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Re: Trying to improve lazy smp
Posted: Thu Apr 16, 2015 7:46 pm
by Sven
cdani wrote:Sven Schüle wrote:cdani wrote:Hi.
I have done a self test at 25+0.03 with 4 threads:
Code: Select all
Rank Name Elo + - games score oppo. draw
1 Andscacs 0.74039 59 7 6 2512 69% -59 45%
2 Andscacs 0.73174 -59 6 7 2512 31% 59 45%
The difference in % is equivalent to 140 elo, but bayeselo shows +-59. Someone knows what I'm interpreting bad? I used bayeselo for more than a year and I did not compared the % until now with standard elo.
The difference between 59 and -59 is 118 which is quite a good match for 140.
Yes, but with standar elo, 69% is 140 elo, not 118. Is simply different for bayeselo?
I think the draw rate plays a role but others can explain that better than me.
Re: Trying to improve lazy smp
Posted: Thu Apr 16, 2015 7:49 pm
by AlvaroBegue
Sven Schüle wrote:cdani wrote:Sven Schüle wrote:cdani wrote:Hi.
I have done a self test at 25+0.03 with 4 threads:
Code: Select all
Rank Name Elo + - games score oppo. draw
1 Andscacs 0.74039 59 7 6 2512 69% -59 45%
2 Andscacs 0.73174 -59 6 7 2512 31% 59 45%
The difference in % is equivalent to 140 elo, but bayeselo shows +-59. Someone knows what I'm interpreting bad? I used bayeselo for more than a year and I did not compared the % until now with standard elo.
The difference between 59 and -59 is 118 which is quite a good match for 140.
Yes, but with standar elo, 69% is 140 elo, not 118. Is simply different for bayeselo?
I think the draw rate plays a role but others can explain that better than me.
Yes, the answer is somewhere in this page:
http://remi.coulom.free.fr/Bayesian-Elo/
[...]In order to perform this calculation, it is necessary to assume a little more than the usual ELO formula. The expected score as a function of the Elo difference is not enough. We need the probability of a win, a draw and a loss as a function of the Elo difference.
Re: Trying to improve lazy smp
Posted: Thu Apr 16, 2015 11:08 pm
by bob
cdani wrote:Sven Schüle wrote:cdani wrote:Hi.
I have done a self test at 25+0.03 with 4 threads:
Code: Select all
Rank Name Elo + - games score oppo. draw
1 Andscacs 0.74039 59 7 6 2512 69% -59 45%
2 Andscacs 0.73174 -59 6 7 2512 31% 59 45%
The difference in % is equivalent to 140 elo, but bayeselo shows +-59. Someone knows what I'm interpreting bad? I used bayeselo for more than a year and I did not compared the % until now with standard elo.
The difference between 59 and -59 is 118 which is quite a good match for 140.
Yes, but with standar elo, 69% is 140 elo, not 118. Is simply different for bayeselo?
What draw rate do you assume for your 69 = 140?
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 12:38 am
by cdani
bob wrote:What draw rate do you assume for your 69 = 140?
I just taked this 140 from FIDE (in fact 141):
https://www.fide.com/fide/handbook.html ... ew=article
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 12:38 am
by cdani
AlvaroBegue wrote:Yes, the answer is somewhere in this page:
http://remi.coulom.free.fr/Bayesian-Elo/
[...]In order to perform this calculation, it is necessary to assume a little more than the usual ELO formula. The expected score as a function of the Elo difference is not enough. We need the probability of a win, a draw and a loss as a function of the Elo difference.
Thanks!!
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 2:23 am
by bob
That has an assumed draw rate however, which might not be correct for your test games...
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 11:11 am
by Sven
bob wrote:
That has an assumed draw rate however, which might not be correct for your test games...
No, the draw rate is simply not part of the underlying theoretical model of the Elo rating system as it is used by the FIDE. Bayeselo uses a different model that takes the probabilities for win, draw, and loss into account as well as other factors like colors. The table in the FIDE handbook lists percentage expectancy values mapped to rating differences (and vice versa) based on the normal distribution, no draw rate is involved there.
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 12:14 pm
by Laskos
cdani wrote:
I have been also able to do a limited test at 20+.03 with 16 cores:
Code: Select all
1 Andscacs 0.74042 114 19 19 704 69% -23 27%
2 Komodo 5.1r2 64-bit 86 40 40 140 46% 114 34%
3 Senpai 1.0 6 41 42 140 34% 114 29%
4 Gull 1.2 x64 -40 41 43 142 27% 114 31%
5 Hannibal 1.3x64 -66 44 46 142 26% 114 20%
6 Protector 1.7.0 -99 45 48 140 22% 114 21%
The result is very good, clearly over 3100 elo.
I am confused, is this 16 core Andscacs against 1 core other engines? To be ahead of Komodo 5.1 is a feat, that's why I am asking.
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 1:13 pm
by cdani
Laskos wrote:cdani wrote:
I have been also able to do a limited test at 20+.03 with 16 cores:
Code: Select all
1 Andscacs 0.74042 114 19 19 704 69% -23 27%
2 Komodo 5.1r2 64-bit 86 40 40 140 46% 114 34%
3 Senpai 1.0 6 41 42 140 34% 114 29%
4 Gull 1.2 x64 -40 41 43 142 27% 114 31%
5 Hannibal 1.3x64 -66 44 46 142 26% 114 20%
6 Protector 1.7.0 -99 45 48 140 22% 114 21%
The result is very good, clearly over 3100 elo.
I am confused, is this 16 core Andscacs against 1 core other engines? To be ahead of Komodo 5.1 is a feat, that's why I am asking.
Yes, 16 cores against 1 core
Is how I have done most of my tests.
Re: Trying to improve lazy smp
Posted: Fri Apr 17, 2015 1:29 pm
by Laskos
cdani wrote:Laskos wrote:cdani wrote:
I have been also able to do a limited test at 20+.03 with 16 cores:
Code: Select all
1 Andscacs 0.74042 114 19 19 704 69% -23 27%
2 Komodo 5.1r2 64-bit 86 40 40 140 46% 114 34%
3 Senpai 1.0 6 41 42 140 34% 114 29%
4 Gull 1.2 x64 -40 41 43 142 27% 114 31%
5 Hannibal 1.3x64 -66 44 46 142 26% 114 20%
6 Protector 1.7.0 -99 45 48 140 22% 114 21%
The result is very good, clearly over 3100 elo.
I am confused, is this 16 core Andscacs against 1 core other engines? To be ahead of Komodo 5.1 is a feat, that's why I am asking.
Yes, 16 cores against 1 core
Is how I have done most of my tests.
Good result. On equal hardware, on a par with Stockfish 2.1, Komodo 2.03, Rybka 3, stronger than the new wave of engines like Texel, Hannibal, Nirvana, Cheng.