----- Original Message ----
> From: Petr Baudis <pa...@ucw.cz>
> There has been some talk about implementing monte-carlo playouts on
> GPUs in the past, I have heard rumours about Polish bachelor student
> doing libego -> GPGPU conversion as a project, etc. but I know of
> nothing concrete ever materializing - is anybody aware of anything?
>
> We have recently bought very high-end nVidia card at our university
> department for trying out GPGPU and I'm thinking of a little project for
> myself, maybe...
>
> I'm not much skilled in this kind of programming though, so I'm not
> quite sure what the best design approach to take would be... my current
> ideas so far are either
>
> (i) Have one game per pipeline, and in each cycle, take a board and
> transform it by playing a random move (or possibly have an extra cleanup
> cycles if capturing stones would take too long); you should be able to
> do some neat pattern matching and so too
>
> (ii) Have one intersection per pipeline, in one cycle play a random
> move, then have board_height cycles for captures and liberty updates
> to ripple through to all the neighbors. The code would be much more
> streamlined, but I'm not sure yet if there is a good way to do the
> rippling - ORing bitmaps?
>
> I guess there is a lot of things to try out.
There may be ways to implement monte carlo effectively on GPUs - but some other
algorithms might make more effective use of the different capabilities of the
GPU. For instance, neural networks might map well to a GPU. It might also be
possible to collect a lot of useful information about shapes using cellular
automata.
The GPU might be the main engine, or it might be deployed to collect
information about the current board situation ( such as the most interesting
plays ) which is then fed to the CPU for creation of a tree structure.
Hard to say a priori -- lots of room for experimentation!
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