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System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of memories, or the mapping of application tasks to architectural resources, are considered. Simulation-based DSE, in which different design instances are evaluated using system-level simulations, typically are computationally costly. Even using high-level simulations and efficient exploration algorithms, the simulation time to evaluate design points forms a real bottleneck in such DSE. Therefore, the vast design space that needs to be searched requires effective design space pruning techniques. This paper presents and studies different strategies for interleaving fast but less accurate analytical performance estimations with slower but more accurate simulations during DSE. By interleaving these analytical estimations with simulations, our hybrid approach significantly reduces the number of simulations that are needed during the process of DSE. Experimental results have demonstrated that such hybrid DSE is a promising technique that can yield solutions of similar quality as compared to simulation-based DSE but only at a fraction of the execution time.