FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11390-021-1406-9.pdf
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3. LiKamWa R, Hou Y, Gao J, Polansky M, Zhong L. RedEye: Analog convnet image sensor architecture for continuous mobile vision. ACM SIGARCH Comput. Archit. News, 2016, 44(3): 255-266. https://doi.org/10.1145/3007787.3001164.
4. Qian Y, Woodland P C. Very deep convolutional neural networks for robust speech recognition. In Proc. the 2016 IEEE Spoken Language Technology Workshop, Dec. 2016, pp.481-488. https://doi.org/10.1109/SLT.2016.7846307.
5. Abdel-Hamid O, Mohamed A, Jiang H, Deng L, Penn G, Yu D. Convolutional neural networks for speech recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2014, 22(10): 1533-1545. https://doi.org/10.1109/TASLP.2014.2339736.
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