Growing and executable system architecture has a significant role in successful production of large and distributed systems. Assessing the effect of different decisions in architecture design can decrease the time and cost of software production, especially when these decisions are related to non-functional properties of system. Performance is a non-functional property which relates to timing behaviour of system. In this paper we propose an approach for modelling and analysis of performance in architecture level. To do this, we follow a general process which needs two formal notations for specifying architecture and performance models of system. In this paper we show how Stochastic Process Algebra (SPA) in the form of PEPA language can be used for performance modelling and analysis of software architectures modelled using Graph Transformation System (GTS). To enable architecture model for performance analysis, equivalent PEPA model should be constructed with transformation. Transformed performance model of the architecture has been analysed through PEPA toolkit for some properties like throughput, sensitivity analysis, response time and utilisation rate. The analysis results have been explained with regard to a realistic case study.
