design space exploration; statistical simulation; system level design
Application specific systems have potential for customization of design with a view to achieve a better cost-performance-power trade-off. Such customization requires extensive design space exploration. In this paper, we introduce a performance evaluation methodology for system-level design exploration that is much faster than traditional cycle-accurate simulation. The trade off is between accuracy and simulation speed. The methodology is based on probabilistic modeling of system components customized with application behavior. Performance numbers are generated by simulating these models. We have implemented our models using SystemC and validated these for uni-processor as well as multiprocessor systems against various benchmarks.