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Work-in-progress : Prediction based convolution neural network acceleration

Yao, Yuan (author)
KTH,Elektronik
Lu, Zhonghai (author)
KTH,Elektronik
 (creator_code:org_t)
2017-10-15
2017
English.
In: Proceedings of the 2017 International Conference on Compilers, Architectures and Synthesis for Embedded Systems Companion, CASES 2017. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450351843
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Although intra-layer parallelism is commonly used to expedite CNN execution, it is difficult to achieve inter-layer parallelism because of data dependence between layers. In the paper, we propose a two-phase prediction and correction mechanism to break the data dependence between CNN layers so as to enable inter-layer parallelism. Our technique achieves one more order of magnitude (from the order of 10 to the order of 100) CNN acceleration compared to other three state-of-the-art GPU based CNN acceleration mechanisms.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)

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Yao, Yuan
Lu, Zhonghai
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ENGINEERING AND TECHNOLOGY
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and Embedded Systems
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Royal Institute of Technology

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