Developing a parallel discrete-event simulation from scratch requires an indepth knowledge of the mapping process from the physical model to the simulation model, and a substantial effort in coping with numerous parallelism issues in the underlying synchronization protocols adopted. The lack of software tools and environments to reduce the development effort significantly is a major hindrance in adopting parallel simulation technology. This paper presents an overview of the SPaDES (Structured Parallel Discrete-Event Simulation) scalable parallel simulation framework. We focus on the performance analysis of SPaDES/C++, an implementation of SPaDES on a distributed-memory Fujitsu AP3000 parallel computer. SPaDES/C++ hides the underlying complex parallel simulation synchronization and parallel programming details from the simulationist. We study various ways of improving SPaDES execution performance including periodic checkpointing of simulation states, aggregation of messages for logical processes that reside on the same physical processors, and increasing the computational granularity of run-time processes to reduce the costs of synchronization and communication. Our empirical results show that the SPaDES framework can deliver good speedup for applications with large problem size and is scalable.