2 Commits

Include renames

Author	SHA1	Message	Date
leonarski_fandClaude Opus 5.5	87f0bdc870	RotationScaleMerge: fit the error model on the device in the GPU build (tier F) ... FitErrorModelGPU puts the samples in the host's rank order with four stable radix passes, so the equal-count bins hold the same samples; computes every normalised deviation with the host's rounding, so every bin median is the host's to the bit; and hands the per-bin terms to the host's own update step, now ErrorModelUpdate (a pure extraction from FitErrorModel). The one thing that differs is the order each bin's two sums are added in: a fixed tree on the device, the order nth_element happened to leave the bin in on the host. a and b^2 can therefore differ from the host fit in their last bits - measured on two synthetic pools: relative difference 2e-16 and 3e-13 in a, 5e-16 in b^2. The device fit is deterministic (same pool, same bits). p.mtz md5 nevertheless unchanged on myob, cytc, 8a1a and 8qaw (GPU build): the difference does not survive the float rounding of the merged sigmas there. A knife-edge decision elsewhere could still see it, which is why this is kept as its own commit. The host fit took 0.4-0.6 s per fit on the large merges, about half of it the initial equal-count split, with only 16-way parallelism in the iterations. Device peak about 72 bytes per sample (the rank sort; each stage's buffers are freed when it is done); the free memory is checked first and a device without it stops with a message naming the CPU build. Kept last on the branch so that it can be dropped on its own. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SVmAWnzCmRKAXVUCdc4iNi	2026-10-08 08:52:04 +02:00
leonarski_f	84228bf8be	v1.0.0-rc.173 (#83) ... * jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports. * jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls. * Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results. * Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable. * Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate. * Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do. * Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence. * Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags. * Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check. * Rugnux: Clear error messages when a data set needs more GPU or host memory than is available. Reviewed-on: #83 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>	2026-09-29 15:57:32 +02:00