Loading stack of images slow

I have about 20k 500px500p images stored in a directory.

My ultimate goal is to reshape them into only a few images, blocking the 500s into the few larger images.

I first wanted to see how fast I could load the images.
```
arr=dask_image.imread.imread('*.png')[:100].compute()
```
versus
```
from PIL import Image
arr=[Image.open(img) for img in glob.glob('*.png')[:100]]
```
The second task is performing much much much faster than the first task (first task hangs).

Can you help me understand why this is so and what I can do to speed this up?

Chunk size is (1,500,500,3) but I changed it to (25,500,500,3) and it didn't really make a difference. I would normally expect this to be a fast and easy Dask operation. I even started processing and threaded distributed clients with no luck.

Help is very much appreciated. Thanks!

No repository files or tests are named. Start by reproducing the dask_image.imread.imread('*.png')[:100].compute() and PIL comparison, then inspect the effects of the reported chunk sizes and threaded or distributed clients. Done means explaining the slowdown and identifying a validated way to make this image-loading workflow faster.

Written by the indexing model from the issue text.