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Hardware-Aware Evolutionary Approaches to Deep Neural Networks

  • Lukas Sekanina,
  • Vojtech Mrazek,
  • Michal Pinos

摘要

This chapter gives an overview of evolutionary algorithm (EA) based methods applied to the design of efficient implementations of deep neural networks (DNN). We introduce various acceleration hardware platforms for DNNs developed especially for energy-efficient computing in edge devices. In addition to evolutionary optimization of their particular components or settings, we will describe neural architecture search (NAS)Neural Architecture Search (NAS) methods adopted to directly design highly optimized DNN architectures for a given hardware platform. Techniques that co-optimize hardware platforms and neural network architecture to maximize the accuracy-energy trade-offs will be emphasized. Case studies will primarily be devoted to NASNeural Architecture Search (NAS) for image classificationImage classification. Finally, the open challenges of this popular research area will be discussed.