Speeding up TensorFlow Cifar10 Example for Experimentation
Note that this exercise only speeds up the first step time by skipping the prefetching of a larger from of the data. This exercise does not speed up the overall training
That said, the tutorial text needs to be updated. It should read 

Search for min_fraction_of_examples_in_queue in cifar10_input.py.

If you lower this number, the first step should be much quicker because the model will not attempt to prefetch the input.
The TensorFlow tutorial for using CNN for the cifar10 data set has the following advice:
EXERCISE: When experimenting, it is sometimes annoying that the first training step can take so long. Try decreasing the number of images that initially fill up the queue. Search for NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN in cifar10.py.
In order to play around with it, I tried decreasing this number by a lot but it doesn't seem to change the training time. Is there anything I can do? I tried even changing it to something as low as 5 and the training session still continued very slowly. 
Any help would be appreciated!