  Over the last years, the computational power of mobile devices such as
smartphones and tablets has grown dramatically, reaching the level of desktop
computers available not long ago. While standard smartphone apps are no longer
a problem for them, there is still a group of tasks that can easily challenge
even high-end devices, namely running artificial intelligence algorithms. In
this paper, we present a study of the current state of deep learning in the
Android ecosystem and describe available frameworks, programming models and the
limitations of running AI on smartphones. We give an overview of the hardware
acceleration resources available on four main mobile chipset platforms:
Qualcomm, HiSilicon, MediaTek and Samsung. Additionally, we present the
real-world performance results of different mobile SoCs collected with AI
Benchmark that are covering all main existing hardware configurations.
