Open lmiq opened 1 year ago
I've been working with a custom cell list (though not implemented as a linked list) that uses a SparseArray
to store indexes into a vector of cells, and only occupied cells are created.
In case that's useful as an inspiration.
Any inspiration is welcome 😁
For reference. The array that depends critically on the number of cells is this one:
" Auxiliary array that contains the indexes in list of the cells with particles, real or images. "
cell_indices::Vector{Int} = zeros(Int,number_of_cells)
It is a linked list array indicating which are the indexes of the cells that contain particles.
The problem of removing this array (and storing, for instance, a simple lists of the indexes of cells with particles), is that we need to make the association in the reverse direction. That is, we need to quickly retrieve the data of a cell with particles just from the (linearized) three-dimensional indexes of the cell, to be able to run over vicinal cells in the inner loops.
An alternative (maybe a good one, actually), is to store the indexes of the vicinal cells as a 26 (in 3D) or 8 (in 2D) array, for each cell containing particles. Each cell struct would then carry an additional field, but the storage requirement would be at most 27*N if each cell contains a single particle.
New idea (cannot test now):
Define a new type of array to store cell_indices
, with a buffer size equal to the number of particles. Define getindex
such that it returns 0
if the cell is not defined, and the indices of the cell if the cell was set, as occurs with the current cell_indices
array. If the number of cells is less than the number of particles, the cells can be indexed as usual. If the number of cells is greater than the number of particles, fill the array in order, to access the indexes with searshortedfirst
afterwards.
A proper implementation of that may allow just substituting the type of array cell_indices
is without modifying anything in the remaining code. The overhead associated with using searchsortedfirst
may not be negligible, but it is not that bad, and probably pays off relative to the current approach, when the number of cells is much greater than the number of particles.
What you're describing is similar conceptually to how the SparseMatrixCSC method I described works. (Internally it selects the column and does searchsortedfirst
over it to get an element.)
The big problem I had with SparseMatrixCSC was that adding individual items is very slow, so I had to pre-allocate the I, J, and V arrays.
Yes, effectively. I think that can work, except that I need a bit more customization as I will need the array type to carry some information about the number of elements effectively used in the array vs. the number of elements of the buffer, to avoid having to resize the arrays too often in the case of list updating. But something on those lines can work, yes, your comment was important.
When systems are highly non-homogeneous, the number of cells can explode to be much greater than the number of particles:
This makes it prohibitive to work with this kind of system. Can we find a way to not allocate empty cells at all? The full cell allocation would need to be lazy, since the construction of the box does not involve the actual coordinates of the system.