An observation in supercomputing in the past decade illustrates the transition of pervasive commodity products being integrated with the worldâ s fastest system. Given todayâ s exploding popularity of mobile devices, we investigate the possibilities for high performance mobile computing. Because parallel processing on mobile devices will be the key element in developing a mobile and computationally powerful system, this study was designed to assess the computational capability of a GPU on a low-power, ARM-based mobile device. The methodology for executing computationally intensive benchmarks on a handheld mobile GPU is presented, including the practical aspects of working with the existing Android-based software stack and leveraging the OpenCL-based parallel programming model. The empirical results provide the performance of an OpenCL Nbody benchmark and an auto-tuning kernel parameterization strategy. The achieved computational performance of the lowpower mobile Adreno GPU is compared with a quad-core ARM, an x86 Intel processor, and a discrete AMD GPU.