[gradsusr] Performance Tips

[Jennifer M Adams]

Does lats4d write out netcdf4?

On Feb 14, 2016, at 3:36 PM, dan martin <sailmaui at gmail.com<mailto:sailmaui at gmail.com>> wrote:

I am not using the 1k data, but I have the same i/o speed issues with the nested nam conus. I've optimized by converting to netcdf. I download the grib2 and run g2ctl and gribmap. Then lats4d to convert to netcdf. This makes a lat/lon file and de-compresses the grib2. This is substantially faster than dealing with grib2 and pdef.

Here is a live example:

http://www.meteogram.com/servlet/metChart?zoom=20&gs=wrfradar&tau=2&lat=38.83&lon=-77.31&units=e

You can change the chart by adjusting the inputs. The zoom is roughly the longitude domain in degrees. As shown the larger the domain the longer it takes to load. If you change that to 50 and then to 5 you'll notice the speed difference. Overall it is fine for my needs. If I left it grib2 and pdef, it takes too long.

Dan




On Tue, Feb 9, 2016 at 12:37 PM, Travis Wilson - NOAA Federal <travis.wilson at noaa.gov<mailto:travis.wilson at noaa.gov>> wrote:
Hi All,

Attached is a very short ppt on grads performance vs python using grib files.  In most cases, grads blows python away.  Times are relative to our machine and consider everything from starting grads/opening the file, to closing the file.

- In particular we have found that shaded1 is much faster.  Up to 40% faster on our machines.
- Wesley Ebisuzaki recommended converting the grib files to a lat/lon grid to eliminate the PDEF entry to significantly speed up the opening time of high resolution grib files. http://gradsusr.org/pipermail/gradsusr/2016-January/039339.html
- Again noted by Wesley, grib packing can have an impact on performance http://gradsusr.org/pipermail/gradsusr/2010-May/027683.html

One thing we show in the ppt is that as the view gets wider (i.e. the number of points that are plotted increase), the slower grads is relative to python.  At some point, python will become faster.   Anyways, to battle with this, regridding (using the re() function) the data within grads significantly speeds up the plotting time (see last slide) when you have a lot of points.  As far as I know, you can’t use re() in grads 2.1a3.  You do have lterp() but a grid is needed.  Is there anything that will allow me to lterp to my image dimensions?  Say my image dimensions are x800 y600 then lterp would interpolate my high resolution grib file to x800 y600 (or some multiple of) when a view exceeds 800 points across.  This will significantly speed up the plotting time when viewing a wide view of a high resolution grib file while not degrading the image quality by much (again, see last slide).

Also, if anyone has other performance tips on plotting high resolution grib files we would love to hear them.

Thanks,
Travis

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--
Jennifer Miletta Adams
Center for Ocean-Land-Atmosphere Studies (COLA)
George Mason University



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