High-dimensional torus networks are becoming common in flagship HPC systems, with five of the top ten systems in June 2014 having networks with more than three dimensions. Although such networks combine performance with scalability at reasonable cost, the challenge of how to achieve optimal performance remains. Tools are needed to help understand how well the traffic is distributed among the many dimensions. This involves not only capturing network traffic but also its comprehensible visualization. However, visualizing such networks requires projecting multiple dimensions onto a two-dimensional screen, which is naturally challenging. To tackle this problem, in this position paper, we propose a visualization technique which can display traffic on torus networks with up to six dimensions. Our fundamental approach is to simultaneously present multiple views of the same network section, with each view visualizing different dimensions. Furthermore, we leverage the multiple-coordinate system concept and combine it with a customized polygon view to provide both a global and a zoomed-in perspective of the network. By interactively linking all the views, our technique makes it possible to analyze how the communication pattern of an application is mapped onto a network.