Abstract
Many modern programmable embedded devices contain CPUs and a GPU that share the same system memory on a single die. Such a unified memory architecture (UMA) allows programmers to implement different communication models between CPU and the integrated GPU (iGPU). Although the simpler model guarantees implicit synchronization at the cost of performance, the more advanced model allows, through the zero-copy paradigm, the explicit data copying between CPU and iGPU to be eliminated with the benefit of significantly improving performance and energy savings. On the other hand, the robot operating system (ROS) has become a de-facto reference standard for developing robotic applications. It allows for application re-use and the easy integration of software blocks in complex cyber-physical systems. Although ROS compliance is strongly required for SW portability and reuse, it can lead to performance loss and elude the benefits of the zero-copy communication. In this article we present efficient techniques to implement CPU–iGPU communication by guaranteeing compliance to the ROS standard. We show how key features of each communication model are maintained and the corresponding overhead involved by the ROS compliancy.
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