In this paper, we present a functional partitioning method for low power real-time distributed embedded systems whose constituent nodes are systems-on-a-chip (SOCs). The system level specification is assumed to be given as a set of task graphs. The goal is to partition the task graphs so that each partitioned segment is implemented as an SOC and the embedded system is realized as a distributed system of SOCs. Unlike most previous synthesis and partitioning tools, this technique merges partitioning and system synthesis (allocation, assignment, and scheduling) into one integrated process; both are implemented within a genetic algorithm. Genetic algorithms can escape local minima and explore the partitioning and synthesis design space efficiently. Through integration with an existing SOC synthesis tool, the proposed partitioning technique satisfies both the hard real-time constraints and the SOC area constraint of each partitioned segment. Under these constraints, our tool performs multi-objective optimization. Thus, with a single run of the tool, it produces multiple distributed SOC-based embedded system architectures that trade off the overall distributed system price and power consumption. Experimental results show the efficacy of our technique.