LCZero: Progress and Scaling. Relation to CCRL Elo

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Milos
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Milos »

CMCanavessi wrote:
Werewolf wrote:
nabildanial wrote:
Werewolf wrote:
Milos wrote:
980M is just a tad bit slower than regular 980 which is much more powerful card especially for ML compared to 1060.
Are you basing that on their GFLOPS processing power?

The 1060 is roughly 3800 GFLOPS and the 980 is 4600 GFLOPS.
I have both 970 and 1060, and their performance are the same for gaming, video rendering and for using Leela. 980 is around 20%-30% faster than a 970 and it should be the same against 1060 too.
That's interesting, but what I was asking Milos is what it is that makes the 980 faster.

Is it processing power measured in GFLOPS? Is that the yardstick we use to measure performance for LCZero prior to buying a card where we can actually test nps?
The only thing that really matters for Leela (and deep learning in general) is the number of CUDA cores. The 970 has 1644, and the 980 has 2048. There's the performance difference.


Here's a table with all nvidia gpu specs:
https://www.studio1productions.com/Arti ... -Chart.htm
Lol, ofc it is not only the number of cores but also core frequency. And, hear, hear, Num_of_cores*2*core_frequency = Num_of_GFLOPS ;).
duncan
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by duncan »

Nay Lin Tun wrote:Leela Milestones and future Goals
(It is time to celebrate and hype about leela)


A lot of milestones happened to Leela in 2 months, a lot more than a lot of people were expected and the future is brighter than 5 years old distributed network stockfish project( initial stockfish 1.3 is 10 years old now)

Goals!

1. To reach the level of A0 (estimated 3300 rating in GTX 1060)

2. To reach the level of latest stockfish on GTX 1060 ( estimated 3550+ rating on 8 cores desktop)

3. To surpass the rating of stockfish on GTX 1060.(getting 3600+)



Achievement milestones

1. Finished 10 millions games,

2. Reached 2800+, super GM level, on 1060 GTX.

3. Gofundme got €5000+ donation for the project.



Future Leela

1. Network will soon be expanded into 15x192 and may further expand into 20x256

( exactly as A0)

2. cuDNN or tensorflow implementation will increase the speed/ elo of Leela on NVIDIA cards (?50% ?100% ?200%), ( too bad for AMD cards though).

3. syzgy Tablebase

4. Auto resign will speed up training up to 30%.

Good luck Leela.
when do you expect to get the results in elo for target 2. cuDNN?
Albert Silver
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Location: Rio de Janeiro, Brazil

Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Albert Silver »

duncan wrote:
Nay Lin Tun wrote:Leela Milestones and future Goals
(It is time to celebrate and hype about leela)


A lot of milestones happened to Leela in 2 months, a lot more than a lot of people were expected and the future is brighter than 5 years old distributed network stockfish project( initial stockfish 1.3 is 10 years old now)

Goals!

1. To reach the level of A0 (estimated 3300 rating in GTX 1060)

2. To reach the level of latest stockfish on GTX 1060 ( estimated 3550+ rating on 8 cores desktop)

3. To surpass the rating of stockfish on GTX 1060.(getting 3600+)



Achievement milestones

1. Finished 10 millions games,

2. Reached 2800+, super GM level, on 1060 GTX.

3. Gofundme got €5000+ donation for the project.



Future Leela

1. Network will soon be expanded into 15x192 and may further expand into 20x256

( exactly as A0)

2. cuDNN or tensorflow implementation will increase the speed/ elo of Leela on NVIDIA cards (?50% ?100% ?200%), ( too bad for AMD cards though).

3. syzgy Tablebase

4. Auto resign will speed up training up to 30%.

Good luck Leela.
when do you expect to get the results in elo for target 2. cuDNN?
There may be a delay since although the new beta may have a 4x speedup, it is performing over 100 Elo worse in matches. The problem is that over 180 changes were made also to the code, none of which were properly tested. When I asked about this I was told there is no time for testing and that 'intuition' was the rule for code changes. Sigh.
"Tactics are the bricks and sticks that make up a game, but positional play is the architectural blueprint."
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Daniel Mehrmann
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Full name: Daniel Mehrmann

Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Daniel Mehrmann »

I think 2950 CCRL elo is a way to high.

I tested Leela id 234 versus Naum 4.6, Deep Shredder 11 and ProDeo. After my results 10+10/game, she has a rating of around 2850 CCRL elo.

Regards
Daniel
Werewolf
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Werewolf »

Daniel Mehrmann wrote:I think 2950 CCRL elo is a way to high.

I tested Leela id 234 versus Naum 4.6, Deep Shredder 11 and ProDeo. After my results 10+10/game, she has a rating of around 2850 CCRL elo.

Regards
Daniel
Depends on your graphics card
JJJ
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by JJJ »

And here is another elo jump in selfplay with the ID 237. 150 elo overall in less than a week folks.
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Laskos
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Full name: Kai Laskos

Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Laskos »

JJJ wrote:And here is another elo jump in selfplay with the ID 237. 150 elo overall in less than a week folks.
Nah, this is self-play with fixed number of playouts. But the nets became slower. At fixed time against standard engine, there was little progress lately, even with the introduction of the larger net, and only on GPU, not on CPU (but CPU results will be anyway irrelevant). On GPU, with the introduction of ID227 larger 15x192 net, maybe there was some improvement, 20-30 Elo points or so, no more, because the nets were much slower. But since larger nets, from ID227 to ID237, in their 500,000 games, I cannot measure sensible improvement at fixed time against a standard engine, probably less than 15 Elo points. This is somehow strange, as the nets are fresh to learn.


For curiosity, I plotted a graph of LC0 at 1 playout pitted against Komodo 11.3.1 at depth=1. You have to keep in mind that this is not fixed time, this is more comparing the evaluations, and I took Komodo because it is among the strongest standard engines at depth=1.
The large, sudden increases are the introduction of larger nets: at ID123 and ID227. Each datapoint is 1000 games, and ID237 shows some small progress compared to ID227, but it is offset somehow by maybe lower speed by 3% or so in fixed time games.

Image
frankp
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Joined: Sun Mar 12, 2006 3:11 pm

Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by frankp »

Nice graphs Kai.
Certainly the 'accuracy' graph on tensorboard is the highest it has ever been, perhaps worryingly so, which is reflected in your results.
I guess it is better to be better if slower, since hardware tends to get better.

Just wish the 'must beat everything else now or the project is failing' brigade, would take a step back. This really is different to the usual 'copy' stockfish and produce another AB searcher. Interesting to see how far it can go. Unfortunately some around the project seem equally infected and want to install egtb so leela does better (less worse) in TCEC, which from my perspective contaminates the zero approach.
Milos
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by Milos »

frankp wrote:Just wish the 'must beat everything else now or the project is failing' brigade, would take a step back. This really is different to the usual 'copy' stockfish and produce another AB searcher. Interesting to see how far it can go. Unfortunately some around the project seem equally infected and want to install egtb so leela does better (less worse) in TCEC, which from my perspective contaminates the zero approach.
Pretty rational comment. Regarding features such as EGBTs I think there is no harm in adding them as long as they are not used in self-play and reference testing.
JohnS
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Re: LCZero: Progress and Scaling. Relation to CCRL Elo

Post by JohnS »

frankp wrote:Just wish the 'must beat everything else now or the project is failing' brigade, would take a step back. This really is different to the usual 'copy' stockfish and produce another AB searcher. Interesting to see how far it can go. Unfortunately some around the project seem equally infected and want to install egtb so leela does better (less worse) in TCEC, which from my perspective contaminates the zero approach.
Agreed. I'm spending a lot of time following this project and find it fascinating. Who knows how strong Leela will become, but the progress to date is impressive to me and clearly shows that new approaches can work in chess.

I ignore the "failing brigade" and enjoy the interesting results and progress.

Kai's work is really interesting in this regard, as are the two ratings lists that clearly show how much it has progressed, even if the absolute Elo numbers may not be entirely accurate (https://docs.google.com/spreadsheets/d/ ... edit#gid=0;
https://docs.google.com/spreadsheets/d/ ... edit#gid=0).