2016-10-28 16:33 GMT+02:00 Francesc Alted <[email protected]>:
> 2016-10-28 13:59 GMT+02:00 Elvis Stansvik <[email protected]>:
>>
>> 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.
>
>
> Zstd was included in Blosc a while ago:
>
> http://blosc.org/blog/zstd-has-just-landed-in-blosc.html
>
> and its performance really shines, even on real data:
>
> http://alimanfoo.github.io/2016/09/21/genotype-compression-benchmark.html
>
> (although here, being only integers of 1 byte, only the BITSHUFFLE filter is
> used, but not the faster SHUFFLE).
>
> As Blosc offers the same API for a number of codecs, trying it in
> combination with Zstd should be really easy.

Zstd indeed looks very well-balanced. The reason I didn't include it
back when I did those benchmarks was that we were really focused on
decompression speed in our application, compression speed was very
much secondary. So I included mostly LZ4 codecs.

>
>>
>> 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.
>
>
> It would be nice if your benchmark code (and dataset) can be made publicly
> available so as to serve to others as a good comparison.

The dataset is unfortunately confidential and not something I can
release. I'm attaching the script I used though, it's very simple.

But, a disclaimer: The benchmarks I did were not really thorough. They
were also internal and never really meant to be published. It was
mostly a quick and dirty test to see which of these LZ4 codecs would
be in the right ballpark for us.

Elvis

>
>>
>>
>> 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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>
>
>
> --
> Francesc Alted
>
> _______________________________________________
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