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leonarski_fandClaude Opus 5 4bdb229fb8 spot_finding: find connected components on the GPU
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The spot finder flagged strong pixels on the device and then labelled them on the
host, so every frame sent the packed bitmask back - 2.26 MB on a large detector -
and the host walked all of it to recover a few hundred pixels. Do the labelling on
the device instead: compact the bitmask into a flat-index-sorted list, find each
pixel's backward neighbours by binary search, union them lock-free with path
halving, then label, accumulate and filter in one kernel. Only the spot list comes
back, and only one stream synchronisation per frame.

The gain in the ordinary case is modest - about a quarter off per-image spot
finding - because the host algorithm is genuinely fast on a normal frame. What
justifies it is the frame that is not ordinary. The host labels a sorted sparse
list through a window spanning two detector lines, so its cost is quadratic in how
many strong pixels share a line. A lit band of detector rows - a hot module, a
panel edge - costs 33 ms at two rows and 377 ms at fifteen, all of it under the
pixel cap that was supposed to bound this, and none of it maskable when the cause
is a diffraction ring rather than a defect: a ring runs tangent to a row at its
top and bottom, which is exactly the shape that hurts. The device version is flat
at 0.05 to 0.64 ms across every geometry tried, so an online run no longer stalls
a quarter of a second on an ice ring. Rejecting an over-cap frame is now free too,
since the count is known before any pixel is written.

Also label once and filter three times. The per-image minimum-pixel search runs the
extraction at three settings, but that setting only decides which components are
kept - it does not change the components - so the search itself need not be
repeated. This helps the host path as much as the device one.

The resolution mask moves to the device as a bit mask, uploaded when the limits
change rather than per frame, since the compaction needs it there.

Parity is asserted permanently rather than argued: five cases covering realistic
frames, occupancy from a hundred pixels to past the cap, the pathological
geometries including rings, the resolution mask, and a hundred-repeat determinism
check - requiring the same partition, the same spot order, and identical counts.
The centroid is a float sum and therefore order-dependent, so the device walks each
component from its root in ascending order and fuses its multiply-add the way the
host's does; note that whether the host fuses at all depends on the architecture
flags, so exact centroid equality is asserted where the compiler fuses and a
two-ulp bound otherwise. Making those accumulators integer would remove that
dependence entirely and is worth doing separately.

Regression set: all 37 crystals identical to the last printed digit. Unit suite
passes with the new cases.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-02 13:34:43 +02:00
leonarski_fandClaude Opus 5 1a1e05ad14 spot_finding: run the same two passes on the CPU as on the GPU
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ImageSpotFinderGPU::Detect launches its kernel twice, feeding the first
pass's strong-pixel bitmap back in so the second recomputes each local
background with those pixels excluded and keeps them strong. The CPU
finder ran a single pass, so the two returned different spot lists for the
same frame and a dataset processed without a GPU did not match one
processed with it.

It matters for any spot wide enough to reach into its own 31x31 background
box: the spot inflates the mean and variance it is then tested against, so
its outer pixels fail the SNR test. On the test image added here - a 5x5
core at 300 counts with a one-pixel ring at 25 - a single pass returns the
25-pixel core and 7500 counts where two passes return the full 49 pixels
and 8100.

pxl_val also becomes int64_t, matching the GPU's pixel_result signature.
It was int32_t, so pxl_val * pxl_val overflowed above 46341 counts even
though the surrounding sums were already 64-bit.

The new parity test compares PixelCount and Count, not just the centroid,
which does not move for a symmetric spot whether or not the ring was
picked up; it was confirmed to fail against the old single-pass CPU.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-07-31 15:37:22 +02:00
leonarski_f c981e1b91c v1.0.0-rc.137 (#46)
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This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132.

* jfjoch_broker: Better track time for each operation in the processing stack
* jfjoch_broker: Rewrite preprocessing of diffraction images in the non-FPGA workflow to better use GPUs (work in progress)
* jfjoch_broker: Remove ROI calculation in the non-FPGA workflow (work in progress)
* jfjoch_viewer: Toolbar displays image number starting from 1 (instead of 0)

Reviewed-on: #46
2026-04-25 19:59:21 +02:00
leonarski_f 061152279c v1.0.0-rc.91 2025-10-20 20:43:44 +02:00