Hi Nicolas, You might also be interested in a new development discussed over the past couple of days on the PDAL list.
See http://lists.osgeo.org/pipermail/pdal/2015-June/000590.html Hope it helps, carl On Fri, Jun 5, 2015 at 4:13 PM, Even Rouault <even.roua...@spatialys.com> wrote: > Le samedi 06 juin 2015 00:18:45, Nicolas Cadieux a écrit : > > Hi, > > I have been using gdal_grid to interpolate LiDAR data for some time now. > > This would be a typical command: > > > > gdal_grid -l P0344_sol2004_XYZI_MTM8_CGVD28_150529 -txe 348733.0 401135.0 > > -tye 5568587.0 5773796.0 -a > > nearest:radius1=3.0:radius2=3.0:angle=0.0:nodata=0.0 -outsize 52402.0 > > 205209.0 -of GTiff > > H:/Nicolas/pytemp/OutPut\P0344_sol2004_XYZI_MTM8_CGVD28_150529.vrt > > H:/Nicolas/pytemp/OutPut\P0344_sol2004_XYZI_MTM8_CGVD28_150529.tif > --confi > > g GDAL_NUM_THREADS ALL_CPUS > > > > As you can see, this is a huge raster and the csv. file (Pointed with a > > .vrt) contains over a billion points. I am trying to do this in one shot > > to avoid boundary effects. (I know I can split this .csv file into > > smaller bits and make this more efficient). The computer I am using has > > 12 cores, 64BG of memory (smaller than the csv file) and a 1TB pcie solid > > state drive. It should manage the task but it has been running for 5 > days > > with less than 10% done). I have access to a super computer with gdal if > > all else fails. > > > > This is my question. The "--config GDAL_NUM_THREADS ALL_CPUS" or > "--config > > GDAL_NUM_THREADS 12" does not seem to work with the nearest neighbor > > algorithm. (It seem to work with the -a count command) If I use this on > a > > smaller data set, I see no difference in speed or cpu usage between using > > the "ALL_CPUS" or not using this switch. Is this a bug or simply a > > limitation of the nearest neighbor algorithm? > > Nicolas, > > The threading mechanism is generic for all algorithms . Add "--debug on" > and > you should see traces like "GDAL_GRID: Using 12 threads". Now, a reason > for it > not being efficient is that the work buffer used by gdalgrid (16 MB) is > too small > w.r.t to nearest speed. Hum, actually looking more closely at the code, I > see > that the quad tree to index the points will be rebuilt for each work > buffer. > This is likely the main cause of the inefficiency and why you don't see > measurable differences between non threaded or threaded computations > (since the > building of the quadtree is not multithreaded). If you compiled from > source, > you could try changing the "const GUInt32 nDesiredBufferSize = > 16*1024*1024;" > line in apps/gdal_grid.cpp to a much higher value. A more proper solution > would be to avoid rebuilding the quad tree for each work buffer. This is > mainly > code restructuring. > > An alternative to gdal_grid would be to use gdal_rasterize + > gdal_fillnodata. > This is usually much much faster, so you could try to check if it gives the > results you expect. > > You could also try scipy : > > http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.interpolate.griddata.html#scipy.interpolate.griddata > Not sure how it behaves with that number of points. > > Even > > > I don't want to move this > > to a super computer if it will not multi-thread properly. > > > > Thanks, > > Nicolas Cadieux > > > > (Gdal1.11.2 downloaded with OSGEO4W 64bit install with QGIS 2.8 on > windows > > 7_64) I use GDAL from the command line not from QGIS. > > > > > > Nicolas Cadieux M.Sc. > > Les Entreprises Archéotec inc. > > 8548, rue Saint-Denis Montréal H2P 2H2 > > Téléphone: 514.381.5112 Fax: 514.381.4995 > > www.archeotec.ca > > _______________________________________________ > > gdal-dev mailing list > > gdal-dev@lists.osgeo.org > > http://lists.osgeo.org/mailman/listinfo/gdal-dev > > -- > Spatialys - Geospatial professional services > http://www.spatialys.com > _______________________________________________ > gdal-dev mailing list > gdal-dev@lists.osgeo.org > http://lists.osgeo.org/mailman/listinfo/gdal-dev >
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