Using CUDA textures to store 2D surfaces

Question

I am currently developing a 3D heat flow simulation on a 3D triangular mesh (basically any shape) with CUDA.

I was thinking of exploiting spatial locality by using CUDA textures or surfaces. Since I have a 3D mesh I thought that a 3D texture would be appropriate. After looking on different examples, however, I am not so sure anymore: 3D Textures are often used for volumes not for surfaces like in my case.

Can I use 3D textures for polygon meshes? Does it make sense? If not, are there other approaches or data structures in CUDA of use for my case?

Answer 1

Using 3D textures to store surface meshes is in fact a good idea. To better point this out, let me recall the clever approach in

Octree Textures on the GPU, GPU Gems 2

using 2D and 3D meshes to store an OctTree and to

1. Create an OctTree using a 3D texture;
2. Fastly traverse the OctTree by exploiting the filtering properties of the 3D texture;
3. Storing the surface polygons by a 2D texture.

OCTTREE TRAVERSAL BY THE FILTERING FEATURES OF A 3D TEXTURE

The tree is stored as an 8-bit RGBA 3D texture mapped in the unit cube [0,1]x[0,1]x[0,1], named as indirection pool. Each node of the tree is an indirection grid. Each child node is identified by the first three coordinates of the RGBA, while the fourth stores some other information, for example, if the node is a leaf or not or if it is empty.

Consider the QuadTree example reported in the paper (figure borrowed from the paper).

The A, B, C and D nodes (boxes) are stored as the texture elements (0,0), (1,0), (2,0) and (3,0), respectively, containing, for a QuadTree, 4 elements, each element storing a link to the child node. In this way, any access to the tree can be done by exploiting the hardware filtering features of the texture memory, a possibility that is illustrated in the following figure:

and by the following code (it is written in Cg, but I'm sure it can be easily ported to CUDA):

STORING THE TREE ELEMENTS BY A 2D TEXTURE

The elements of the tree can be stored by the classical approach exploiting the (u,v) coordinates, see UV mapping. The paper linked to above discusses a way to improve this method, but this is beyond the scope of this answer.