Abstract: Three parallel discrete-event simulators-synchronous, conservative and optimistic-implemented on an Intel Paragon multicomputer are comparatively evaluated. Parallelism is achieved by model decomposition, distributing the simulation among a set of collaborative logical processes. The three simulators differ in the way those processes synchronize to obey causal restrictions in the simulation of events. Message passing network models are used to study these simulation alternatives. A set of experiments are carried out to understand how model parameters influence simulator performance. Experimental evidence leads to the conclusion that the optimistic simulator is not a viable tool for the analysis of this kind of models. The opposite conclusion applies to the other two: if the workload assigned to each logical process is above a certain threshold then the synchronization overhead is comparatively low and the simulators perform and scale well up to a large number of processors. The performance threshold is influenced by some parameters of the simulated model (size of the network, load level and message length), as well as by the number of processors used by the simulators.