Adaptive distributed parallel training method for a deep learning model based on dynamic critical paths of dag

HIGHLIGHTS

• who: Yan Zeng et al. from the School of Computing Science, Hangzhou Danzi University, Hangzhou, China have published the Article: Adaptive Distributed Parallel Training Method for a Deep Learning Model Based on Dynamic Critical Paths of DAG, in the Journal: Mathematics 2022, 10, 4788. of /2022/
• what: The authors propose an adaptive based on the dynamic generation of critical DAG (directed acyclic graph) paths called FD-DPS to solve this efficiency problem. The experiments show that FD-DPS can achieve 12.76% and 11.78% faster on PnasNet_mobile and ResNet_200 models respectively compared with the . . .
  

   

  

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