With increases of display resolution and graphical quality demands, global illumination techniques are sought after to meet such demands. However, global illumination algorithms have a long processing time on mobile devices, such as smartphones or tablet PCs. Besides the performance issue, the algorithms consume a large amount of battery-powered energy. The performance and energy consumption have a trade-off relationship. The dynamic voltage and frequency scaling (DVFS) algorithms control the balance between the performance and the energy consumption by adjusting the GPU and CPU’s frequencies. To improve the performance of the global illumination algorithm and reduce the high energy consumption of the current DVFS algorithm, we suggest new algorithms with new metrics for estimating the amount of workload for GPUs as well as their memory workload. Using our new DVFS algorithms, we increase the energy efficiency, the performance per watt, of a global illumination algorithm by 33.59% in comparison to a conventional general-purpose DVFS algorithm, without modifying the underlying algorithm core.