Run-time adaptable architectures for heterogeneous behavior embedded systems

As embedded applications are getting more complex, they are also demanding highly diverse computational capabilities. The majority of all previously proposed reconfigurable architectures targets static data stream oriented applications, optimizing very specific computational kernels, corresponding to the typical embedded systems characteristics in the past. Modern embedded devices, however, impose totally new requirements. They are expected to support a wide variety of programs on a single platform. Besides getting more heterogeneous, these applications have very distinct behaviors. In this paper we explore this trend in more detail. First, we present a study about the behavioral difference of embedded applications based on the Mibench benchmark suite. Thereafter, we analyze the potential optimizations and constraints for two different run-time dynamic reconfigurable architectures with distinct programmability strategies: a fine-grain FPGA based accelerator and a coarse-grain array composed by ordinary functional units. Finally, we demonstrate that reconfigurable systems that are focused to single data stream behavior may not suffice anymore.