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Zhihao Jia
,
Oded Padon
,
James J. Thomas
,
Todd Warszawski
,
Matei Zaharia
,
Alex Aiken
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1145/3341301.3359630
· OA: W2981758446
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1145/3341301.3359630
· OA: W2981758446
Existing deep neural network (DNN) frameworks optimize the computation graph of a DNN by applying graph transformations manually designed by human experts. This approach misses possible graph optimizations and is difficult to scale, as new DNN operators are introduced on a regular basis.
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