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23/10/21: Optimized for Android: SFMXnps

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@github-actions github-actions released this 15 Aug 10:19
64937b7

SFMXnps is stronger than Stockfish17dev on Android. To proof this and, in particular, to become more familiar with testing on an Android device, a large number of c-chess-cli tournaments were performed and are shown below.

All tournaments were played on a Xiaomi Poco M3 (Android 12, Snapdragon 662, 4 GB RAM) using Termux and the CETSA script, which utilizes c-chess-cli. Concurrency was set to 4 and TCs from 5+0.05s to 120+1.2s with 1 thread per engine were tested. Also one tournament with 2 threads and concurrency 2 was carried out to test the SMP performance. More details are given in the configuration files which can be, together with the played games, downloaded below.
The absolute value of the rating was set to 3100 ELO for each tournament and the rating offsets and all other values were calculated by the script with Bayeselo. Opening suite was UHO_2022_8mvs_+110_+119.epd. It should be noted that such kind of openings enlarge ELO differences but have the advantage of reduced draw rates.

TC: 5+0.05s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3142   0.0   17   16   250  154.5  61.8  105   46   99  42.0  39.6  3058 
   2 SFnps230802    3058  83.1   16   17   250   95.5  38.2   46  105   99  18.4  39.6  3142 
---------------------------------------------------------------------------------------------------------

TC: 7+0.07s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3139   0.0   16   16   250  152.5  61.0   98   43  109  39.2  43.6  3061 
   2 SFnps230802    3061  77.1   16   16   250   97.5  39.0   43   98  109  17.2  43.6  3139 
---------------------------------------------------------------------------------------------------------
 
TC: 10+0.1s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3142   0.0   16   16   250  155.0  62.0  101   41  108  40.4  43.2  3058 
   2 SFnps230802    3058  84.5   16   16   250   95.0  38.0   41  101  108  16.4  43.2  3142 
---------------------------------------------------------------------------------------------------------

TC: 15+0.15s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3125   0.0   15   15   250  143.0  57.2   83   47  120  33.2  48.0  3075 
   2 SFnps230802    3075  50.4   15   15   250  107.0  42.8   47   83  120  18.8  48.0  3125 
---------------------------------------------------------------------------------------------------------

TC: 20+0.2s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3127   0.0   20   19   150   86.5  57.7   51   28   71  34.0  47.3  3073 
   2 SFnps230802    3073  53.0   19   20   150   63.5  42.3   28   51   71  18.7  47.3  3127 
---------------------------------------------------------------------------------------------------------

TC: 25+0.25s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3124   0.0   19   19   150   85.5  57.0   47   26   77  31.3  51.3  3076 
   2 SFnps230802    3076  48.2   19   19   150   64.5  43.0   26   47   77  17.3  51.3  3124 
---------------------------------------------------------------------------------------------------------

TC: 25+0.25s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3135   0.0   18   18   150   90.0  60.0   51   21   78  34.0  52.0  3065 
   2 SFnps230802    3065  69.4   18   18   150   60.0  40.0   21   51   78  14.0  52.0  3135 
---------------------------------------------------------------------------------------------------------

TC: 40+0.4s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3119   0.0   20   20   150   83.0  55.3   50   34   66  33.3  44.0  3081 
   2 SFnps230802    3081  37.3   20   20   150   67.0  44.7   34   50   66  22.7  44.0  3119 
---------------------------------------------------------------------------------------------------------

TC: 60+0.6s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3124   0.0   18   18   150   85.5  57.0   46   25   79  30.7  52.7  3076 
   2 SFnps230802    3076  48.5   18   18   150   64.5  43.0   25   46   79  16.7  52.7  3124 
---------------------------------------------------------------------------------------------------------
 
TC: 90+0.9s   Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3117   0.0   17   17   150   82.5  55.0   39   24   87  26.0  58.0  3083 
   2 SFnps230802    3083  34.4   17   17   150   67.5  45.0   24   39   87  16.0  58.0  3117 
---------------------------------------------------------------------------------------------------------
 
TC: 120+1.2s  Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3117   0.0   20   20   100   55.0  55.0   24   14   62  24.0  62.0  3083 
   2 SFnps230802    3083  34.1   20   20   100   45.0  45.0   14   24   62  14.0  62.0  3117 
---------------------------------------------------------------------------------------------------------

TC: 120+1.2s  Threads: 2
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3121   0.0   20   20   100   56.0  56.0   26   14   60  26.0  60.0  3079 
   2 SFnps230802    3079  41.1   20   20   100   44.0  44.0   14   26   60  14.0  60.0  3121 
---------------------------------------------------------------------------------------------------------

TC: 180+1.0s  Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3116   0.0   22   22   100   54.5  54.5   27   18   55  27.0  55.0  3084 
   2 SFnps230802    3084  31.1   22   22   100   45.5  45.5   18   27   55  18.0  55.0  3116 
---------------------------------------------------------------------------------------------------------

TC: 180+1.8s  Threads: 1
Rank Name          Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801  3134   0.0   30   30    50   30.0  60.0   17    7   26  34.0  52.0  3066 
   2 SFnps230802    3066  67.4   30   30    50   20.0  40.0    7   17   26  14.0  52.0  3134 
---------------------------------------------------------------------------------------------------------
  Δ = delta from the next higher rated opponent
  # = number of games played
  Σ = total score, 1 point for win, 1/2 point for draw

Older tournaments:
image
Two recent tourneys added to the graph:
SFMXvsSFonAndroid2a

SF16 has a smaller net than current SF17dev and is faster than SF20230802. Could it be that Stockfish16nps is stronger than SFMX?

TC: 10+0.1s  Threads: 1
Rank Name           Rating   Δ     +    -     #     Σ    Σ%     W    L    D   W%    =%   OppR 
   1 SFMXnps230801   3137   0.0   19   19   300  173.5  57.8  107   60  133  35.7  44.3  3082 
   2 SFnps16         3116  20.8   19   19   300  160.5  53.5   92   71  137  30.7  45.7  3092 
   3 SFnps20230802   3047  69.3   19   19   300  116.0  38.7   49  117  134  16.3  44.7  3127 
---------------------------------------------------------------------------------------------------------
  Δ = delta from the next higher rated opponent
  # = number of games played
  Σ = total score, 1 point for win, 1/2 point for draw

Not very likely but not impossible either. Thus the above question will be answered by future tournaments at various TCs.
Edit 09/09/23: See https://github.com/Joachim26/StockfishNPS/releases/tag/Master_DroidSFnps-bb4c63b3

Windows tournaments included in the graph:
image
Reasonable results, since the speed ratio of the two engines is smaller on Windows (~1.4 for modern builds) than on Android (~1.6). Even more tournaments with (much) more games should be performed to give clearer results.