Evaluation of DarkNet19 and DarkNet53 Inference Time on CPU, GPU, and FPGA

The Convolutional Neural Networks used in machine learning applications such as handwriting recognition, object detection, or speech recognition are dealing with large amounts of data, thus requiring high computing capabilities. To meet this need, various hardware solutions have been proposed and are being rapidly improved. Choosing a hardware platform that offers the most effective support, whether it's speed, accuracy, or power consumption, becomes very important. In this paper, the inference time for DarkNet19 and DarkNet53, two convolutional neuronal networks used in object detection, is evaluated on a selection of CPUs, GPUs, and FPGAs.