Hi Florian,

?

???? That sounds like an interesting project. I've looked at this a little. If 
it were me, I would start by implementing the simplest possible MC playouts in 
gpgpu,?as efficiently as possible, before looking at adding things like 
patterns.?

???? I also heartily encourage you to learn about genetic algorithms. (But?not 
really because of?RAVE.)

- Dave Hillis

-----Original Message-----
From: Florian Erhardt <[EMAIL PROTECTED]>
To: computer-go <[email protected]>
Sent: Mon, 11 Feb 2008 4:06 pm
Subject: [computer-go] gpugo



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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