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Simulation is becoming an increasingly important technique for what-if analysis in the context of (real-time) decision making applications. Consequently, quick delivery of simulation outputs to end-users (or applications) is a core objective. One approach for high performance simulation consists of exploiting parallel techniques, where the simulation model is partitioned into objects (or logical processes), concurrently executing events on different CPUs and/or multiple CPU-cores. For this type of simulation systems,a further run-time improvement arose from the exploitation of event uncertainty, both in time and space, which has lead to more flexible synchronization protocols. Although this approach can provide significant performance gains, one drawback is the risk of less reliable simulation results due to potential bias induced by the mechanisms for resolving the uncertainty, which are sometimes exclusively targeted to run-time effectiveness. In this article we focus on space uncertain simulation events in optimistic parallel simulation and introduce a mechanism that, compared to previous approaches, allows trading-off execution speed vs reliability of simulation results. In other words, our target is the achievement of high performance while controlling, at the same time, the bias introduced by space uncertainty on the simulation output.