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.

本文研究了Android生态系统中深度学习的现状及其在智能手机上的限制，同时概述了四个主要移动芯片平台（Qualcomm、HiSilicon、MediaTek和Samsung）上可用的硬件加速资源，并介绍了利用AI基准测试收集的不同移动SoCs的实际性能结果。

AI基准测试：在Android智能手机上运行深度神经网络