Impact of event scheduling on performance of time warp parallel simulations

In conventional parallel processing, the main objective of scheduling is to reduce the processor´s idle time. However, in Time Warp (TW), which is an optimistic parallel discrete event simulation approach, keeping the processors busy does not necessarily lead to good performance, since the processors may be performing erroneous computations that must be eventually rolled back. Hence, the existing knowledge on scheduling is not easily transferable to TW simulations. The main objective of this work is to study the impact of scheduling policies on performance of TW. We compare a dynamic scheduling scheme with a static one. Our experimental results indicate that the dynamic policy reduces rollback costs for small shared memory multiprocessors.<>