ROSGM: A Real-Time GPU Management Framework with Plug-In Policies for ROS 2

Robot Operating System (ROS) is a prevailing software framework for robotic application development. Graphics Processing Unit (GPU) is widely used in many ROS applications as a first-order computation resource. Unfortunately, ROS does not do any resource management for GPU, and different components in a ROS application directly submit their GPU workload without coordinating with each other, which may cause severe problems in both general performance and real-time capability. This paper presents ROSGM, a real-time ROS 2 GPU Management framework. Instead of providing a fixed GPU management policy for all scenarios, ROSGM allows the addition of any management policy as a plug-in and dynamic switching among different management policies at run-time, which is helpful since GPU management policies are typically device-dependent, and different applications or the same application in different modes may need different GPU management policies. Besides, ROSGM supports dynamic task loading and unloading for integrating additional functionalities when required at run-time. We conduct experiments to evaluate ROSGM. The results show that by properly managing the GPU resource using ROSGM, we can significantly improve the performance of ROS 2 applications. The flexibility of adding management policies as plug-ins, dynamic switching of management policies, and dynamic task loading and unloading helps improve the adaptability of ROSGM.