Commit Graph

6 Commits

Author SHA1 Message Date
leonarski_f 02fa15c2b9 jfjoch_process: spread per-image GPU work across all visible GPUs
The offline worker threads built MXAnalysisWithoutFPGA without selecting a CUDA
device, so all per-image preprocessing/spot-finding/azimuthal integration ran on
GPU 0 (only the indexer pool was distributed). Add pin_gpu() to CUDAWrapper - a
process-wide round-robin counter (counter++ % get_gpu_count(), no thread id, no-op
without a GPU, honours CUDA_VISIBLE_DEVICES) - and call it once per worker before
building the analysis resources so their CUDA streams/engines land on distinct
devices.

Also add NUMA_GPU_REVIEW.md: a working note mapping ImageBuffer/NUMAHWPolicy/GPU
dispatch with goals and a staged plan (multi-broker GPU isolation via
CUDA_VISIBLE_DEVICES, dropping libnuma, reassessing NUMA pinning for the FPGA path).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-17 15:29:52 +02:00
leonarski_f 061152279c v1.0.0-rc.91 2025-10-20 20:43:44 +02:00
leonarski_f 28d224afab version 1.0.0-rc.25 2024-11-22 21:25:20 +01:00
leonarski_f 16bbf54f2a Remove open source license (for now) 2023-09-15 10:47:21 +02:00
leonarski_f 9d978a41f7 NUMAHWPolicy: Added 2023-07-28 11:07:15 +02:00
leonarski_f 669b2d9358 CUDAWrapper: Move select device to dedicated wrapper 2023-07-27 21:30:10 +02:00