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I am reading hyperslabs from a medium-sized gzip-compressed hdf5 file generated
by the 1.6.5 library; the dataset is around 1000 x 20000 x 20, and I am reading
around 1000 slabs of size 1000 x 1 x 20; the slabs are irregularly spaced. The
reads are somewhat slower than what I expected based on the performance for
a toy version of the problem. In my read algorithm, however, I am essentially
doing the following loop:
for each slab {
H5Sselect_hyperslab(space_id, H5S_SELECT_SET, start, stride, count, block)
H5Dread( etc )
}
should I expect better performance if instead, I construct a union of
hyperslabs, then do the read, like so:
initialize the slab as empty?
for each slab {
H5Sselect_hyperslab(space_id, H5S_SELECT_OR, start, stride, count, block)
}
H5Dread( etc )
which method is preferred, and why?
thanks,
- --sep
[ Steven E. Pav {bikes/bitters/linux} nerd ]
[ a palindrome: stacks ask cats ]
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