A More Scalable Deep-learning Processing Unit For Depthwise Separable Convolution

Due to the excellent energy efficiency and real-time performance, FPGA has gradually become an important computing platform for CNN inference. However, most FPGA based Deep-learning Processing Units (DPU) are not scalable enough to cope with the rapid changes in both operator type and network structure of convolutional neural networks (CNNs). To solve this problem, we proposed the Dataflow Driven ...