Breaking down the parallel time into work, idleness, and overheads is crucial for assessing the performance of HPC applications, but difficult to measure in asynchronous dependent tasking runtime systems. No existing tools allow its measurement portably and accurately. This paper introduces POT: a tool-suite for dependent task-based applications performance measurement. We focus on its low-disturbance methodology consisting of task modeling, discrete-event tracing, and post-mortem simulation-based analysis. It supports the OMPT standard OpenMP specifications. The paper evaluates the precision of POT’s parallel time breakdown analysis on LLVM and MPC implementations and shows that measurement bias may be neglected above \(16\, \upmu \) s workload per task, portably across two architectures and OpenMP runtime systems