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Component-based development is a software engineering paradigm that canfacilitate the construction of embedded systems and tackle its complexities.The modern embedded systems have more and more demanding requirements. One wayto cope with such versatile and growing set of requirements is to employheterogeneous processing power, i.e., CPU-GPU architectures. The new CPU-GPUembedded boards deliver an increased performance but also introduce additionalcomplexity and challenges. In this work, we address the component-to-hardwareallocation for CPU-GPU embedded systems. The allocation for such systems ismuch complex due to the increased amount of GPU-related information. Forexample, while in traditional embedded systems the allocation mechanism mayconsider only the CPU memory usage of components to find an appropriateallocation scheme, in heterogeneous systems, the GPU memory usage needs also tobe taken into account in the allocation process. This paper aims at decreasingthe component-to-hardware allocation complexity by introducing a 2-layercomponent-based architecture for heterogeneous embedded systems. The detailedCPU-GPU information of the system is abstracted at a high-layer by compactingconnected components into single units that behave as regular components. Theallocator, based on the compacted information received from the high-levellayer, computes, with a decreased complexity, feasible allocation schemes. Inthe last part of the paper, the 2-layer allocation method is evaluated using anexisting embedded system demonstrator; namely, an underwater robot.

A Two-Layer Component-Based Allocation for Embedded Systems with GPUs