This paper studies the interactive visualization and post-mortem analysis of execution traces generated by task-parallel programs. We focus on the detection of performance anomalies inaccessible to state-of-the-art performance analysis techniques, including anomalies deriving from the interaction of multiple levels of software abstractions, anomalies associated with the hardware, and anomalies resulting from interferences between optimizations in the application and run-time system. Building on our practical experience with the performance debugging of representative task-parallel applications and run-time systems for dynamic dependent task graphs, we designed a new tool called Aftermath. This tool enables the visualization of intricate anomalies involving multiple layers and components in the system. It also supports filtering, aggregation and joint visualization of key metrics and performance indicators, such as task duration, run-time state, hardware performance counters and data transfers. The tool also relates this information to the machine's topology. While not specifically designed for non-uniform memory access (NUMA) architectures, Aftermath takes advantage of the explicit memory regions and dependence information in dependent task models to precisely capture long-distance and inter-core effects. Aftermath supports traces of up to several gigabytes, with fast and intuitive navigation and the on-line configuration of new derived metrics. As it has proven invaluable to optimize both run-time environments and applications, we illustrate Aftermath on genuine cases encountered in the OpenStream project.