One of the challenges for the developer of highly-parallel MPI applications running on distributed high performance computing systems is to understand the complex behavior of their applications. It requires to identify inefficiencies, and to optimize them such that communication waiting times can be reduced. This task can only be accomplished with the help of elaborated tools that provide insight into the details of the application using an automatic analysis or an intuitive visualization approach. While the first can only target a specific problem domain, the latter allows humans to discuss performance problems with a broader view and from multiple perspectives. We present a new visualization technique for performance data of MPI applications based on circular hierarchies. It intuitively presents communication patterns and allows developers to correlate those with arbitrary performance metrics. A hierarchyaware layout increases scalability and helps to identify communication inefficiencies by analyzing and integrating the system's hardware topology. We discuss both our approach as well as its integration into the Score-P performance analysis work flow. Its applicability is presented with a real-world use case of the COSMO+SPECS+FD4 climate simulation code.