Publication: PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation
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PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation

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Author(s)
Tim Kaler , Tao B. Schardl , Brian Xie , Charles E. Leiserson , Jie Chen , Aldo Pareja , Georgios Kollias

Published in
Proceedings of the Symposium on Algorithmic Principles of Computer Systems (APOCS)

Editor(s)
Schapira Michael

Year
2021

Publisher
Society for Industrial and Applied Mathematics

AD Theory and Techniques
Parallelism, Reverse Mode

BibTeX
@INPROCEEDINGS{
         Kaler2021PAW,
       author = "Tim Kaler and Tao B. Schardl and Brian Xie and Charles E. Leiserson and Jie Chen and
         Aldo Pareja and Georgios Kollias",
       title = "{PARAD}: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic
         Differentiation",
       booktitle = "Proceedings of the Symposium on Algorithmic Principles of Computer Systems
         (APOCS)",
       pages = "144--158",
       doi = "10.1137/1.9781611976489.11",
       url = "https://epubs.siam.org/doi/abs/10.1137/1.9781611976489.11",
       eprint = "https://epubs.siam.org/doi/pdf/10.1137/1.9781611976489.11",
       address = "Philadelphia, PA",
       publisher = "Society for Industrial and Applied Mathematics",
       editor = "Schapira Michael",
       year = "2021",
       ad_theotech = "Parallelism, Reverse Mode"
}


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