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Jungfraujoch/image_analysis/structure_refinement
leonarski_fandClaude Fable 5.1 d122118d73 Refinement: the per-evaluation host chain on the threads and in place
Byte-identical: every pass is element by element in the serial loop's order, or a copy that is no longer made.

- The engine's gradients are read in place from its pinned buffers and widened to double on the threads
  (RefinementGPUEngine::HostGradient/HostRestraintGradient); the positions go up from a pinned vector of the
  engine's host side; the model's atom pointers are kept between calls (the model is the context's own).
- Context: the riders moved and folded on the threads - a parent takes its riders in index order through a
  CSR list (SetRiderParents), as the serial walk added them.
- AtomTarget: the parameters set and the gradient assembled on the threads; the per-atom gradient vectors kept
  between evaluations (7 MB each on a large model: made anew, their pages fault in every time).
- RefinementMinimiser: the sweeps over the parameters (x + alpha d, s, y) on the threads it is given, the dot
  products the serial chains they were; Direction()'s working vector and a let-go pair's vectors reused.

A/B against the frozen combined2 binary, one lock hold each, outputs identical but provenance lines:
cytc refinement 1.600 -> 1.548 s (live), 1.724 -> 1.668 (CLI); thau 1.906 -> 1.885, 2.031 -> 2.027;
4nwv (with the commit before) 39.9 -> 35.5 s, the ladder 14.6 -> 12.7, each step 8.3 -> 7.2.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
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