As an architecture geek I'm rooting for Risc-V too, or at least enough to see it have commercial adoption. Would love to have a box now, but the few SBC's I've seen have been pretty cost prohibitive and more for testing purposes.
M1 Apple Silicon for Chess?
Moderator: Ras
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Re: M1 Apple Silicon for Chess?
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- Full name: Alayan Feh
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Re: M1 Apple Silicon for Chess?
Or I just spend my time wisely. My intention here was just to point out the in my view unwarranted negativity. It reminds me of the initial reception in this forum of Alpha Chess Zero (and many here will probably still deny that LC0 wouldn't have existed without Deepmind's papers).
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Re: M1 Apple Silicon for Chess?
Hi! Could you please give me the link to download LC0 and Cfish binary for Silicon M1? I already have Stockfish M1 (1 milion nps versus 6200 knps with Rosetta 2 on my Mac mini M1 8-256 GB) I can report here the results of my engine vs engine matches if you are interested.George Sobala wrote: ↑Wed Nov 25, 2020 8:00 am Benchmarks on a MacBook Air 16GB 8-core GPU
Stockfish compiled for M1 Apple Silicon, commit f9595828eb7e5e970b0be3ee5f84ddd726845523 Wed 11 Nov
Cfish compiled for M1 Apple Silicon, commit 6193ed1c3809cb4b71ad8f630fa4f52160390fb6 Sun 15 NovCode: Select all
bench 2408119 bench 64 1 20 2270034 bench 64 2 20 4503092 bench 64 4 20 9069926 bench 64 6 20 10820178 bench 64 8 20 12438598
dragon-ox running under Rosetta-2Code: Select all
bench 2844055 bench 64 1 20 2614400 bench 64 2 20 5232224 bench 64 4 20 10152288 bench 64 6 20 12388337 bench 64 8 20 14935531
lc0, compiled for M1 running on CPU using Apple's Accelerate framework, output of benchmark first position only:Code: Select all
command nodes sec nps bench 1 1915866 4.80 399139 bench 2 3653649 4.70 777372 bench 4 5690302 3.36 1693542
lc0, compiled for M1 running on GPU using OpenCL, output of benchmark first position only:Code: Select all
--backend=blas --weights=J92-330 97 --backend=blas --weights=T70net-703810 1703
Code: Select all
--backend=opencl --weights=J92-330 104 --backend=opencl --weights=T70net-703810 3431
Thank you in advance, AlexChess
Chess engines and dedicated chess computers fan since 1981
macOS Sequoia 16GB-512GB, Windows 11 & Ubuntu ARM64.
ProteusSF Dev Forum

ProteusSF Dev Forum
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Re: M1 Apple Silicon for Chess?
I would really like to know how this one would perform https://shop.solid-run.com/product/SRLX ... E064H08CH/
Anyone that would speculate on that ?
Anyone that would speculate on that ?
“Modern chess is too much concerned with things like pawn structure. Forget it, checkmate ends the game.” – Nigel Short
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Re: M1 Apple Silicon for Chess?
Mekiroje wrote: ↑Sat Feb 06, 2021 6:31 pm I would really like to know how this one would perform https://shop.solid-run.com/product/SRLX ... E064H08CH/
Anyone that would speculate on that ?

Yes, HoneyComb is wonderful.
If Trusted Computing wins, it will be my way. Ready to use Linux on ARM & open source. But until now, simply lowering a little the system protection, I'm able to use every application and OS with my surprising fast Mac mini M1. So, returning to the topic, I want to understand how to compile NATIVE Silicon M1 chess engines (I already have Stockfish ARM64 *1.1 Mnps* that easily wins against Ethereal 12.75 64 bit Rosetta 2)
Chess engines and dedicated chess computers fan since 1981
macOS Sequoia 16GB-512GB, Windows 11 & Ubuntu ARM64.
ProteusSF Dev Forum

ProteusSF Dev Forum
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Re: M1 Apple Silicon for Chess?
From your benchmark, it looks like it's pretty solid, in NNUE it will be slower because ARM lacks good AVX support.George Sobala wrote: ↑Wed Nov 25, 2020 10:02 am Comparison of Stockfish and Cfish running on 8 cores, classical v NNUE, on M1 and iMac Pro Xeon W
run using
stockfish|cfish 64 8 20 default depth classical|NNUE
iMac Pro compile options:Code: Select all
Stockfish Cfish M1 classical 16319718 17118388 M1 NNUE 10100445 12759621 Xeon W classical 16900088 17929299 Xeon W NNUE 13631405 14191552
Code: Select all
george@Georges-iMac-Pro-2 ~ % stockfish Stockfish 141120 by the Stockfish developers (see AUTHORS file) compiler Compiled by g++ (GNUC) 10.2.0 on Apple Compilation settings include: 64bit AVX512 BMI2 AVX2 SSE41 SSSE3 SSE2 POPCNT __VERSION__ macro expands to: 10.2.0 quit george@Georges-iMac-Pro-2 ~ % cfish Cfish 141120 64 BMI2 by Syzygy based on Stockfish compiler Compiled by gcc (GNUC) 10.2.0 on Apple Compilation settings include: 64bit AVX512 BMI2 AVX2 SSE41 SSSE3 SSE2 POPCNT __VERSION__ macro expands to: 10.2.0 quit
The SF classic result is much better, 4 big core and 4 small core matching Xeon's 8 big cores.
Can you also run just one thread for SF classic, for both M1 and Xeon? I'm very interested in single threaded performance of a CPU.
Thanks!
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Re: M1 Apple Silicon for Chess?
Actually I got impatient so I went on Scaleway and rented an M1.George Sobala wrote: ↑Wed Nov 25, 2020 10:02 am Comparison of Stockfish and Cfish running on 8 cores, classical v NNUE, on M1 and iMac Pro Xeon W
run using
stockfish|cfish 64 8 20 default depth classical|NNUE
Code: Select all
Stockfish Cfish M1 classical 16319718 17118388 M1 NNUE 10100445 12759621 Xeon W classical 16900088 17929299 Xeon W NNUE 13631405 14191552
Here's what I got with Stockfish Classical
./stockfish bench
3568884 nps
./stockfish bench 64 1 20
3024394 nps
./stockfish bench 64 8 20
17084333 nps
The Macbook 2019 that my workplace provided, which has a single thread Geekbench score of around 1050 gets this,
./stockfish bench
2168394 nps
./stockfish bench 64 1 20
1908261 nps
The Intel version was compiled with x86-64-bmi2. So the m1 is about 64% faster in ST than the Intel Mac, about in line with what Geekbench suggests. Would love it if someone with the latest Zen 3 do a similar test (especially single thread).
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Re: M1 Apple Silicon for Chess?
Performance of Stockfish dev from today looks like:
This is on an M1 Air. I love the fact that it's 100% fanless.
Code: Select all
Zen1 1700X 3.2GHz: 1520000
Ivy Bridge 3.5GHz: 1760000
Haswell 3.4GHz: 1860000
M1 3.2GHz: 2390000
Zen2 3900X 3.8-4.2GHz: 2490000
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Re: M1 Apple Silicon for Chess?
That's also a pretty good result for M1, matching Zen 2 while having weaker vector instructions.
I'll pick an M1 up eventually. Overall seems better than any alternative. Pretty sure they will provide higher core count models as well, but I dont really need that many cores.
I'll pick an M1 up eventually. Overall seems better than any alternative. Pretty sure they will provide higher core count models as well, but I dont really need that many cores.