EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization. (arXiv:2202.10935v1 [cs.LG])

Conventionally, DNN models are trained once in the cloud and deployed in edge
devices such as cars, robots, or unmanned aerial vehicles (UAVs) for real-time
inference. However, there are many cases that require the models to adapt to
new environments, domains, or new users. In order to realize such domain
adaption or personalization, the models on devices need to be continuously
trained on the device. In this work, we design EF-Train, an efficient DNN
training accelerator with a unified channel-level …

arxiv cnn data personalization training