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Scavenging Run-time Resources to Boost Utilization in Component-based Embedded Systems with GPUs


Publication Type:

Journal article


International Journal on Advances in Software


Many modern embedded systems with GPUs are required to process huge amount of data that is sensed from their environment. However, due to some inherent properties of these systems such as limited energy, computation and storage resources, it is important that the resources should be used in an efficient way. For example, camera sensors of a robot may provide low-resolution frames for positioning itself in an open environment and high-resolution frames to analyze detected objects. In this paper, we introduce a method that, when possible, scavenges the unused resources (i.e., memory and number of GPU computation threads) from the critical functionality and distributes them to the non-critical functionality. As a result, the overall system performance is improved without compromising the critical functionality. The method uses a monitoring solution that checks the utilization of the system resources and triggers their distribution to the non-critical functionality whenever possible. As a proof of concept, we realize the proposed method in a state-of-the-practice component model for embedded systems. As an evaluation, we use an underwater robot case study to evaluate the feasibility of the proposed solution.


author = {Gabriel Campeanu and Saad Mubeen},
title = {Scavenging Run-time Resources to Boost Utilization in Component-based Embedded Systems with GPUs},
volume = {11},
number = {1{\&}2},
pages = {159--169},
month = {June},
year = {2018},
journal = {International Journal on Advances in Software},
url = {}