A CGRA-Based Approach for Accelerating Convolutional Neural Networks

@article{Tanomoto2015ACA,
  title={A CGRA-Based Approach for Accelerating Convolutional Neural Networks},
  author={Masakazu Tanomoto and Shinya Takamaeda-Yamazaki and Jun Yao and Yasuhiko Nakashima},
  journal={2015 IEEE 9th International Symposium on Embedded Multicore/Many-core Systems-on-Chip},
  year={2015},
  pages={73-80}
}
Convolutional neural network (CNN) is an emerging approach for achieving high recognition accuracy in various machine learning applications. To accelerate CNN computations, various GPU-based or application-specific hardware approaches have been recently proposed. However, since they require large computing hardware and absolute energy amount, they are not suitable for embedded applications. In this paper, we propose a novel approach to accelerate CNN computations using a CGRA (Coarse Grained… CONTINUE READING

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