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parallel: divide num_core by num_thread if available #691
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+ cluster.format_num_worker(): divide the number of cores by the number of threads if found [for linux only] using lscpu command + smallbaselineApp.plot_result(): translate numWorker = all + update API hierarchy of cluster.py as it now depends on utils0.py
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+ ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension + cluster.DaskCluster: - set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - revert "divide num core by num of threads per core" (insarlab#691) as it's not right. - translate numWorker = all to 80% of available cores, as it seems to work better on HPC
yunjunz
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+ ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension + cluster.DaskCluster: - set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - revert "divide num core by num of threads per core" (insarlab#691) as it's not right. - translate numWorker = all to 80% of available cores, as it seems to work better on HPC
yunjunz
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Nov 13, 2021
+ cluster.DaskCluster: - run(): set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - format_num_worker(): revert "divide num core by num of threads per core" (insarlab#691) as it's not right. - format_num_worker(): support num of workers in percentage, e.g. 80% to use 80% of all cores + ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension
yunjunz
added a commit
to yunjunz/MintPy
that referenced
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Nov 13, 2021
+ cluster.DaskCluster: - run(): set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - format_num_worker(): revert "divide num core by num of threads per core" (insarlab#691) as it's not right. - format_num_worker(): support num of workers in percentage, e.g. 80% to use 80% of all cores + ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension
5 tasks
yunjunz
added a commit
to yunjunz/MintPy
that referenced
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Nov 13, 2021
+ cluster.DaskCluster: - run(): set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - format_num_worker(): revert "divide num core by num of threads per core" (insarlab#691) as it's not right. - format_num_worker(): support num of workers in percentage, e.g. 80% to use 80% of all cores + ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension
yunjunz
added a commit
that referenced
this pull request
Nov 13, 2021
+ cluster.DaskCluster: - run(): set the num of scaled workers to the num of boxes, to avoid unnecessary resource initiation - format_num_worker(): revert "divide num core by num of threads per core" (#691) as it's not right. - format_num_worker(): support num of workers in percentage, e.g. 80% to use 80% of all cores + ifgram_inversion: use ceil instead of rint to prevent the occurrence of extra small patches. + cluster.split_box2sub_boxes: - add a min step size constrain - trim the final number of boxes, to avoid negative dimension
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Description of proposed changes
cluster.format_num_worker()
: divide the number of cores by the number of threads per core if found [for linux only] usinglscpu
command. Note again that this only affect the translation ofnumWorker = all
. Fix ifgram_inversion: dask failure with large number of workers #518.smallbaselineApp.plot_result()
: translatemintpy.compute.numWorker = all
. Fix plot & save to pic section of smallbaselineApp fails with "numWorker = all" #689update API hierarchy of
cluster.py
as it now depends onutils0.py
Reminders