Snowflake: A Model Agnostic Accelerator for Deep Convolutional Neural Networks

Understand

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 for custom accelerators to achieve close to 100% computational efficiency.