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I am running LeelaZero on my small and slow pc, Win10, without modern GPU, it is running on the CPU only (something like a cherry trail processor).

Could you give me some hints which settings might perform best under such conditions?
I presume the NN used should be as small as possible?! Any experience you want to share is welcome, thanks in advance.
(I dont expect miracles, of course, with such hardware limitations.)

chessico wrote: ↑Wed Jan 09, 2019 8:39 pm I am running LeelaZero on my small and slow pc, Win10, without modern GPU, it is running on the CPU only (something like a cherry trail processor).

Could you give me some hints which settings might perform best under such conditions?
I presume the NN used should be as small as possible?! Any experience you want to share is welcome, thanks in advance.
(I dont expect miracles, of course, with such hardware limitations.)

I used the 11248 network in my 72nd Amateur Series Division 4 tournament.

--threads=1 ramlimit-mb=256 --no-ponder

chessico wrote: ↑Wed Jan 09, 2019 8:39 pm I am running LeelaZero on my small and slow pc, Win10, without modern GPU, it is running on the CPU only (something like a cherry trail processor).

Could you give me some hints which settings might perform best under such conditions?
I presume the NN used should be as small as possible?! Any experience you want to share is welcome, thanks in advance.
(I dont expect miracles, of course, with such hardware limitations.)

128x10 networks or smaller networks would be the best your cpu.

Try these networks or 35xx series network(128x10) .This rating list shows 35xx network are as strong as 32xx network in blitz.
https://docs.google.com/spreadsheets/d/ ... =868347223
https://github.com/dkappe/leela-chess-w ... d-Networks

Graham Banks wrote: ↑Wed Jan 09, 2019 10:08 pm

chessico wrote: ↑Wed Jan 09, 2019 8:39 pm I am running LeelaZero on my small and slow pc, Win10, without modern GPU, it is running on the CPU only (something like a cherry trail processor).

Could you give me some hints which settings might perform best under such conditions?
I presume the NN used should be as small as possible?! Any experience you want to share is welcome, thanks in advance.
(I dont expect miracles, of course, with such hardware limitations.)

I used the 11248 network in my 72nd Amateur Series Division 4 tournament.

--threads=1 ramlimit-mb=256 --no-ponder

As a general rule, chess engines requires both search and evaluation.
20x256 networks can give you the best evaluation only when you have adequate power to search, GPU with cuda cores.
I am pretty sure that 35xx networks or distilled networks that I mentioned in above post will be much stronger than your 20x256 in your cpu setting.

I’m in the process of finding the optimal dimensions for a cpu-only network.

The approach I am taking is to distill a 20 block network into a smaller size using the larger network to train the smaller one. My network of choice is 11258. I am using se–film networks, Which are somewhat stronger than the vanilla resent networks of the same size.

So far I have distilled 16x2, 96x8 and am currently distilling 112x9. They are available from my distilled networks page, along with some others. https://github.com/dkappe/leela-chess-w ... d-Networks

To give you a sense of performance, I have an ongoing tournament (including some t35 128x10-se nets).

I thank you all very much, your answers will certainly help me to get Leela working a little better on my mini pc. And special thanks to Dietrich for his distillations, I will try them and compare how they work on my machine.

Hi
for CPU use I would suggest, worth a try:

lc0 >= 0.17 to allow ponder on
scs 64x8 network run1 550000 steps (link). Not too large for speed sake, but skilled enough. So well balanced...
Cpuct MCTS 1.700000
Minibatch size 16
Max prefetch nodes 0
Scale thinking time 1.200000
NN cache size 400000 (to be tuned according to the RAM use you grant)
Other settings=default ones

Indeed 35xx series networks (128x10) are getting interesting, latest ones seem to reach even level as the above arrangement (older ones do not). But I played very few games opposing these, so this needs further testing.

16x2 distilled 11258 is far too weak, despite its speed. Cannot compete with the scs 64x8, and loses as well against the non-distilled, very slow on CPU, same 11258 NN. I tried several higher MCTS settings to wider the search itself, as speed provides depth anyway, but no way. Big thank anyway to dkappe for his work and for sharing it, much useful (and fun!) & appreciated. I am looking forward to test the promising 96x8 one.

All my tests were using a single core on CPU (no GPU). So my conclusions may of course not apply to more powerful hardware

I have a question. Can someone tell me if the following installation is correct?

Currently I have only a laptop core duo 2x 2.4 Ghz 64 Bit.

Also I have LC0 v20.1 installed as Windows only.

NN = 11258-16x2-se-4.pb
client.exe
Lc0.exe
libopenblas.dll
(all in the same folder)

I clicked on the Lc0.exe and gave the command
"go nodes 100".

Then I installed Lc0 as UCI engine under ChessBase.

Lc0 runs well and reaches 1 - 3 kN /s. Search Depth 13 in the middlegame: after 150 seconds.

Is that good with my hardware? Or have I forgotten something, perhaps an important command?

Eduard wrote: ↑Fri Jan 11, 2019 10:42 pm I have a question. Can someone tell me if the following installation is correct?

Currently I have only a laptop core duo 2x 2.4 Ghz 64 Bit.

Also I have LC0 v20.1 installed as Windows only.

NN = 11258-16x2-se-4.pb
client.exe
Lc0.exe
libopenblas.dll
(all in the same folder)

I clicked on the Lc0.exe and gave the command
"go nodes 100".

Then I installed Lc0 as UCI engine under ChessBase.

Lc0 runs well and reaches 1 - 3 kN /s. Search Depth 13 in the middlegame: after 150 seconds.

Is that good with my hardware? Or have I forgotten something, perhaps an important command?

Better depth than I was getting.

64x6 or 64x8? The 96x8-se is already released. 112x9-se is at almost 140k of 200k steps.

Next is 144x11-se.