Feasibility of the Computation Task Offloading to GPGPU-enabled Devices in Mobile Cloud

Abstract

Smart mobile devices including smart phones and tablets have become one of the most popular devices in the personal computing environment. Users spend much time using smart mobile devices to the extent that it exceeds their time spent using PC. One of the major characteristics of applications used by users through smart mobile devices is that the applications in the field of entertainment like games and augmented reality require a great deal of computations. In order to deal with this, smart mobile devices began to be loaded with an application processor equipped with high performance GPU. In this study, the feasibility of having computation-intensive mobile applications to use the GPU resource of another GPGPU-enabled device in the same space for their computation tasks was verified. If benefits can be obtained in terms of the performance by having the high performance GPU of a remote device perform the complex computations that are currently performed on local device CPU, such an approach can be used as an essential technology for mobile clouds that can be established based on the mobile devices. In order to verify this, we not only implemented the game 'Reversi' using the Monte Carlo Tree Search (MCTS) algorithm but also implemented a remote GPU support framework to Android platform so that it supports task offloading to GPGPU-enabled remote mobile devices. The Reversi game offloads computationally heavy parts of the MCTS to a remote GPU through our remote GPU support framework. We compare its performance with the case where the MCTS was completely performed on a local CPU. The results of experiments showed that the winning rate dramatically increases when the remote GPU was used. This result indicates workload offloading between the mobile devices can be a meaningful approach for the mobile cloud implementation.