leonarski_fandClaude Opus 4.8
dd25de461d
First stage of moving the rotation scale/merge onto the GPU. The per-frame partial-scaling loop (inverse-variance group-mean reduction -> robust per-frame IRLS G -> corr update, x scaling_iter) now runs in RotationScaleMergeGPU (.cu) when a GPU is present; the CPU loops remain the fallback. The host keeps the one-time raw-hkl sort and the per-space-group gemmi ASU keying, and hands the GPU a group-ordered permutation + CSR so the per-group reduction is a DETERMINISTIC segmented reduction (one thread per group, fixed order, no atomics) - preserving the run-to-run determinism just won on the CPU path (a float atomicAdd reduction would have re-introduced jitter). Reduction is one-thread-per-group (groups average tens of obs, so a block-per-group wastes threads); the IRLS is one block per frame with a deterministic shared-memory reduction. Validated: bit-identical to the CPU path and deterministic run-to-run on lyso/cytC/Ins_H/pding (P41212 ISa 7.8 CC1/2 99.7%, etc.). The scaling kernels are ~7x faster than the CPU compute (~36 ms for 3 iters vs ~0.28 s); end-to-end scale/merge ~2.0 -> ~1.5 s. The remaining gap to the <1 s target is the per-pass host round-trip (corr down/upload for the CPU combine + per-SG group-CSR rebuild); phase 2 keeps the data resident by moving the 3D combine and the merge/error-model onto the GPU too, so nothing round-trips. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Jungfraujoch
Application to receive data from the PSI JUNGFRAU and EIGER detectors.
All documentation is now placed in docs/ subdirectory and for the current version hosted on Jungfraujoch Read The Docs page.