Hi Steven,
On Mar 3, 2010, at 1:12 PM, steven e. pav wrote:
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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?
The latter will probably have somewhat better performance. However, it
is much more important to align your hyperslabs with your chunk boundaries. If
you can't align the hyperslabs & chunk boundaries, you should increase your
chunk cache size to hold several chunks in memory.
Quincey
> thanks,
>
>
>
> - --sep
>
>
> [ Steven E. Pav {bikes/bitters/linux} nerd ]
> [ a palindrome: stacks ask cats ]
>
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