Snowflake: A Model Agnostic Accelerator for Deep Convolutional Neural Networks

@article{Gokhale2017SnowflakeAM,
  title={Snowflake: A Model Agnostic Accelerator for Deep Convolutional Neural Networks},
  author={Vinayak Gokhale and Aliasger Zaidy and Andre Xian Ming Chang and Eugenio Culurciello},
  journal={CoRR},
  year={2017},
  volume={abs/1708.02579}
}
Deep convolutional neural networks (CNNs) are the deep learning model of choice for performing object detection, classification, semantic segmentation and natural language processing tasks. CNNs require billions of operations to process a frame. This computational complexity, combined with the inherent parallelism of the convolution operation make CNNs an excellent target for custom accelerators. However, when optimizing for different CNN hierarchies and data access patterns, it is difficult… CONTINUE READING
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