Cache detector module slices in FormatNXmx to avoid redundant HDF5 reads#881
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dwmoreau wants to merge 3 commits into
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Cache detector module slices in FormatNXmx to avoid redundant HDF5 reads#881dwmoreau wants to merge 3 commits into
dwmoreau wants to merge 3 commits into
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get_raw_data() was re-parsing the nxmx object tree and recomputing detector module slices on every call, triggering hundreds of thousands of HDF5 attribute reads for data_origin and data_size per dataset. Cache nxdata, nxdetector, and the module slices in _start(), where other static detector properties are already cached, and thread the precomputed slices through to the get_raw_data functions in nexus/__init__.py and FormatNXmxEigerFilewriter. Developed with assistance from Claude Code (claude-opus-4-6)
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Here's a little snippet you can run without running any processing to show the time savings of this PR: It's messy, but what it does is read a 4-img JF16M dataset (256 panels) and call get_raw_data 100 times, 25 times per image. It prints out the sum of the panels each time to verify it's the same on main and on the feature branch (which it is). On my computer it runs in ~24s on main and ~20s on the feature branch. |
phyy-nx
moved this from Need larger review
to In progress
in DIALS Spring Performance Updates
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get_raw_data() was re-parsing the nxmx object tree and recomputing detector module slices on every call, triggering hundreds of thousands of HDF5 attribute reads for data_origin and data_size per dataset. Cache nxdata, nxdetector, and the module slices in _start(), where other static detector properties are already cached, and thread the precomputed slices through to the get_raw_data functions in nexus/init.py and FormatNXmxEigerFilewriter.
Developed with assistance from Claude Code (claude-opus-4-6)