Octree | Unity3D Octree implementation

I tried creating an octree in c++. Seems to work fairly well, but when I print the content of the tree it returns an access violation error. Running this in debug will print two different numbers, although the content should not have been changed. Here is the printout:

I'm trying write a WGSL shader that reads an octree that is stored in a storage buffer. The problem is, the compiler doesn't like the dynamic index I'm calculating to access leaves in the storage buffer. wgpu produces the following validation error:

I am trying to pass a vector of vectors to an SSB0, however I get a segfault when passing it through with glBufferData. The structure in C++ is:

Let's say Octree() is a container with Elements of type double.

Can I use sizeof(Octree) to determine how much memory in bytes is taken up by my octree?

Sizeof() should change if I change the resolution/depth of my octree - which does not seem to be the case when I test it.

Is there a way I could determine the dynamically allocated memory size of my octree?

I get this error just by including the header file to my code. I'm using visual studio 2019 and c++17, I've included the linker files and all but it doesn't want to work.

What could it be?

Error C4996 'std::iterator': warning STL4015: The std::iterator class template (used as a base class to provide typedefs) is deprecated in C++17. (The header is NOT deprecated.) The C++ Standard has never required user-defined iterators to derive from std::iterator. To fix this warning, stop deriving from std::iterator and start providing publicly accessible typedefs named iterator_category, value_type, difference_type, pointer, and reference. Note that value_type is required to be non-const, even for constant iterators. You can define _SILENCE_CXX17_ITERATOR_BASE_CLASS_DEPRECATION_WARNING or _SILENCE_ALL_CXX17_DEPRECATION_WARNINGS to acknowledge that you have received this warning. TCC2 D:\dev\CMake\vcpkg\installed\x64-windows\include\pcl\octree\octree_iterator.h 71

In physics simulations (for example n-body systems) it is sometimes necessary to keep track of which particles (points in 3D space) are close enough to interact (within some cutoff distance d) in some kind of index. However, particles can move around, so it is necessary to update the index, ideally on the fly without recomputing it entirely. Also, for efficiency in calculating interactions it is necessary to keep the list of interacting particles in the form of tiles: a tile is a fixed size array (eg 32x32) where the rows and columns are particles, and almost every row-particle is close enough to interact with almost every column particle (and the array keeps track of which ones actually do interact).

What algorithms may be used to do this?

Here is a more detailed description of the problem:

1. Initial construction: Given a list of points in 3D space (on the order of a few thousand to a few million, stored as array of floats), produce a list of tiles of a fixed size (NxN), where each tile has two lists of points (N row points and N column points), and a boolean array NxN which describes whether the interaction between each row and column particle should be calculated, and for which:

   a. every pair of points p1,p2 for which distance(p1,p2) < d is found in at least one tile and marked as being calculated (no missing interactions), and

   b. if any pair of points is in more than one tile, it is only marked as being calculated in the boolean array in at most one tile (no duplicates),

   and also the number of tiles is relatively small if possible (but this is less important than being able to update the tiles efficiently)

2. Update step: If the positions of the points change slightly (by much less than d), update the list of tiles in the fastest way possible so that they still meet the same conditions a and b (this step is repeated many times)

It is okay to keep any necessary data structures that help with this, for example the bounding boxes of each tile, or a spatial index like a quadtree. It is probably too slow to calculate all particle pairwise distances for every update step (and in any case we only care about particles which are close, so we can skip most possible pairs of distances just by sorting along a single dimension for example). Also it is probably too slow to keep a full (quadtree or similar) index of all particle positions. On the other hand is perfectly fine to construct the tiles on a regular grid of some kind. The density of particles per unit volume in 3D space is roughly constant, so the tiles can probably be built from (essentially) fixed size bounding boxes.

To give an example of the typical scale/properties of this kind of problem, suppose there is 1 million particles, which are arranged as a random packing of spheres of diameter 1 unit into a cube with of size roughly 100x100x100. Suppose the cutoff distance is 5 units, so typically each particle would be interacting with (2*5)**3 or ~1000 other particles or so. The tile size is 32x32. There are roughly 1e+9 interacting pairs of particles, so the minimum possible number of tiles is ~1e+6. Now assume each time the positions change, the particles move a distance around 0.0001 unit in a random direction, but always in a way such that they are at least 1 unit away from any other particle and the typical density of particles per unit volume stays the same. There would typically be many millions of position update steps like that. The number of newly created pairs of interactions per step due to the movement is (back of the envelope) (10**2 * 6 * 0.0001 / 10**3) * 1e+9 = 60000, so one update step can be handled in principle by marking 60000 particles as non-interacting in their original tiles, and adding at most 60000 new tiles (mostly empty - one per pair of newly interacting particles). This would rapidly get to a point where most tiles are empty, so it is definitely necessary to combine/merge tiles somehow pretty often - but how to do it without a full rebuild of the tile list?

P.S. It is probably useful to describe how this differs from the typical spatial index (eg octrees) scenario: a. we only care about grouping close by points together into tiles, not looking up which points are in an arbitrary bounding box or which points are closest to a query point - a bit closer to clustering that querying and b. the density of points in space is pretty constant and c. the index has to be updated very often, but most moves are tiny

I'm implementing octree data structure. In octants i store triangles. So question: When i need to to stop dividing octants in Octree? I think about max depth or number of max number of triangles in octant, but how i can calculate this values?

This is the log (truncated) from my analysis of the hashmap:

I'm flattening out an octree and sending it to my fragment shader using an SSBO, and I believe I am running into some memory alignment issues. I'm using std430 for the layout and binding a vector of voxels to this SSBO this is the structure in my shader. I'm using GLSL 4.3 FYI