8000 added gpu support by min-hieu-netropy · Pull Request #174 · colmap/glomap · GitHub
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Merged
merged 18 commits into from
Mar 20, 2025
Merged

added gpu support #174

merged 18 commits into from
Mar 20, 2025

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min-hieu-netropy
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@min-hieu-netropy min-hieu-netropy commented Mar 10, 2025 •
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added gpu support to global positioning and bundle adjustment
stats on a 1k image data set with exhaustive matching on RTX4090:

  • global positioning:
    • cpu: 420.37341s
    • gpu: 94.93816s
  • bundle adjustment:
    • cpu: 72.99911s (first stage), 1074.74076s (second stage)
    • gpu: 114.81785s (first stage), 343.74347s (second stage)

I think the performance gain would be much higher on bigger dataset since the gpu utilization is only ~20% when I run these tests. Also, global positioning seems to benefit the most from GPU usage

@min-hieu-netropy min-hieu-netropy mentioned this pull request Mar 10, 2025
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@ichsan2895
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Sorry, I am not good for advance coding, but I really appreciate this PR. Please @lpanaf consider to merge it when it ready.

ahojnnes
ahojnnes reviewed Mar 13, 2025
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CMakeLists.txt Outdated
@@ -1,6 +1,6 @@
cmake_minimum_required(VERSION 3.28)

project(glomap VERSION 1.0.0)
project(glomap_gpu VERSION 1.0.0)
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Let's keep the original project name.

We should add an option to enable/disable CUDA support (similar to how colmap works).

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Hi, I was fixed the naming back to glomap. The commit has the GlobalPositioning.use_gpu and BundleAdjustment.use_gpu options in option_manager.cc

@lpanaf
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lpanaf commented Mar 13, 2025

Hi @min-hieu-netropy, thank you very much for this pull request. I was checking your code and figured that the min_num_images_gpu_solver for the global positioning step and the bundle adjustment step are set to be 1000, 300. Did you run any experiments to choose this number? If not, I would prefer to keep it consistent with the heuristic number set by COLMAP (50 in this case)

@min-hieu-netropy
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Hi @min-hieu-netropy, thank you very much for this pull request. I was checking your code and figured that the min_num_images_gpu_solver for the global positioning step and the bundle adjustment step are set to be 1000, 300. Did you run any experiments to choose this number? If not, I would prefer to keep it consistent with the heuristic number set by COLMAP (50 in this case)

Hi, I originally put in the colmap number but wanted to experiment with different datasets so I made it 1000 and 300. However feel free to change it.

@DuVogel87
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i added:

'--GlobalPositioning.use_gpu 1
--BundleAdjustment.use_gpu 1 '

to my script.

But when running it i get this error:

'I20250318 20:11:45.942935 31020 image_undistorter.cc:20] Undistorting images..
I20250318 20:11:45.942958 31020 image_undistorter.cc:41] Image undistortion done
I20250318 20:11:45.943114 31020 global_positioning.cc:46] Setting up the global positioner problem
W20250318 20:11:54.332746 31020 global_positioning.cc:380] Requested to use GPU for bundle adjustment, but Ceres was compiled without CUDA support. Falling back to CPU-based dense solvers.
W20250318 20:11:54.333981 31020 global_positioning.cc:397] Requested to use GPU for bundle adjustment, but Ceres was compiled without cuDSS support. Falling back to CPU-based sparse solvers.
I20250318 20:11:54.333993 31020 global_positioning.cc:71] Solving the global positioner problem
I20250318 20:26:16.512383 31020 global_positioning.cc:80] Ceres Solver Report: Iterations: 60, Initial cost: 2.755906e+07, Final cost: 5.299410e+01, Termination: CONVERGENCE
I20250318 20:26:16.936136 31020 track_filter.cc:86] Filtered 1422 / 635890 tracks by angle error
I20250318 20:26:16.945920 31020 timer.cc:87] Elapsed time: 871.00336 [seconds]'

I get this when running 'colmap -h'
'COLMAP 3.12.0.dev0 -- Structure-from-Motion and Multi-View Stereo
(Commit 6556b4e2 on 2025-03-04 with CUDA)'

This when running 'glomap -h'
'GLOMAP -- Global Structure-from-Motion
This version was compiled with CUDA!'

Don't know what i did wrong. I appreciate any form of help. Thx!

@min-hieu-netropy
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Hi, it seems like you're using a ceres version without CUDA support. You can try building ceres (version >= 2.3) from source and try again.

@lpanaf lpanaf merged commit ce51d8b into colmap:main Mar 20, 2025
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@xiemeilong
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xiemeilong commented Mar 22, 2025 •
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How much VRAM do I approximately need? I was able to run it successfully with 3600 images, but I get an error when I use 6000 or 9000. Is this because I don't have enough VRAM? My VRAM is 16GB.

-------------------------------------
I20250321 10:49:13.659646  4070 image_undistorter.cc:20] Undistorting images..
I20250321 10:49:13.659672  4070 image_undistorter.cc:41] Image undistortion done
I20250321 10:49:13.660104  4070 global_positioning.cc:46] Setting up the global positioner problem
I20250321 10:49:36.217622  4070 global_positioning.cc:71] Solving the global positioner problem
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
F0000 00:00:1742554194.110962    4070 block_sparse_matrix.cc:818] Check failed: cudaSuccess == cudaHostAlloc(&values, sizeof(double) * size, cudaHostAllocDefault) (0 vs. 1) 
*** Check failure stack trace: ***
    @     0x5f72ed1d4c7d  absl::lts_20240722::log_internal::LogMessage::PrepareToDie()
    @     0x5f72ed1d4cf5  absl::lts_20240722::log_internal::LogMessage::SendToLog()
    @     0x5f72ed1d4711  absl::lts_20240722::log_internal::LogMessage::Flush()
    @     0x5f72ed1d5026  absl::lts_20240722::log_internal::LogMessageFatal::~LogMessageFatal()
    @     0x5f72ec72b77d  ceres::internal::BlockSparseMatrix::AllocateValues()
*** Aborted at 1742554194 (unix time) try "date -d @1742554194" if you are using GNU date ***
PC: @                0x0 (unknown)
*** SIGABRT (@0xfe6) received by PID 4070 (TID 0x7572e836c000) from PID 4070; stack trace: ***
    @     0x757330e6b206 (unknown)
    @     0x75730c506330 (unknown)
    @     0x75730c55fb2c pthread_kill
    @     0x75730c50627e gsignal
    @     0x75730c4e98ff abort
    @     0x5f72ed1d4261 absl::lts_20240722::log_internal::LogMessage::FailWithoutStackTrace()
    @     0x5f72ed1d4cc4 absl::lts_20240722::log_internal::LogMessage::Die()
    @     0x5f72ed1d4d78 absl::lts_20240722::log_internal::LogMessage::SendToLog()
    @     0x5f72ed1d4711 absl::lts_20240722::log_internal::LogMessage::Flush()
    @     0x5f72ed1d5026 absl::lts_20240722::log_internal::LogMessageFatal::~LogMessageFatal()
    @     0x5f72ec72b77d _ZN5ceres8internal17BlockSparseMatrix14AllocateValuesEi.cold
    @     0x5f72ecd4b080 ceres::internal::BlockSparseMatrix::BlockSparseMatrix()
    @     0x5f72ecd90e4a ceres::internal::BlockJacobianWriter::CreateJacobian()
    @     0x5f72ecd5d435 ceres::internal::ProgramEvaluator<>::CreateJacobian()
    @     0x5f72ecd8425c ceres::internal::TrustRegionPreprocessor::Preprocess()
    @     0x5f72ecd3e0e6 ceres::Solver::Solve()
    @     0x5f72ecd3fa2b ceres::Solve()
    @     0x5f72ec7b73f7 glomap::GlobalPositioner::Solve()
    @     0x5f72ec75a821 glomap::GlobalMapper::Solve()
    @     0x5f72ec751af8 glomap::RunMapper()
    @     0x5f72ec74c043 main
    @     0x75730c4eb1ca (unknown)
    @     0x75730c4eb28b __libc_start_main
    @     0x5f72ec74d0a5 _start
Aborted (core dumped)
ERROR:root:Mapper failed with code 34304. Exiting.


Sat Mar 22 03:20:47 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 565.57.01              Driver Version: 565.57.01      CUDA Version: 12.7     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 4080 ...    On  |   00000000:01:00.0  On |                  N/A |
|  0%   30C    P8              2W /  320W |     506MiB /  16376MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
+-----------------------------------------------------------------------------------------+

@xiemeilong
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This exception might also happen even with just 1000 photos.

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@lpanaf lpanaf lpanaf approved these changes

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@min-hieu-netropy @ichsan2895 @lpanaf @DuVogel87 @xiemeilong @ahojnnes
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