Reducing the time-to-market factor is a challenge for many embedded systems designers. In that respect, hardwaresoftware partitioning is a key issue which has been studied during the last two decades. In this paper we present an extension to recent works dealing with metrics for guiding the hardware-software partitioning step. This extension builds upon and complement our own work with metrics in the Design Trotter project, and is combined with the affinity metric approach. We show that the proposed extension improves the original affinity metric in terms of parallelism detection, and thus can help system designers to make wiser hardware-software partitioning decisions, which in turn reduces the time-to-market factor.