http://computer-go.org/pipermail/computer-go/2008-October/016680.html
Interestingly, I did this a while ago. Here's my results:
$ ./Bench 1 100000
b: 14840, w: 17143 mercy: 67982
elapsed time: 3.42s
playouts/sec: 29208
so, nearly 30k/sec random playouts on 9x9. That's using a hack that stops
the game when the score is heavily in favour of one player, it drops to
around 20k/sec with that turned off.
Nice!-) 20k playouts/sec (without the early cutoffs) is the rough number
usually mentioned for these light playouts, reachable even in Java. My own
Haskell code for that was a factor of 5 slower:-(
actually, that 5x is relative to jrefbot on my machine (Pentium M760, 2Ghz),
which doesn't quite reach 20k/sec, so if your code would run at 20k/sec on
my laptop, it would be 10x as fast as my bot:-(( Since you can't release your
code, could you perhaps time the jrefbot from the url above on your machine
as a reference point, so that I know how far I've yet to go? Something like:
$ time ((echo "genmove b";echo "quit") |
d:/Java/jre6/bin/java -jar refbots/javabot/jrefgo.jar 20000)
= E5
real 0m2.539s
user 0m0.030s
sys 0m0.031s
Btw, I just realised where my bot dropped from 5x to 8x: to work around
http://hackage.haskell.org/trac/ghc/ticket/2669
all my array accesses were wrapped in exception handlers, to get
useful error messages while I adapted my code to the refbot spec..
That's not the only bug that got in the way:
http://hackage.haskell.org/trac/ghc/ticket/2727
forced me to move from functional to imperative arrays much sooner
than I wanted, and due to
http://hackage.haskell.org/trac/ghc/ticket/1216
I did not even consider 2d arrays (the tuple allocations might have gotten
in the way anyhow, but still..).
What do those folks working on parallel Haskell arrays think about the
sequential Haskell array baseline performance?
Claus
-- my slow bot's current time (for 20k playouts on a 2Ghz laptop):
$ time ((echo "genmove b";echo "quit") | ./SimpleGo.exe 20000)
TEXT e5 - amaf-score: 0.127
TEXT e6 - amaf-score: 0.126
TEXT d5 - amaf-score: 0.126
TEXT f5 - amaf-score: 0.118
TEXT d6 - amaf-score: 0.116
TEXT f4 - amaf-score: 0.115
TEXT e7 - amaf-score: 0.115
TEXT f6 - amaf-score: 0.114
TEXT d4 - amaf-score: 0.110
TEXT d3 - amaf-score: 0.108
TEXT e5 - amaf-score: 0.127
= e5
=
real 0m10.711s
user 0m0.030s
sys 0m0.031s
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