Optimizing Power and Performance For Machine Learning at the Edge Model Deployment Overview, Arm

Neural Networks have seen tremendous success in interpreting the signals from our physical world, such as vision, voice, and vibration. However, the unprecedented intelligence brought by the neural networks only becomes significant when we deploy them on ubiquitous mobile and IoT devices. Resource constraints of hardware and diverse ML features call for a new and critical component on top of the traditional endtoend development process: model optimization and deployment. We envision that efficient ML infe