[ander]

My knowledge of the LBM is very limited, but it is my understanding that it can be implemented efficiently on GPU's since each "cell's" update is only dependent on surrounding cells. I also assume then that this update is explicit, since otherwise some linear system would likely have had to be solved and the GPU use would be less efficient (?)

My question then is why is this method likely more efficient than for instance an explicit method for compressible flows, where each cell is also only dependent on locally nearby cells. As an example, a second order MUSCL scheme for a 2D grid could have a nine point stencil as shown below:

OOXOO
OOXOO
XXXXX
OOXOO
OOXOO

(X'es are part of the stencil)

while a basic LBM could have the following nine point stencil in 2D:

XXX
XXX
XXX

I guess both of these methods could be effectively parallelized on a GPU, but my impression is still stat LBM is regarded as superior in this regard. If this impression is true, what is the reason for it? Is it due to less restrictive stable time step? Ofc for an explicit implementation of Navier Stokes, the viscous terms will put large restrictions on the time step due to the von neumann number which scales with 1/dx^2.

I hope someone can enlighten me