Comments (3)
Sure. If it works well for your case it's all good. I usually do something like this to control memory, cache (75% memory), and cores:
['-J-Xmx32G', '-c', '24G', '-q', '32']
I'll release this fix with the next version in the coming days.
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Hi @griembauer thanks for reaching out and reporting this. The linked PR should fix it.
I was looking at your parameterization (I replaced the t_srs
value with the EPSG code):
kwargs = {
't_srs': 2157,
'returnWF': True,
'terrainFlattening': True,
'refarea': 'gamma0',
'export_extra': ['layoverShadowMask'],
'outdir': '/data/s1_results_timeline_extension/tests',
'speckleFilter': None,
'spacing': 20.0,
'externalDEMFile': '/data/dem/ireland_dem_20m_int.tif',
'externalDEMNoDataValue': None,
'externalDEMApplyEGM': True,
'alignToStandardGrid': True,
'demResamplingMethod': 'BILINEAR_INTERPOLATION',
'imgResamplingMethod': 'BILINEAR_INTERPOLATION',
'standardGridOriginX': 400900.0,
'standardGridOriginY': 1002740.0,
'clean_edges': True,
'polarizations': ['VV', 'VH'],
'scaling': 'dB',
'groupsize': 999,
'gpt_args': ['-x', '-c', '8G', '-q', '1'],
'tmpdir': '/data/temp_dir_calculations',
'shapefile': '/data/grassdata/loc_2157/PERMANENT/.tmp/b64d9297e23a/1025.0.geojson'
}
I highly recommend increasing the number of cores and the memory with gpt_args
. What you have defined is likely not enough for processing. Furthermore, splitting the workflow via groupsize
helps a lot for requiring fewer resources.
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Great, thanks a lot for the quick help and recommendations! For the limited AOI I have, the configuration works well, but I guess I am a bit too cautious to give SNAP/GPT a lot of resources ;) I will experiment with multiple cores and the groupsize
parameter!
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