2016-10-28 13:23 GMT+02:00 Peter Steinbach <[email protected]>:
> I second this request big time and would add zstd, if we are already trying
> out various encoders. ;)

This may not be of interest, and does not include zstd, but I'm
attaching an excerpt from some of the results I got when back when
doing our basic benchmarking of some algorithms (all lossless).

It was based on those that we settled on Blosc_LZ4HC at level 4, since
we were looking for very fast decompression times, while longer
compression times and slightly larger file size was acceptable up to
certain points. The gzip results are included mostly because that's
what we were using at the time and I wanted them as a comparison, but
we knew we wanted something else. The input for those benchmarks was a
500x300x300 float dataset containing a tomographic 3D image.

I might try to dig up the script I used for the benchmark and see if
we still have the input I used, and do a test with lossy ZFP. It could
be very interesting for creating 3D "thumbnails" in our application.

Elvis

>
> P
>
>
> On 10/28/2016 01:12 PM, Elvis Stansvik wrote:
>>
>> 2016-10-28 1:53 GMT+02:00 Miller, Mark C. <[email protected]>:
>>>
>>> Hi All,
>>>
>>> Just wanted to mention a new HDF5 floating point compression plugin
>>> available on github...
>>>
>>> https://github.com/LLNL/H5Z-ZFP
>>>
>>> This plugin will come embedded in the next release of the Silo library as
>>> well.
>>
>>
>> Thanks for the pointer. That's very interesting. I had not heard about
>> ZFP before. The ability to set a bound on the error in the lossless
>> case seems very useful.
>>
>> Do you know if there has been any comparative benchmarks of ZFP
>> against other compressors?
>>
>> After some basic benchmarking, we recently settled on Blosc_LZ4HC at
>> level 4 for our datasets (3D float tomography data), but maybe it
>> would be worthwhile to look at ZFP as well..
>>
>> Best regards,
>> Elvis
>>
>>>
>>> --
>>> Mark C. Miller, LLNL
>>>
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>>
>>
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>
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