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"Tensor processing primitives: a programming abstraction for efficiency and ..."

Evangelos Georganas et al. (2021)

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DOI: 10.1145/3458817.3476206

access: closed

type: Conference or Workshop Paper

metadata version: 2024-04-08

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  dblp key:
  - conf/sc/GeorganasKAAABB21
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  persistent URL:
  - https://dblp.org/rec/conf/sc/GeorganasKAAABB21
Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke:
Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. SC 2021: 14

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