3 papers
cs.LG2020
Automated Design Space Exploration for optimised Deployment of DNN on Arm Cortex-A CPUs
Miguel de Prado, Andrew Mundy, Rabia Saeed +3
The spread of deep learning on embedded devices has prompted the development of numerous methods to optimise the deployment of deep neural networks (DNN). Works have mainly focused…
cs.CV2018
Learning to infer: RL-based search for DNN primitive selection on Heterogeneous Embedded Systems
Miguel de Prado, Nuria Pazos, Luca Benini
Deep Learning is increasingly being adopted by industry for computer vision applications running on embedded devices. While Convolutional Neural Networks' accuracy has achieved a m…
cs.NE2018
QUENN: QUantization Engine for low-power Neural Networks
Miguel de Prado, Maurizio Denna, Luca Benini +1
Deep Learning is moving to edge devices, ushering in a new age of distributed Artificial Intelligence (AI). The high demand of computational resources required by deep neural netwo…