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- Context: COLMAP DB ~34 GB; ~10,130 fisheye images (~3 GB total). Running
glomap mapper(cuDSS build, CUDA 12.8) on Ubuntu, 64 GB RAM, GPU: NVIDIA GeForce RTX 3090. - Observed: After track establishment (10.3M → 3.885M filtered), global positioning begins, then the kernel OOM-kills glomap at ~42 GB RSS. Happens consistently. cuDSS is enabled;
--GlobalPositioning.use_gpu/--BundleAdjustment.use_gpuare at defaults (1). - Logs/syslog snippet:
Out of memory: Killed process XXXX (glomap) total-vm:~59G, anon-rss:~42G …right after “Solving the global positioner problem.” - Questions/requests:
- Recommended flags/workflow for large scenes to reduce peak RAM during global positioning/BA?
- Is there a built-in way to chunk/stream the solver (e.g., batch tracks/poses) or an out-of-core mode?
- Any known memory regressions/tunables for cuDSS builds in recent commits?
- Guidance on safe limits (tracks, matches, overlaps) for ~10k-image rigs?
- Environment: glomap commit as of 2025-11-26 (COLMAP 3.13.0, cuDSS 0.7.1, CUDA 12.8), Ubuntu, 64 GB RAM, NVIDIA GeForce RTX 3090.
- Repro command (example):
(Global positioning starts, then OOM.)
glomap mapper \ --database_path /path/to/database.db \ --image_path /path/to/images \ --output_path /path/to/glomap_out \ --BundleAdjustment.optimize_intrinsics 1 \ --BundleAdjustment.optimize_principal_point 0 \ --BundleAdjustment.optimize_rig_poses 1 \ --BundleAdjustment.max_num_iterations 300
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