The growing concerns of power efficiency, silicon reliability, and performance scalability motivate research in the area of adaptive embedded systems, i.e., systems endowed with decisional capacity, capable of online decision making so as to meet certain performance criteria. The scope of possible adaptation strategies is subject to the targeted architecture specifics, and may range from simple scenario-driven frequency/voltage scaling to rather complex heuristic-driven algorithm selection. This paper advocates the design of distributed memory homogeneous multiprocessor systems as a suitable template for the best exploiting adaptation features, thereby tackling the aforementioned challenges. The proposed solution lies in the combined use of a typical application processor for global orchestration along with such an adaptive multiprocessor core for the handling of data-intensive computation. This paper describes an exploratory homogeneous multiprocessor template designed from the ground up for scalability and adaptation. The proposed contributions aim at increasing architecture efficiency through smart distributed control of architectural parameters such as frequency, and enhanced techniques for load balancing such as task migration and dynamic multithreading.