multi-core support in scripting


I would like to know if global mapper supports multi-cores when using scripts.

I searched entire scripting reference documentation and haven't found anything about multi-core/multi-threaded support 

The thing is that we use script to load approx 500x500km elevation data and then grid it to lots of small 2x2km tiles and while the script works perfectly, the CPU load is always about 13% and it has 15 gigs of ram still left but it's taking forever compared to if it was able to use all cores..

according to  - it should support multi-core: (if gridding is meant by tiling)

Dramatically faster processing speeds by leveraging multiple cores, significantly reducing the processing time required for operations like contour generation, view-shed calculations, gridding, and re-projecting layers that cover a large area of the world.

or according to this: they are using 12 core CPU and exporting to DEM (which is what I do) has increased by 33% and takes only few minutes..

maybe these published information is misleading but I haven't found any more information about multi-core support in scripting

does anybody have some ideas how to force global mapper scripts use advantage of all cores?

I am using i7-7700k with 32 gigs of RAM



Best Answer

  • bmg_bobbmg_bob Global Mapper Programmer Posts: 1,726
    Answer ✓

    We added support for multiple cores during tiled (gridded) raster exports in version 18.0, but we have not yet implemented it for elevation grid exports.  It is on our list (item #18056), and is tentatively scheduled for implementation in version 19.  I have added your information to the request, and we will post a message on this thread when the status of the feature request changes.



  • mdekysmdekys Posts: 4
    thanks Bob, 

    do you have any estimation when version 19 will be available?

  • bmg_bobbmg_bob Global Mapper Programmer Posts: 1,726
    mdekys said:
    do you have any estimation when version 19 will be available?

    Our plan is to release it in September, 2017.

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