Analytic performance model for speculative, synchronous, discrete-event simulation

Performance models exist that reliably describe the execution time and efficiency of parallel discrete-event simulations executed in a synchronous iterative fashion. These performance models incorporate the effects of processor heterogeneity, other processor load due to shared computational resources, application workload imbalance, and the use of speculative computation. This includes modeling the effects of predictive optimism, a technique for improving the accuracy of speculative assumptions. We extend these models to incorporate correlated workloads across the set of processors and validate the models with two different applications.