BibTeX records: Ansha Yu

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@inproceedings{DBLP:conf/icdcs/ArdestaniKLPARA22,
  author       = {Ehsan K. Ardestani and
                  Changkyu Kim and
                  Seung Jae Lee and
                  Luoshang Pan and
                  Jens Axboe and
                  Valmiki Rampersad and
                  Banit Agrawal and
                  Fuxun Yu and
                  Ansha Yu and
                  Trung Le and
                  Hector Yuen and
                  Dheevatsa Mudigere and
                  Shishir Juluri and
                  Akshat Nanda and
                  Manoj Wodekar and
                  Krishnakumar Nair and
                  Maxim Naumov and
                  Chris Petersen and
                  Mikhail Smelyanskiy and
                  Vijay Rao},
  title        = {Supporting Massive {DLRM} Inference through Software Defined Memory},
  booktitle    = {42nd {IEEE} International Conference on Distributed Computing Systems,
                  {ICDCS} 2022, Bologna, Italy, July 10-13, 2022},
  pages        = {302--312},
  publisher    = {{IEEE}},
  year         = {2022},
  url          = {https://doi.org/10.1109/ICDCS54860.2022.00037},
  doi          = {10.1109/ICDCS54860.2022.00037},
  timestamp    = {Thu, 20 Oct 2022 09:13:03 +0200},
  biburl       = {https://dblp.org/rec/conf/icdcs/ArdestaniKLPARA22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/abs-2110-11489,
  author       = {Ehsan K. Ardestani and
                  Changkyu Kim and
                  Seung Jae Lee and
                  Luoshang Pan and
                  Valmiki Rampersad and
                  Jens Axboe and
                  Banit Agrawal and
                  Fuxun Yu and
                  Ansha Yu and
                  Trung Le and
                  Hector Yuen and
                  Shishir Juluri and
                  Akshat Nanda and
                  Manoj Wodekar and
                  Dheevatsa Mudigere and
                  Krishnakumar Nair and
                  Maxim Naumov and
                  Chris Peterson and
                  Mikhail Smelyanskiy and
                  Vijay Rao},
  title        = {Supporting Massive {DLRM} Inference Through Software Defined Memory},
  journal      = {CoRR},
  volume       = {abs/2110.11489},
  year         = {2021},
  url          = {https://arxiv.org/abs/2110.11489},
  eprinttype    = {arXiv},
  eprint       = {2110.11489},
  timestamp    = {Wed, 08 Feb 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2110-11489.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/abs-1906-00091,
  author       = {Maxim Naumov and
                  Dheevatsa Mudigere and
                  Hao{-}Jun Michael Shi and
                  Jianyu Huang and
                  Narayanan Sundaraman and
                  Jongsoo Park and
                  Xiaodong Wang and
                  Udit Gupta and
                  Carole{-}Jean Wu and
                  Alisson G. Azzolini and
                  Dmytro Dzhulgakov and
                  Andrey Mallevich and
                  Ilia Cherniavskii and
                  Yinghai Lu and
                  Raghuraman Krishnamoorthi and
                  Ansha Yu and
                  Volodymyr Kondratenko and
                  Stephanie Pereira and
                  Xianjie Chen and
                  Wenlin Chen and
                  Vijay Rao and
                  Bill Jia and
                  Liang Xiong and
                  Misha Smelyanskiy},
  title        = {Deep Learning Recommendation Model for Personalization and Recommendation
                  Systems},
  journal      = {CoRR},
  volume       = {abs/1906.00091},
  year         = {2019},
  url          = {http://arxiv.org/abs/1906.00091},
  eprinttype    = {arXiv},
  eprint       = {1906.00091},
  timestamp    = {Wed, 15 Apr 2020 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1906-00091.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}