Before revision:  Based on our application-driven analysis , we have identified several performance bottlenecks for mobile applications powered by on-device deep learning inference .
After revision:  Our measurement and analysis suggest that on-device inference can cost up to two orders of magnitude greater response time and energy when compared to cloud-based inference, and that loading model and computing probability are two performance bottlenecks for mobile applications powered by on-device deep learning inference .