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Parallelization #197
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Two performance tests on Google cloud, using 22 vCPU with 44GB RAM 10GB RAM was used as RAM disk using tmpfs, where the _tiles directory was placed, since I've found that it will increase the performance for the "Split filtered country files to tiles" part greatly. For Germany
For Great Britain
From CPU graphs, the "Split filtered country files to tiles" part seems to almost CPU bound, with 75% total CPU usage. So I think maybe the "Merge splitted tiles with land, elevation, and sea" part should be looked at first for improving performance, that part does not seem to be close to CPU bound currently. It would also be nice to have some performance numbers from others, to see where the main bottlenecks are. |
Currently prototyping this in #235 |
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Paralyze calls in each processing step of the threads do not occupy the same Ressource
Implement time measurement before to track it
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