Peter Vajda, Research Manager at Facebook, presents the “Hardware-aware Deep Neural Network Design” tutorial at the May 2019 Embedded Vision Summit.
A central problem in the deployment of deep neural networks is maximizing accuracy within the compute performance constraints of embedded devices. In this talk, Vajda discusses approaches to addressing this challenge based on automated network search and adaptation algorithms. These algorithms not only discover neural network models that surpass state-of-the-art accuracy, but are also able to adapt models to achieve efficient implementation on diverse processing platforms for real-world applications.
