Optimum use of resources in heterogeneous system architectures

Current High Performance Embedded Architectures offer architectural improvements over previous generations of embedded and desktop architectures. A Heterogeneous System Architecture constitutes the most fundamental difference. Thus introducing many powerful hardware accelerator blocks like a GPU or DSP. However, most application designers do not take into account the recent advantages of Heterogeneous System Architectures and therefore encounter performance problems. Heterogeneous System Architectures are suitable for processing large amounts of data like 4k-HD video at 30 frames per second (fps). In many cases, software frameworks are used which are not optimized for current architectures (i.e. all processing is done in the CPU). The GPU in such systems is merely used to drive display output. This leads to designs which do not fulfill the performance expectations. In video systems, this often shows in a very reduced frame rate. Described performance challenges can be solved by adapting the problem to the available system architecture. The paper will give real world examples. The solution to performance bottle necks could be to assess different parts of the implementation according to their impact on performance. In case certain tasks can be re-assigned to dedicated hardware blocks, valuable resources can be freed. However, using dedicated hardware blocks (for video these can be scalers, encoders, overlay) require additional communication, which may lead to an excessive amount of memory transfers. Capacity bottlenecks manifest in video systems with a very slow video frame rate (