Hello !
My name is Florian Erhardt, I am a bachelor student of computer sciences
and am in the process of optimizing libEGO for gpgpu. For now I
implemented the SFMT (even I can do copy and paste) on the gpu and am
now atomizing the MC to be done by the gpu. If everything works as I
planned it, I'll have a releasable program in a few months (I still
have to learn lots about parallelizing, gpu programming and programming
in general [maybe leaning about genetic algorithms can't hurt either -
The RAVE algorithm is more like a genetic algorithm - Right ?] - and I
have to go to university :-) ).
For now I'm using a MC-engine with UCT, trying out how much patterns
and other things might make the results better.
Now as I understand it, using patterns, groupstatus, ... during the
MC-playout makes the results from the playout more meaningful (stronger
- 30k instead of random), so if I would make the playout with a small
engine (the easiest way to use the power of the gpu) the result should
be more meaningful too. Has anyone done any test like that (like use
gnugo level 0 instead of an MC-playout) ? Does anyone have a
minimalistic non-MC go engine I could look at ? One more thing - has
anyone tried using quasi-MC for go ?
Well - that's all folks.
mfg
Florian Erhardt
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