Project: datamanagement
Issue DM-2787: Footprint dilation performance regression
In DM-1128 we implemented span-based dilation for footprints. A brief test on synthetic data indicated that this was a performance win over the previous version of the code. In May 2015, this code was merged to HSC and applied to significant quantities of real data for the first time. A major performance regression was identified: {quote} [May-9 00:26] Paul Price: processCcd is now crazy slow. [May-9 00:29] Paul Price: Profiling... [May-9 00:40] Paul Price: I'm thinking it's the Footprint grow code... [May-9 00:44] Paul Price: And the winner is…. Footprint construction: [May-9 00:44] Paul Price: 2 0.000 0.000 702.280 351.140 /home/astro/hsc/products/Linux64/meas_algorithms/HSC-3.8.0/python/lsst/meas/algorithms/detection.py:191(makeSourceCatalog)  2 0.005 0.002 702.274 351.137 /home/astro/hsc/products/Linux64/meas_algorithms/HSC-3.8.0/python/lsst/meas/algorithms/detection.py:228(detectFootprints)  15 0.001 0.000 698.597 46.573 /home/pprice/hsc/afw/python/lsst/afw/detection/detectionLib.py:3448(__init__)  15 698.596 46.573 698.596 46.573 {_detectionLib.new_FootprintSet} [May-9 00:53] Paul Price: If I revert HSC-1243 ("Port better Footprint-grow code from LSST"), then the performance regression goes away. @jbosch @jds may be interested... {quote} The source of the regression must be identified and resolved for both HSC and LSST.
Story points: 5