An Approach of Feed-Forward Neural Network Throughput-Optimized Implementation in FPGA

Rihards Novickis, Daniels Jānis Justs, Kaspars Ozols, Modris Greitāns
2020 Electronics  
Artificial Neural Networks (ANNs) have become an accepted approach for a wide range of challenges. Meanwhile, the advancement of chip manufacturing processes is approaching saturation which calls for new computing solutions. This work presents a novel approach of an FPGA-based accelerator development for fully connected feed-forward neural networks (FFNNs). A specialized tool was developed to facilitate different implementations, which splits FFNN into elementary layers, allocates computational
more » ... cates computational resources and generates high-level C++ description for high-level synthesis (HLS) tools. Various topologies are implemented and benchmarked, and a comparison with related work is provided. The proposed methodology is applied for the implementation of high-throughput virtual sensor.
doi:10.3390/electronics9122193 fatcat:kv7lzpqhrfhohjawuxq4mpwq7a