ENH: Tag memory based on data shape, annotate T2SMap #2898
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commented
Dec 2, 2022
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@mgxd Do you have time for a review? |
mgxd
reviewed
Dec 7, 2022
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I haven't profiled. I think our general problem has been underestimating actual memory usage, but we don't have a documented process for assessing the quality of the estimation. I feel like I've seen some graphs from @soichih or @HippocampusGirl that show overall memory usage, but I'm not sure what tools they use. (If either of you have suggestions, please let us know!) Oscar pointed at nipreps/mriqc#984 for recent changes to profiling in MRIQC that we should adopt. |
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Changes proposed in this pull request
T2SMap was tagged with the default memory consumption (~100MB), when it should be based on the size of the input files. This implements #1100 in order to get a direct estimate of that, and then passes that along, with an additional factor based on the number of echos and a safety factor of 2.
Fixes #1100.
Fixes #2728.
Documentation that should be reviewed