There are significant opportunities for the development of parallel/distributed simulation algorithms in the context of parametric study of discrete event systems. In such studies, simulation of multiple (often a large number of) parametric variants is required in order to, for example, identify significant parameters (factor screening), determine directions for response improvement (gradient estimation), find optimal parameter settings (response optimization), or construct a model of the response (meta-modeling). The computational burden in this case is to a large extent due to the large number of alternatives that need to be simulated. An effective strategy in this context is to concurrently simulate a number of parametric variants: the structural similarity of the variants often allows for significant amount of sharing of the simulation work, and the code for concurrent simulation of the variants can often be implemented in a parallel/distributed environment. In this paper, we describe two methods of parallel/distributed/concurrent simulation called the standard clock (SC) and the general shared clock (GSC) simulation. Both approaches rely on an event-reservation approach: by contrast to most discrete-event simulation approaches that are based on an event-scheduling approach, in the SC and GSC simulation, the occurrence instances of all events are reserved on the time axis. These instances may or may not be used. This event-reservation approach frees the clock mechanism of the simulation from needing feedback from the state-update mechanism. Due to this autonomy of the clock mechanism, a single clock can be used to drive a number (possibly large) of variants concurrently and in parallel. The autonomy of the clock mechanism is also the key to the different implementation strategies we adopt. To illustrate, we describe the simulation of parametric versions of wireless communication networks on message passing and shared memory environments.