Krishnakumar Nair, Kumaraswamy Nanthakumar, Karthikeyan Umapathy:
Instantaneous Time-Frequency Features in Characterizing Ventricular Arrhythmias Using Empirical Mode Decomposition. ACSSC 2018: 1225-1229 - 2017
- [j2]Krishnanand Balasundaram, Stéphane Massé, Talha Farid, Krishnakumar Nair, John Asta, Robert J. Cusimano, Edward J. Vigmond, Kumaraswamy Nanthakumar, Karthikeyan Umapathy:
Morphologically constrained signal subspace characterization of electrograms during ventricular fibrillation. Biomed. Signal Process. Control. 38: 379-387 (2017) - 2013
- [j1]Krishnanand Balasundaram, Stéphane Massé, Krishnakumar Nair, Karthikeyan Umapathy:
A classification scheme for ventricular arrhythmias using wavelets analysis. Medical Biol. Eng. Comput. 51(1-2): 153-164 (2013) - [c4]Krishnanand Balasundaram, Stéphane Massé, Krishnakumar Nair, Karthikeyan Umapathy:
Automated signal pattern detection in ECG during human ventricular arrhythmias. EMBC 2013: 1029-1032 - 2011
- [c3]J. Jeyaratnam, Karthikeyan Umapathy, Stéphane Massé, Krishnakumar Nair, Talha Farid, Sridhar Krishnan, Kumaraswamy Nanthakumar:
Relating spatial heterogeneities to rotor formation in studying human ventricular fibrillation. EMBC 2011: 231-234 - [c2]E. Afatmirni, Kumaraswamy Nanthakumar, Stéphane Massé, Krishnakumar Nair, Talha Farid, Sridhar Krishnan, Paul Dorian, Karthikeyan Umapathy:
Predicting refibrillation from pre-shock waveforms in optimizing cardiac resuscitation. EMBC 2011: 251-254 - [c1]Krishnanand Balasundaram, Stéphane Massé, Krishnakumar Nair, Talha Farid, Kumaraswamy Nanthakumar, Karthikeyan Umapathy:
Wavelet-based features for characterizing ventricular arrhythmias in optimizing treatment options. EMBC 2011: 969-972
Coauthor Index
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