In recent computing systems, CPUs have encountered the situations in which they cannot meet the increasing throughput demands. To overcome the limits of CPUs in processing heavy tasks, especially for computer graphics, GPUs have been widely used. Therefore, the performance of up-to-date computing systems can be maximized when the task scheduling between the CPU and the GPU is optimized. In this paper, we analyze the system in the perspective of performance, energy efficiency, and temperature according to the execution methods between the CPU and the GPU. Experimental results show that the GPU leads to better efficiency compared to the CPU when single application is executed. However, when two applications are executed, the GPU does not guarantee superior efficiency than the CPU depending on the application characteristics.