In this paper, we address the problem of selecting the optimal number of processing cores and their operating voltage/frequency for a given workload, to minimize overall system power under application-dependent QoS constraints. Selecting the optimal system configuration is non-trivial, since it depends on task characteristics and system-level interaction effects among the cores. For this reason, our QoS-driven methodology for power aware partitioning and frequency selection is based on functional, cycle-accurate simulation on a virtual platform environment. The methodology, being application-specific, is demonstrated on the DES (Data Encryption System) algorithm, representative of a wider class of streaming applications with independent input data frames and regular workload.