It seems the table got broken, I hope this one stays.
System size (number of atoms) Ubuntu 22.04 WSL2/W11 Enterprise Edition Ubuntu 22.04 Difference (native - WSL2)
GB 25095 nucleosome 18.18 ns/day 18.07 ns/day -0.11 -1%
2492 myoglobin 759.16 ns/day 931.53 ns/day 172.37 23%
304 TRPCage 1643.09 ns/day 2263.16 ns/day 620.07 38%
PME 1067095 STMV NPT 4fs 16.93 ns/day 17.43 ns/day 0.5 3%
1067095 STMV NVE 4fs 17.68 ns/day 18.46 ns/day 0.78 4%
408609 Cellulose NPT 4fs 44.54 ns/day 49.47 ns/day 4.93 11%
408609 Cellulose NVE 4fs 46.19 ns/day 50.24 ns/day 4.05 9%
90906 FactorIX NPT 4fs 195.93 ns/day 224.97 ns/day 29.04 15%
90906 FactorIX NVE 4fs 208.39 ns/day 233.16 ns/day 24.77 12%
23558 JAC NPT 4fs 482.40 ns/day 673.96 ns/day 191.56 40%
23558 JAC NPT 2fs 266.75 ns/day 387.01 ns/day 120.26 45%
23558 JAC NVE 4fs 501.50 ns/day 696.70 ns/day 195.2 39%
From: Martin Juhás
Sent: Wednesday, February 15, 2023 10:14 PM
To: AMBER Mailing List <amber.ambermd.org>
Subject: benchmarking Amber 22 with WSL2 on Windows 11
Dear Amber users,
I have been running some benchmarks of Amber 22 using Ubuntu 22.04 on WSL2 with Windows 11 and compared it to the native Ubuntu 22.04. Since there is not much information concerning WSL performance online, I would like to share my results with you. Based on my results, the slowdown due to virtualization tends to decrase with the increasing number of atoms in the system. For the common systems in drug-design projects, let's say 50-90K atoms, the difference is about 15-20%.
Perhaps someone did his own benchmarking and found ways to improve the performance, any comments are welcome.
Amber 22 with all available patches, CUDA 11.8
PC: 8CPU 11th Gen Intel(r) Core(tm) i9-11900 . 2.50GHz, NVIDIA RTX A4000, 128 GB RAM
Average timings for all steps
System size (number of atoms)
Ubuntu 22.04 WSL2/W11 Enterprise Edition
Ubuntu 22.04
Difference (native - WSL2)
GB
25095
nucleosome
18.18
ns/day
18.07
ns/day
-0.11
-1%
2492
myoglobin
759.16
ns/day
931.53
ns/day
172.37
23%
304
TRPCage
1643.09
ns/day
2263.16
ns/day
620.07
38%
PME
1067095
STMV NPT 4fs
16.93
ns/day
17.43
ns/day
0.5
3%
1067095
STMV NVE 4fs
17.68
ns/day
18.46
ns/day
0.78
4%
408609
Cellulose NPT 4fs
44.54
ns/day
49.47
ns/day
4.93
11%
408609
Cellulose NVE 4fs
46.19
ns/day
50.24
ns/day
4.05
9%
90906
FactorIX NPT 4fs
195.93
ns/day
224.97
ns/day
29.04
15%
90906
FactorIX NVE 4fs
208.39
ns/day
233.16
ns/day
24.77
12%
23558
JAC NPT 4fs
482.40
ns/day
673.96
ns/day
191.56
40%
23558
JAC NPT 2fs
266.75
ns/day
387.01
ns/day
120.26
45%
23558
JAC NVE 4fs
501.50
ns/day
696.70
ns/day
195.2
39%
Martin Juhás
Department of Pharmaceutical Chemistry and Pharmaceutical Analysis
Charles University, Faculty of Pharmacy in Hradec Králové
Akademika Heyrovského 1203/8, 500 05 Hradec Králové
Czech Republic
E-mail: juhasm.faf.cuni.cz<mailto:juhasm.faf.cuni.cz>
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Received on Wed Feb 15 2023 - 13:30:04 PST
