Resource-efficient ML for Edge and Endpoint IoT Devices

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May 2019

SeeDot is an automatic quantization tool that generates efficient machine learning (ML) inference code for IoT devices. ML models are usually expressed in floating-point, and IoT devices typically lack hardware support for floating-point arithmetic. Hence, running such ML models on…

Github for SeeDot

December 2018

Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One example of a ubiquitous real-world application where such models are desirable is resource-scarce devices and sensors in the Internet…

Github for Edge Machine Learning (Edge ML)