A combined analytical and simulation-based model for performance evaluation of a reconfigurable instruction set processor

Performance evaluation is a serious challenge in designing or optimizing reconfigurable instruction set processors. The conventional approaches based on synthesis and simulations are very time consuming and need a considerable design effort. A combined analytical and simulation-based model (CAnSO*) is proposed and validated for performance evaluation of a typical reconfigurable instruction set processor. The proposed model consists of an analytical core that incorporates statistics gathered from cycle-accurate simulation to make a reasonable evaluation and provide a valuable insight. Compared to cycle-accurate simulation results, CAnSO proves almost 2% variation in the speedup measurement.