Journal article

Power aware data and memory management for dynamic applications

In recent years, the semiconductor industry has turned its focus towards heterogeneous multiprocessor platforms. They are an economically viable solution for coping with the growing setup and manufacturing cost of silicon systems. Furthermore, their inherent flexibility 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 into account and do not deal with the dynamic behaviour of these novel applications. The main limitations of current techniques are outlined and an approach for dealing with them is introduced.

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