Developing CPU-GPU Embedded Systems Using Platform-Agnostic Components

Nowadays, there are many embedded systems with different architectures that have incorporated GPUs. However, it is difficult to develop CPU-GPU embedded systems using component-based development (CBD), since existing CBD approaches have no support for GPU development. In this context, when targeting a particular CPU-GPU platform, the component developer is forced to construct hardware-specific components, which are problematic to (re-)use in different contexts. Moreover, hard-coding specific GPU-usage characteristics (e.g., the number of utilized GPU threads) inside the component is not possible without making detailed assumptions about the system in which the component is used, which conflicts with separation-of-concerns CBD principle.The paper presents a solution to allow component-based development of platform-agnostic CPU-GPU embedded systems through: i) high-level API, ii) adapters, and iii) code template. The API abstracts the specifics of the different platforms, while the adapters externalize hardware-specific activities outside components. We also raise the decision regarding the GPU-usage specifications, from the component to the system level. Furthermore, to minimize the development effort, we provide a code template that contains ready-made code fragments required for GPU development. As a case study, we examine the feasibility of our solution applied on a component-based vision system of an underwater robot.