Architectural smells have been studied in the literature looking at several aspects, such as their impact on maintainability as a source of architectural debt, their correlations with code smells, and their evolution in the history of complex projects. The goal of this paper is to extend the study of architectural smells from a different perspective. We focus our attention on software performance and we aim to quantify the impact of architectural smells as support to explain the root causes of system performance hindrances. Our method consists of a study design matching the occurrence of architectural smells with performance metrics. We exploit state-of-the-art tools for architectural smell detection, software performance profiling and testing the systems under analysis. The removal of architectural smells generates new versions of systems from which we derive some observations on design changes improving/worsening performance metrics. Our experimentation considers two complex open-source projects, and results show that the detection and removal of two common types of architectural smells yield lower response time (up to 47%) with a large effect size (for 50%-90% of the hot spot methods). The median memory consumption is also lower (up to 40%) with a large effect size (for all the services).