what does `a factor of K-fold` mean in GPU-based training? From the book "Deep Learning and Convolutional Neural Networks for Medical Image Computing"


  As we learned about the current state of research on deep learning, I
  was surprised to find that other investigators had used convolutional
  neural networks, one type of deep learning, in the past [22, 23]. But
  there seemed to be something different about the most recent crop of
  deep learning algorithms. They routinely used GPU processing to
  accelerate training by as much as a factor of 40-fold. They also used
  multiple convolution layers and multiple data reduction layers.


does 40-fold mean "K-Fold Cross-Validation"?
The author here refers to a comparison between older and most recent implementations of deep learning algorithms regarding execution time (accelerating processing speed). It just means that "they used GPUs and achieved x40 better execution time". It has nothing to do with K-Folds.