Successive dynamic time warping with a set of window sizes
Hmm

There are few properties to help you.

Let Wi be a warping window of width i

It is the case that DTW_wi(A,B) >= DTW_wi+1(A,B) 

Other than that, there is little to say.

If you have not already, you should read
http://www.cs.unm.edu/~mueen/DTW.pdf
and
http://www.cs.ucr.edu/~eamonn/CIKM_2016_DTW_clustering.pdf

If you are only interested in the smallest items in the matrix, then using lower bounds (the LB_Keogh) will give you an easy 100-fold speed up.