leonarski_fandClaude Opus 5.5
5de7189643
- Scaling: the 80%-of-card check runs right after the device ingest's sort and cut, where the observation and distinct-hkl counts are first known, instead of after the geometry smoothing; same counts, same decision, but a run that goes to the CPU no longer does the device smoothing (6.9 s on an 8 GB card for a 33 M observation set) or holds its memory meanwhile. - Rigid body: engines budgeted on a quarter of the card's total (the validation's plan), not min(total/4, free - 1 GB). A busy card no longer sends the rigid body to the CPU (measured on an 8 GB card: ~80 s and a different fit); engine allocations wait for GPU work beside the run, and an engine that cannot be set up fails the validation (RigidBodyGPUFailure) instead of falling back to the CPU. - Beam-centre FFT: GPU when its footprint is at most half of the card's total, otherwise CPU, logged; no catch-and-rescore on the CPU after a GPU failure. - FitPerFrameG reserves its per-frame vector (CPU scaling waited on the heap lock on Windows). - get_gpu_free_memory(): cudaMemGetInfo, except on an integrated GPU under Linux, where free also counts MemAvailable less a tenth of the total. Used only where free memory is waited on (cuda_memory_available) or quoted in out-of-memory messages; it decides nothing. The two card-filling [CUDAMemHelpers] tests skip on integrated GPUs. - Out-of-memory messages point at rugnux --no-gpu instead of "the CPU build". Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Jungfraujoch
Application to receive and analyse data from the PSI JUNGFRAU and EIGER detectors, together with
rugnux, its program for processing stored diffraction data - rotation and serial, macromolecular
and small-molecule - from images to merged reflections.
All documentation is now placed in docs/ subdirectory and for the current version hosted on Jungfraujoch Read The Docs page.