Conferences and supporting programme
Machine Learning on Arm Cortex-M Microcontrollers
Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing and deploying neural network (NN) solutions on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.
--- Date: 26.02.2019 Time: 3:00 PM - 3:30 PM Location: Conference Counter NCC Ost