Power-efficient data management for dynamic applications

In recent years, the semiconductor industry has turned its focus towards heterogeneous multi-processor platforms. They are an economically viable solution for coping with the growing setup and manufacturing cost of silicon systems. Furthermore, their inherent flexibility also perfectly supports the emerging market of interactive, mobile data and content services. The platform's performance and energy depend largely on how well the data-dominated services are mapped on the memory subsystem. A crucial aspect thereby is how efficient data is transferred between the different memory layers. Several compilation techniques have been developed to optimally use the available bandwidth. Unfortunately, they do not take the interaction between multiple threads running on the different processors into account, only locally optimize the bandwidth nor deal with the dynamic behavior of these applications. The contributions of this chapter are to outline the main limitations of current techniques and to introduce an approach for dealing with the dynamic multi-threaded of our application domain.