Motivation

massive data movements and computational complexity of DCNNs

• performance: CPU
• power consumption: GPU
• fine-grained computing and routing resources still limit the power efficiency and runtime reconfiguration: FPGA

Contributions

• a hybrid data reuse pattern for different layer sizes
• computing resources reconfigurable: a highly scalable and efficient mapping method
• a layer-based scheduling framework: optimization on both power efficiency and performance