Automated analysis of multithreaded programs for performance modeling

ABSTRACTThe behavior of multithreaded programs is often difficult to understand and predict. Synchronization operations and limited computational resources combine to produce complex non-linear dependencies between a program's configuration parameters and its performance. Performance models are used to understand these dependencies. Such models are complex, and constructing them requires a solid understanding of the program's behavior. As a result, building models of complex applications manually is extremely time-consuming and error-prone. In this paper we demonstrate that such models can be built automatically. This paper presents our approach for automatically modeling multithreaded programs. Our framework uses a combination of static and dynamic analyses of a single representative run of a system to build a model that can then be explored under a variety of configurations. We show how the models are constructed and show they accurately predict the performance of various multithreaded programs, including complex industrial applications.