Does cuda version of LM work? about fast_gicp HOT 13 CLOSED

I fixed build errors and some Eigen-related alignment errors and added build and run tests with the latest PCL. Can you see if refactor branch works with PCL 1.11?

Thanks for your hard work,
I just about to report the Eigen related problem which you have nailed.
It works on PCL 1.11.1.
The gicp_align works, through the test app, may need some further tweak.
Thanks again.

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Sorry, I met some GPU-related error and needed a bit more time to fix it. I suppose it'll be done next week.

from fast_gicp.

Thanks.
Very appreciate your hard work.
I will follow your lm-cuda branch.

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I still have some problems on the GPU version and need more time to make it workable...

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I was re-checking the code, and found that it was a termination criteria bug. I pushed the fixed code to lm_cuda branch. Could you test if it works on your environment?

from fast_gicp.

I was re-checking the code, and found that it was a termination criteria bug. I pushed the fixed code to lm_cuda branch. Could you test if it works on your environment?

Hi, I have tried both master and lm_cuda branch with gicp_align. there are two crushes

1. fast_gicp::FastVGICP single and mt.

fast_gicp::FastVGICP<pcl::PointXYZ, pcl::PointXYZ>::create_voxelmap(std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&) 0x000055bd6d6b7d12
void test<fast_gicp::FastVGICP<pcl::PointXYZ, pcl::PointXYZ> >(fast_gicp::FastVGICP<pcl::PointXYZ, pcl::PointXYZ>&, std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&, std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&) 0x000055bd6d695301
main 0x000055bd6d68e0f3
__libc_start_main 0x00007f343269cbf7
_start 0x000055bd6d690eca

Signal: SIGSEGV (Segmentation fault)

2.fast_gicp::FastVGICPCuda

still crushed at

__GI___libc_free 0x00007fb57d9c7a6d
fast_gicp::FastVGICPCuda<pcl::PointXYZ, pcl::PointXYZ>::setInputSource(std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&) 0x000056131cbeb799
void test<fast_gicp::FastVGICPCuda<pcl::PointXYZ, pcl::PointXYZ> >(fast_gicp::FastVGICPCuda<pcl::PointXYZ, pcl::PointXYZ>&, std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&, std::shared_ptr<pcl::PointCloudpcl::PointXYZ const> const&) 0x000056131cbdc251
main 0x000056131cbd70f3
__libc_start_main 0x00007fb57d951bf7
_start 0x000056131cbd9d7a

target:17047[pts] source:17334[pts]
--- vgicp_cuda (parallel_kdtree) ---
Signal: SIGSEGV (Segmentation fault)

I have made some changes to make it fit for PCL 1.11.1 (replace boost::shared_ptr with std::shared_ptr)
And since I don't use catin
#add_dependencies(gicp_align ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
#add_dependencies(gicp_kitti ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
commended in cmakelist. Otherwise it gives cmake error for
" add_dependencies called with incorrect number of arguments"

the environment is
ubuntu 18.04.1 with 5.4.0-42-generic
clion with gcc version 7.5.0
PCL 1.11.1
Cuda compilation tools, release 10.2, V10.2.89
I hope it will help.

from fast_gicp.

Thanks for your help. With the PCL installed via apt, this problem didn't reproduce. It seems it has some problems with the latest PCL. I'll add some tests for the latest PCL to fix it.

from fast_gicp.

Thanks for your help. With the PCL installed via apt, this problem didn't reproduce. It seems it has some problems with the latest PCL. I'll add some tests for the latest PCL to fix it.

PCL 1.11+
API changes:
Replace boost::shared_ptr with std::shared_ptr
At your last commit (lm with CPU), I replace boost::shared_ptr with std::shared_ptr, it works fine.

For PCL change details
Starting with PCL 1.11, PCL uses std::shared_ptr and std::weak_ptr instead of the boost smart pointers. The change leverages type aliases included with the 1.10.0 release.

PCL 1.11 also introduces pcl::index_t which should be used for the size of point types instead of int, std::size_t, etc. EOL for deprecated features is also explicitly mentioned in the deprecation compile time warnings

https://github.com/PointCloudLibrary/pcl/blob/master/CHANGES.md#-1110-11052020-

I hope you can make a new branch for PCL 1.11+
consider it still updates frequently.

from fast_gicp.

I fixed build errors and some Eigen-related alignment errors and added build and run tests with the latest PCL. Can you see if refactor branch works with PCL 1.11?

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Hi,@koide3
Could you tell me how to handle the Eigen align problem?
I recently meet this problem, but I don't know how to fix it.
I read from stack flow, It may relate to the SSE CPU alignment. Eigen needs to align memory for 4byte alignment, last time I just enable build compilation -march native in CMake list. It goes away automatically.
But this time before your refactor branch, the Cuda still crush on Eigen align part
How do you fix it?
Any advice or links will be helpful

__GI___libc_free 0x00007f3e8dd41a6d
Eigen::internal::handmade_aligned_free Memory.h:98
Eigen::internal::aligned_free Memory.h:179
Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> >::deallocate Memory.h:763
std::allocator_traits<Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> > >::deallocate alloc_traits.h:328
std::_Vector_base<Eigen::Matrix<float, 3, 3, 0, 3, 3>, Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> > >::_M_deallocate stl_vector.h:180
std::_Vector_base<Eigen::Matrix<float, 3, 3, 0, 3, 3>, Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> > >::~_Vector_base stl_vector.h:162
std::vector<Eigen::Matrix<float, 3, 3, 0, 3, 3>, Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> > >::~vector stl_vector.h:435
fast_gicp::FastVGICPCuda<pcl::PointXYZ, pcl::PointXYZ>::setInputSource fast_vgicp_cuda_impl.hpp:82
test<fast_gicp::FastVGICPCuda<pcl::PointXYZ, pcl::PointXYZ> > align.cpp:58
main align.cpp:176
__libc_start_main 0x00007f3e8dccbbf7
_start 0x0000555f67d0d4da

from fast_gicp.

The cause of the problem was std::make_shared that uses the standard (non-aligned) allocator by default. An easy workaround was to avoid make_shared and use new to create an instance. pcl::make_shared, which properly uses Eigen::aligned_allocator, would be a better solution if we don't need to take care of old version of PCL, though.

// AdditiveGaussianVoxel has Eigen variables, and this may cause an alignment error
voxel = std::make_shared<AdditiveGaussianVoxel>();

// This properly calls ALIGNED_OPERATOR_NEW
voxel.reset(new AdditiveGaussianVoxel);

It looks the new error you faced is relating to std::vector, and we need another workaround. I'll try to reproduce it on my PC.

from fast_gicp.

The cause of the problem was std::make_shared that uses the standard (non-aligned) allocator by default. An easy workaround was to avoid make_shared and use new to create an instance. pcl::make_shared, which properly uses Eigen::aligned_allocator, would be a better solution if we don't need to take care of old version of PCL, though.

// AdditiveGaussianVoxel has Eigen variables, and this may cause an alignment error
voxel = std::make_shared<AdditiveGaussianVoxel>();

// This properly calls ALIGNED_OPERATOR_NEW
voxel.reset(new AdditiveGaussianVoxel);

It looks the new error you faced is relating to std::vector, and we need another workaround. I'll try to reproduce it on my PC.

Thanks for the quick reply.
The mentioned problem does not exist in your new branch (refactor). It can reproduce on lm_cuda. With PCL 1.11.1 and replace boost::shared_ptr with std::shared_ptr.
According to your reply, std::make_shared uses the standard (non-aligned) allocator by default.
When the (non-aligned) allocator and aligned allocator are mixed, this kind of problem randomly appears in the object-free process.

Eigen::internal::handmade_aligned_free Memory.h:98
Eigen::internal::aligned_free Memory.h:179
Eigen::aligned_allocator<Eigen::Matrix<float, 3, 3, 0, 3, 3> >::deallocate Memory.h:763

This is my bad. Did not read the following doc carefully. I hope others won't make the same mistake.
= 1.10.0 (19.01.2020) =
Starting with PCL 1.10, to ensure compatibility with future PCL releases, please use pcl::make_shared and the Class::Ptr + Class::ConstPtr type-alias instead of using direct names like {boost, std}::shared_ptr or {boost, std}::make_shared. There is also pcl::shared_ptr which offers the same abstraction for non-PCL types.

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Oh, I see.

std::make_shared<>

    return std::allocate_shared<_Tp>(std::allocator<_Tp_nc>(),
			       std::forward<_Args>(__args)...);

pcl::make_shared<>

   return std::allocate_shared<T>(Eigen::aligned_allocator<T>(), std::forward<Args> (args)...);

If I need to make an Eigen related object, the last one is preferred.

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