A driver monitoring camera will be a valuable component when it comes to autonomous driving for levels 3 & 4. The camera is able to distinguish the area of the drivers' attention. For this purpose the estimation of the gaze of the driver is needed. Additionally to signal "eyes on road," the user experience for HMI can be significantly improved. We'll present a deep learning approach that trains a neural network in an end-to-end manner. Small patches of the eye serve as input to a convolution neural network. The tradeoff between a deep and shallow net is an important aspect when it comes to a commercial product. The massive use of GPUs can help to find the best tradeoff between accuracy and number of needed FLOPS as well as the best suited DNN architecture.