The dependence list in time warp

Time Warp is known for its ability to maximize the exploitation of the parallelism inherent in a simulation. However, this potential has been undermined by the cost of processing causality violations. Minimizing this cost has been one of the most challenging issues facing Time Warp. In this paper, we present dependence list cancellation, a direct cancellation technique for Time Warp which is intended for use in a distributed memory environment such as a network of workstations. This approach provides for the swift cancellation of erroneous events, thereby preventing the propagation of their (erroneous) descendants. The dependence list also provides an event filtering function which detects erroneous future events, and also reduces the number of anti-messages used in the simulation. Our experimental work indicates that dependence list cancellation results in a dramatic reduction in the time required to process causality violations in Time Warp.