Performance prediction using simulation of large-scale interconnection networks in POSE

Parallel discrete event simulation (PDES) of models with fine-grained computation remains a challenging problem. We explore the usage of POSE, our parallel object-oriented simulation environment, for application performance prediction on large parallel machines such as BlueGene. This study involves the simulation of communication at the packet level through a detailed network model. This presents an extremely fine-grained simulation: events correspond to the transmission and receipt of packets. Computation is minimal, communication dominates, and strong dependencies between events result in a low degree of parallelism. There is limited look-ahead capability since the outcome of many events is determined by the application whose performance the simulation is predicting. Thus conservative synchronization approaches are challenging for this type of problem. We present recent experiences and performance results for our network simulator and illustrate the utility of our simulator through prediction and validation studies for a molecular dynamics application.