Modeling Software Contention Using Colored Petri Nets

Commercial servers, such as database or application servers, often attempt to improve performance via multi-threading. Improper multi-threading architectures can incur contention, limiting performance improvements. Contention occurs primarily at two levels: (1) blocking on locks shared between threads at the software level and (2) contending for physical resources (such as the cpu or disk) at the hardware level. Given a set of hardware resources and an application design, there is an optimal number of threads that maximizes performance. This paper describes a novel technique we developed to select the optimal number of threads of a target-tracking application using a simulation-based colored Petri nets (CPNs) model. This paper makes two contributions to the performance analysis of multi-threaded applications. First, the paper presents an approach for calibrating a simulation model using training set data to reflect actual performance parameters accurately. Second, the model predictions are validated empirically against the actual application performance and the predicted data is used to compute the optimal configuration of threads in an application to achieve the desired performance. Our results show that predicting performance of application thread characteristics is possible and can be used to optimize performance.