remove the uselsss weight return type from election provider API #9569

kianenigma · 2021-08-16T14:54:12Z

This is my retaliation against my current way of benchmarking intra-pallet hooks.

In the past, I tried to push such operations toward returning a weight. This worked fine, but it made all the APIs quite ugly, with no clear benefit to compensate for it.

Over time my sentiment changed and I disliked this way of weighing things more and more. Now, I strongly think that a combination of the below are much better:

self-weighing functions
control hooks that allow the user of a trait to set worse case values in it (see trait ElectionDataProvider::add_voter etc.).

In this PR, I move all of these on_initialize intra-pallet interactions to be self-weighing. This means that the destination of a call will measure its own weight and directly register it with the system pallet (as mandatory, because this assumption is only for on_initialize stuff). The only responsibility of the call site is to ensure it is NOT benchmarking that piece of the code twice. This is why you see functions like create_snapshot are now split into create_snapshot_internal and create_snapshot_external.

part of paritytech/polkadot-sdk#461

polkadot companion paritytech/polkadot#3662

…ove-election-weight-api

kianenigma · 2021-08-17T08:34:01Z

/benchmark runtime pallet pallet_staking

parity-benchapp · 2021-08-17T08:34:03Z

Benchmark Runtime Pallet for branch "kiz-remove-election-weight-api" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     72.9
              µs

Reads = 5
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     72.9
              µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    57.04
              µs

Reads = 3
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    57.04
              µs

Reads = 3
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    60.58
              µs

Reads = 6
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    60.58
              µs

Reads = 6
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    52.23
    + s    0.052
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     51.91     0.234    0.4%
    2     51.61     0.128    0.2%
    4     52.74      0.17    0.3%
    6     52.75     0.432    0.8%
    8     53.31     0.161    0.3%
   10     52.21     0.142    0.2%
   12     52.44     0.194    0.3%
   14     52.86     0.261    0.4%
   16     52.82     0.208    0.3%
   18     52.45     0.075    0.1%
   20     52.97     0.143    0.2%
   22     53.43     0.288    0.5%
   24      53.1     0.155    0.2%
   26     53.15     0.265    0.4%
   28     53.82     0.146    0.2%
   30     55.31     0.082    0.1%
   32     54.28     0.712    1.3%
   34     55.35     0.282    0.5%
   36     55.64     0.363    0.6%
   38     55.43     0.239    0.4%
   40     56.02     0.216    0.3%
   42     56.16     0.314    0.5%
   44     54.74     0.476    0.8%
   46     54.24     0.279    0.5%
   48     55.04     0.093    0.1%
   50     54.88     0.111    0.2%
   52     54.77     0.141    0.2%
   54     54.84     0.181    0.3%
   56     55.09     0.234    0.4%
   58     55.45      0.21    0.3%
   60     55.31     0.141    0.2%
   62     55.47      0.39    0.7%
   64     55.31     0.108    0.1%
   66     55.88     0.194    0.3%
   68     55.07     0.464    0.8%
   70     55.44     0.234    0.4%
   72     56.12     0.199    0.3%
   74     56.66     0.265    0.4%
   76     56.25      0.22    0.3%
   78     56.21     0.267    0.4%
   80     56.46     0.136    0.2%
   82     56.58     0.241    0.4%
   84     56.64     0.343    0.6%
   86      56.8     0.298    0.5%
   88     56.65      0.37    0.6%
   90     56.27     0.218    0.3%
   92      57.3     0.274    0.4%
   94      56.9     0.192    0.3%
   96      57.5     0.303    0.5%
   98      57.1     0.178    0.3%
  100     57.14     0.232    0.4%

Quality and confidence:
param     error
s             0

Model:
Time ~=    52.41
    + s     0.05
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    84.94
    + s    2.409
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0      79.6     0.168    0.2%
    2     89.54     0.612    0.6%
    4      93.6     0.173    0.1%
    6     98.97     0.278    0.2%
    8     105.6     0.249    0.2%
   10     109.6     0.202    0.1%
   12     113.9       0.4    0.3%
   14     118.7     0.148    0.1%
   16     122.7      0.22    0.1%
   18     127.8     0.287    0.2%
   20       133     0.209    0.1%
   22     138.6     0.431    0.3%
   24     143.7     0.382    0.2%
   26     147.2     0.438    0.2%
   28     152.8     0.308    0.2%
   30       159     1.284    0.8%
   32       163     0.746    0.4%
   34     167.2      0.37    0.2%
   36     171.7     0.378    0.2%
   38       176     0.681    0.3%
   40     181.2     0.262    0.1%
   42     186.5     0.356    0.1%
   44     194.3     1.156    0.5%
   46     195.6     0.637    0.3%
   48     200.5     0.463    0.2%
   50       205     0.555    0.2%
   52     209.1     0.467    0.2%
   54     215.3      0.46    0.2%
   56     219.6     0.644    0.2%
   58     223.8     0.412    0.1%
   60     228.8     0.454    0.1%
   62     236.9     4.186    1.7%
   64     237.8     0.814    0.3%
   66     243.7     0.687    0.2%
   68     248.8      0.77    0.3%
   70     253.8     1.423    0.5%
   72     256.6     1.252    0.4%
   74     263.5     0.505    0.1%
   76     268.4     0.822    0.3%
   78     274.3     1.527    0.5%
   80     277.3     0.804    0.2%
   82     282.5     3.363    1.1%
   84     286.2     0.851    0.2%
   86     290.7     0.548    0.1%
   88     296.2     0.345    0.1%
   90     299.4      0.61    0.2%
   92     308.2      0.41    0.1%
   94     313.2     0.884    0.2%
   96     315.8     0.965    0.3%
   98     322.3     0.855    0.2%
  100     328.3     5.759    1.7%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    84.65
    + s    2.416
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    35.01
              µs

Reads = 6
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    35.01
              µs

Reads = 6
Writes = 2
Pallet: "pallet_staking", Extrinsic: "kick", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    23.46
    + k    16.51
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    k   mean µs  sigma µs       %
    1     43.92     0.145    0.3%
    3     78.56     0.151    0.1%
    5     109.3     1.379    1.2%
    7     136.7     0.301    0.2%
    9     171.1     2.288    1.3%
   11     201.2     0.313    0.1%
   13     232.1     0.586    0.2%
   15     271.1     1.746    0.6%
   17     300.2     1.006    0.3%
   19       341     1.728    0.5%
   21     363.2     1.458    0.4%
   23     395.1     2.787    0.7%
   25       425     0.836    0.1%
   27     468.9     1.007    0.2%
   29     495.6     1.114    0.2%
   31     537.7     4.159    0.7%
   33     556.4     1.092    0.1%
   35     606.3     1.524    0.2%
   37       640     9.632    1.5%
   39     658.8     4.067    0.6%
   41     706.6     2.324    0.3%
   43     744.7     8.727    1.1%
   45     769.3     2.398    0.3%
   47     795.5     2.021    0.2%
   49     831.8      1.92    0.2%
   51     866.2     3.661    0.4%
   53     892.2     2.107    0.2%
   55     941.1     10.31    1.0%
   57       971     12.43    1.2%
   59     999.2     7.713    0.7%
   61      1010     2.888    0.2%
   63      1044     5.648    0.5%
   65      1075     3.284    0.3%
   67      1119     12.05    1.0%
   69      1166     4.014    0.3%
   71      1188     13.94    1.1%
   73      1219     9.224    0.7%
   75      1248     5.133    0.4%
   77      1307     12.65    0.9%
   79      1328     1.799    0.1%
   81      1355     11.98    0.8%
   83      1393     5.882    0.4%
   85      1419     7.597    0.5%
   87      1440     13.42    0.9%
   89      1493     5.658    0.3%
   91      1532     11.24    0.7%
   93      1569     9.557    0.6%
   95      1567     8.124    0.5%
   97      1631     3.716    0.2%
   99      1642     9.634    0.5%
  101      1672     8.654    0.5%
  103      1707     7.243    0.4%
  105      1748     7.601    0.4%
  107      1789     10.96    0.6%
  109      1840     10.53    0.5%
  111      1853     11.13    0.6%
  113      1905     9.765    0.5%
  115      1966     10.47    0.5%
  117      1995     11.62    0.5%
  119      1975     10.92    0.5%
  121      2048     11.94    0.5%
  123      2045     14.87    0.7%
  125      2076     8.258    0.3%
  127      2128     11.63    0.5%

Quality and confidence:
param     error
k         0.015

Model:
Time ~=    19.54
    + k    16.55
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    42.18
    + n    5.608
              µs

Reads = 7 + (1 * n)
Writes = 2 + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     47.79     0.116    0.2%
    2     53.14     0.141    0.2%
    3     58.41     0.283    0.4%
    4      64.3     0.255    0.3%
    5     70.35     0.192    0.2%
    6     75.89     0.248    0.3%
    7     81.45     0.134    0.1%
    8     86.93     0.272    0.3%
    9     93.81     0.264    0.2%
   10     98.91     0.325    0.3%
   11     104.7     0.166    0.1%
   12     109.3     0.311    0.2%
   13     115.3     0.189    0.1%
   14     120.3     0.398    0.3%
   15     125.6     0.459    0.3%
   16     131.1     0.327    0.2%

Quality and confidence:
param     error
n          0.01

Model:
Time ~=    42.23
    + n    5.601
              µs

Reads = 7 + (1 * n)
Writes = 2 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    17.89
              µs

Reads = 3
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    17.89
              µs

Reads = 3
Writes = 0
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.36
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.36
              µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    28.27
              µs

Reads = 3
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    28.27
              µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.504
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.504
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.776
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.776
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     2.76
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     2.76
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.777
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.777
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    3.339
    + v    0.055
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
    0     2.839     0.026    0.9%
   20     4.356     0.031    0.7%
   40     5.561      0.03    0.5%
   60     6.751     0.058    0.8%
   80     7.887     0.019    0.2%
  100     8.976     0.048    0.5%
  120     10.14     0.016    0.1%
  140     11.25     0.032    0.2%
  160     12.48     0.036    0.2%
  180     13.69     0.062    0.4%
  200     14.46     0.078    0.5%
  220     15.78     0.074    0.4%
  240     16.59     0.041    0.2%
  260     18.11     0.058    0.3%
  280     18.84     0.038    0.2%
  300     20.55     0.043    0.2%
  320     21.12     0.057    0.2%
  340     22.36     0.162    0.7%
  360     23.41     0.047    0.2%
  380     24.77     0.272    1.0%
  400     25.89     0.232    0.8%
  420      26.9     0.198    0.7%
  440      27.8     0.048    0.1%
  460     28.96     0.039    0.1%
  480     30.77     0.034    0.1%
  500     31.32     0.076    0.2%
  520     32.26      0.06    0.1%
  540     33.31     0.049    0.1%
  560     34.65     0.037    0.1%
  580     35.71     0.054    0.1%
  600     37.61     0.095    0.2%
  620     38.02     0.063    0.1%
  640     39.17     0.042    0.1%
  660     40.24     0.073    0.1%
  680     41.35     0.051    0.1%
  700     42.42     0.041    0.0%
  720     43.51     0.051    0.1%
  740     44.72     0.046    0.1%
  760      45.8     0.077    0.1%
  780     46.87     0.045    0.0%
  800     47.99     0.045    0.0%
  820     49.24     0.044    0.0%
  840     50.34     0.042    0.0%
  860     51.44     0.074    0.1%
  880     52.62     0.054    0.1%
  900     53.96     0.252    0.4%
  920     54.94     0.071    0.1%
  940     55.92     0.069    0.1%
  960     57.06     0.066    0.1%
  980     58.21     0.058    0.0%
 1000     59.27     0.062    0.1%

Quality and confidence:
param     error
v             0

Model:
Time ~=    3.361
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     61.8
    + s    2.404
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     56.81     0.182    0.3%
    2     66.91     0.175    0.2%
    4     71.62      0.15    0.2%
    6     75.77     0.205    0.2%
    8     82.35     0.131    0.1%
   10     85.04     0.102    0.1%
   12     90.29     0.221    0.2%
   14     95.74      0.24    0.2%
   16     100.6     0.211    0.2%
   18     105.3     0.227    0.2%
   20       110     0.263    0.2%
   22       115     0.222    0.1%
   24     119.7       0.3    0.2%
   26     123.9     0.173    0.1%
   28     129.3     0.367    0.2%
   30     134.1     0.652    0.4%
   32     138.6     0.249    0.1%
   34     143.2     0.188    0.1%
   36     148.6     0.638    0.4%
   38     153.2     0.362    0.2%
   40       158     0.194    0.1%
   42     162.7     0.268    0.1%
   44     167.3     0.515    0.3%
   46       172     0.835    0.4%
   48     177.1     0.399    0.2%
   50     180.9     0.434    0.2%
   52       186     0.738    0.3%
   54     191.3     0.453    0.2%
   56     195.3     0.602    0.3%
   58     201.7     0.497    0.2%
   60     204.9     0.626    0.3%
   62     211.3     0.145    0.0%
   64     215.2     0.486    0.2%
   66     220.1     0.561    0.2%
   68     224.7     0.714    0.3%
   70       230     0.936    0.4%
   72     234.7      0.68    0.2%
   74     240.4      0.34    0.1%
   76     243.6     0.778    0.3%
   78     248.9     1.062    0.4%
   80     254.2     0.661    0.2%
   82     258.1     1.291    0.5%
   84     263.1     0.703    0.2%
   86     268.5     1.184    0.4%
   88       274     0.729    0.2%
   90       278     1.106    0.3%
   92     283.7     0.503    0.1%
   94     288.6     1.114    0.3%
   96       300     13.59    4.5%
   98     297.3     0.802    0.2%
  100     302.4     0.928    0.3%

Quality and confidence:
param     error
s         0.003

Model:
Time ~=    61.19
    + s    2.416
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     3794
    + s       20
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1       245     0.147    0.0%
   20     994.1     12.98    1.3%
   39      1732     13.89    0.8%
   58      2450     7.298    0.2%
   77      3141      12.1    0.3%
   96      3840     13.97    0.3%
  115      4522      17.8    0.3%
  134      5151     13.61    0.2%
  153      5796     18.03    0.3%
  172      6433     25.31    0.3%
  191      7046     17.09    0.2%
  210      7643     22.39    0.2%
  229      8224     22.51    0.2%
  248      8798     20.86    0.2%
  267      9381     21.35    0.2%
  286      9899     24.05    0.2%
  305     10420     22.57    0.2%
  324     10960      17.1    0.1%
  343     11450     14.09    0.1%
  362     11940     18.53    0.1%
  381     12410     26.08    0.2%
  400     12880      25.9    0.2%
  419     13300     33.15    0.2%
  438     13750     36.46    0.2%
  457     14180      37.5    0.2%
  476     14560     28.26    0.1%
  495     14950      29.3    0.1%
  514     15320     49.11    0.3%
  533     15900     61.04    0.3%
  552     16030     31.52    0.1%
  571     16360     46.45    0.2%
  590     16650     24.53    0.1%
  609     16980      49.2    0.2%
  628     17270     26.79    0.1%
  647     17510     29.79    0.1%
  666     17800     50.14    0.2%
  685     18020      22.8    0.1%
  704     18250     20.85    0.1%
  723     18470     29.12    0.1%
  742     18660     38.58    0.2%
  761     18870     37.76    0.2%
  780     19050     31.38    0.1%
  799     19200     28.57    0.1%
  818     19340        29    0.1%
  837     19450      33.2    0.1%
  856     19580     28.72    0.1%
  875     19680     37.04    0.1%
  894     19780     18.29    0.0%
  913     19840     16.92    0.0%
  932     19900     18.32    0.0%
  951     19940     25.26    0.1%
  970     19950     21.36    0.1%
  989     19970     29.49    0.1%

Quality and confidence:
param     error
s         0.224

Model:
Time ~=     3394
    + s    19.97
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    115.1
    + n    47.23
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     205.2     0.191    0.0%
    6     398.8      0.83    0.2%
   11     674.4     3.722    0.5%
   16     875.2     10.18    1.1%
   21      1120      15.8    1.4%
   26      1339     8.439    0.6%
   31      1595     8.353    0.5%
   36      1820     9.508    0.5%
   41      2060     12.55    0.6%
   46      2289     15.36    0.6%
   51      2513     11.41    0.4%
   56      2758     17.61    0.6%
   61      2980     14.55    0.4%
   66      3225     13.28    0.4%
   71      3461      14.1    0.4%
   76      3684      10.3    0.2%
   81      3918     14.89    0.3%
   86      4161     15.01    0.3%
   91      4371     10.33    0.2%
   96      4632     15.69    0.3%
  101      4893     15.81    0.3%
  106      5119     13.79    0.2%
  111      5374     18.09    0.3%
  116      5545     17.03    0.3%
  121      5801     20.27    0.3%
  126      6066     21.96    0.3%
  131      6320     18.57    0.2%
  136      6533     30.61    0.4%
  141      6757      16.8    0.2%
  146      7038     17.38    0.2%
  151      7243     19.65    0.2%
  156      7535     9.365    0.1%
  161      7711     19.41    0.2%
  166      7945     10.15    0.1%
  171      8205     22.48    0.2%
  176      8472     47.36    0.5%
  181      8701     22.12    0.2%
  186      8933     25.05    0.2%
  191      9152     18.71    0.2%
  196      9408     20.41    0.2%
  201      9632     38.07    0.3%
  206      9852     32.06    0.3%
  211     10060     32.69    0.3%
  216     10360     25.12    0.2%
  221     10510     23.15    0.2%
  226     10830     36.17    0.3%
  231     11060     34.31    0.3%
  236     11340     29.18    0.2%
  241     11480     30.84    0.2%
  246     11670     15.73    0.1%
  251     11940     32.83    0.2%
  256     12190     32.47    0.2%

Quality and confidence:
param     error
n          0.02

Model:
Time ~=    114.5
    + n    47.27
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    159.2
    + n    60.46
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     211.9     1.353    0.6%
    6     510.2     1.155    0.2%
   11     818.9     1.832    0.2%
   16      1130     11.77    1.0%
   21      1436     10.82    0.7%
   26      1734      12.8    0.7%
   31      2032     15.81    0.7%
   36      2330     13.13    0.5%
   41      2625     13.37    0.5%
   46      2940     16.75    0.5%
   51      3231     15.06    0.4%
   56      3548     13.26    0.3%
   61      3843     8.866    0.2%
   66      4141     16.83    0.4%
   71      4470     13.94    0.3%
   76      4785     25.99    0.5%
   81      5063     15.73    0.3%
   86      5372     21.49    0.4%
   91      5682     15.66    0.2%
   96      5985     14.67    0.2%
  101      6255     29.06    0.4%
  106      6590     14.08    0.2%
  111      6842     15.63    0.2%
  116      7212     16.81    0.2%
  121      7487     27.78    0.3%
  126      7798      25.7    0.3%
  131      8092     24.13    0.2%
  136      8425     19.76    0.2%
  141      8746     29.02    0.3%
  146      8964     16.41    0.1%
  151      9264      30.2    0.3%
  156      9568     28.75    0.3%
  161      9919     9.734    0.0%
  166     10130     10.23    0.1%
  171     10430     19.51    0.1%
  176     10800     22.85    0.2%
  181     11090     23.91    0.2%
  186     11520     34.14    0.2%
  191     11730     27.63    0.2%
  196     11960     36.28    0.3%
  201     12400     27.51    0.2%
  206     12630      30.5    0.2%
  211     12920     34.26    0.2%
  216     13150     25.66    0.1%
  221     13470     48.26    0.3%
  226     13870      34.2    0.2%
  231     14040      32.2    0.2%
  236     14470     36.67    0.2%
  241     14740     44.51    0.3%
  246     14950     39.63    0.2%
  251     15230     57.31    0.3%
  256     15740     35.79    0.2%

Quality and confidence:
param     error
n         0.029

Model:
Time ~=    164.4
    + n    60.44
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    48.95
    + l    0.074
              µs

Reads = 3 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    l   mean µs  sigma µs       %
    1     48.04     0.167    0.3%
    2     49.38      0.14    0.2%
    3     49.53     0.073    0.1%
    4     48.53     0.265    0.5%
    5     48.97     0.448    0.9%
    6     49.43     0.123    0.2%
    7      49.7     0.125    0.2%
    8     49.56     0.126    0.2%
    9     48.69     0.134    0.2%
   10     49.42     0.516    1.0%
   11     48.78     0.139    0.2%
   12     50.39     0.212    0.4%
   13     49.12     0.187    0.3%
   14      50.5     0.109    0.2%
   15     49.39     0.199    0.4%
   16     50.39      0.37    0.7%
   17     51.05     0.141    0.2%
   18     50.79     0.178    0.3%
   19     49.89     0.233    0.4%
   20     51.04     0.114    0.2%
   21     50.13     0.174    0.3%
   22     50.07     0.129    0.2%
   23     51.02     0.187    0.3%
   24     51.39     0.107    0.2%
   25     51.08     0.224    0.4%
   26     50.04     0.389    0.7%
   27     50.02     0.196    0.3%
   28     50.13     0.153    0.3%
   29     51.06     0.201    0.3%
   30     51.34     0.104    0.2%
   31     51.21      0.15    0.2%
   32     50.02     0.189    0.3%

Quality and confidence:
param     error
l         0.003

Model:
Time ~=    48.83
    + l    0.071
              µs

Reads = 3 + (0 * l)
Writes = 3 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + e    34.93
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    e   mean µs  sigma µs       %
    1     43.17     0.107    0.2%
    2     70.76     0.107    0.1%
    3      94.3     0.278    0.2%
    4     123.1     0.181    0.1%
    5     150.7     1.273    0.8%
    6     173.8     0.266    0.1%
    7     199.9      0.79    0.3%
    8     227.2     0.394    0.1%
    9     252.2     0.516    0.2%
   10     283.2     0.815    0.2%
   11     307.4     0.487    0.1%
   12     337.4     0.895    0.2%
   13     365.6     0.923    0.2%
   14     394.2     1.016    0.2%
   15     422.3     0.995    0.2%
   16     453.9     8.408    1.8%
   17     480.9     1.002    0.2%
   18     506.4      1.11    0.2%
   19     541.1     0.945    0.1%
   20     562.3     1.064    0.1%
   21     597.7     1.326    0.2%
   22     628.2     1.233    0.1%
   23     663.6     9.262    1.3%
   24     691.6     2.253    0.3%
   25     727.8     5.591    0.7%
   26     754.8     1.275    0.1%
   27     789.6     3.655    0.4%
   28     825.5     14.58    1.7%
   29       850     3.833    0.4%
   30     888.7     7.878    0.8%
   31     936.6     14.56    1.5%
   32     965.6      15.6    1.6%
   33     975.7     1.838    0.1%
   34      1013     6.758    0.6%
   35      1047     2.213    0.2%
   36      1086     7.721    0.7%
   37      1098     6.826    0.6%
   38      1125     5.718    0.5%
   39      1170     11.12    0.9%
   40      1184     10.21    0.8%
   41      1219     14.79    1.2%
   42      1262     6.685    0.5%
   43      1303     10.65    0.8%
   44      1353     14.48    1.0%
   45      1365     8.182    0.5%
   46      1408     10.67    0.7%
   47      1436     11.65    0.8%
   48      1473     13.85    0.9%
   49      1491     7.271    0.4%
   50      1555     16.42    1.0%
   51      1583     7.809    0.4%
   52      1612      10.7    0.6%
   53      1650     6.306    0.3%
   54      1693     9.445    0.5%
   55      1715      11.4    0.6%
   56      1768     11.56    0.6%
   57      1797     14.41    0.8%
   58      1841     11.43    0.6%
   59      1877     14.79    0.7%
   60      1909     11.02    0.5%
   61      1952     15.93    0.8%
   62      1983     12.87    0.6%
   63      2035     13.79    0.6%
   64      2056     12.77    0.6%
   65      2106     11.94    0.5%
   66      2144     11.61    0.5%
   67      2177     17.85    0.8%
   68      2218     4.989    0.2%
   69      2242     11.87    0.5%
   70      2269      13.4    0.5%
   71      2315     10.17    0.4%
   72      2365     10.26    0.4%
   73      2401     11.92    0.4%
   74      2444     15.93    0.6%
   75      2485     12.53    0.5%
   76      2492     9.015    0.3%
   77      2535     8.263    0.3%
   78      2601     6.901    0.2%
   79      2628     12.13    0.4%
   80      2650      13.2    0.4%
   81      2755     8.378    0.3%
   82      2736     15.33    0.5%
   83      2792     12.77    0.4%
   84      2850     12.59    0.4%
   85      2905     13.91    0.4%
   86      2909     10.13    0.3%
   87      2980     13.02    0.4%
   88      2997     16.44    0.5%
   89      3064     11.53    0.3%
   90      3076     8.505    0.2%
   91      3124     12.95    0.4%
   92      3138     6.352    0.2%
   93      3256     20.45    0.6%
   94      3236     13.82    0.4%
   95      3324     19.67    0.5%
   96      3337     16.02    0.4%
   97      3423     16.02    0.4%
   98      3421     8.561    0.2%
   99      3474     7.922    0.2%
  100      3498     13.84    0.3%

Quality and confidence:
param     error
e         0.073

Model:
Time ~=        0
    + e    35.16
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    72.36
    + s    2.404
              µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1     72.72     0.157    0.2%
    2        77     0.536    0.6%
    3     78.26     0.389    0.4%
    4     81.51     0.129    0.1%
    5     83.93     0.284    0.3%
    6     86.56     0.519    0.5%
    7     88.71     0.151    0.1%
    8     91.03     0.263    0.2%
    9     93.98     0.978    1.0%
   10     95.95     0.283    0.2%
   11     98.24     0.166    0.1%
   12     101.4     0.345    0.3%
   13     104.1     0.249    0.2%
   14     107.8     0.301    0.2%
   15     108.5     0.566    0.5%
   16     110.5     0.193    0.1%
   17     113.8     0.871    0.7%
   18     115.3      0.25    0.2%
   19     117.7     0.365    0.3%
   20     119.9     0.336    0.2%
   21     122.7     0.358    0.2%
   22       125     0.385    0.3%
   23       129     0.275    0.2%
   24       130     0.428    0.3%
   25     132.4     0.251    0.1%
   26     135.8     0.646    0.4%
   27     137.9     0.436    0.3%
   28     139.7     0.481    0.3%
   29     142.7     0.432    0.3%
   30     145.5      0.72    0.4%
   31     147.4     0.364    0.2%
   32     149.8     0.345    0.2%
   33     151.9     0.394    0.2%
   34     153.5     0.234    0.1%
   35     156.7     0.401    0.2%
   36     158.8     0.258    0.1%
   37     160.7     0.481    0.2%
   38     163.2     0.587    0.3%
   39     166.6     0.632    0.3%
   40     168.8     0.347    0.2%
   41     171.3     0.267    0.1%
   42     174.9     1.239    0.7%
   43     178.3      0.91    0.5%
   44     179.5     1.021    0.5%
   45     182.9     2.028    1.1%
   46     182.6     0.562    0.3%
   47     184.4     0.588    0.3%
   48     187.3     0.782    0.4%
   49     189.2     0.623    0.3%
   50     191.9     0.645    0.3%
   51     194.9     1.796    0.9%
   52     196.5     0.892    0.4%
   53     199.3     0.712    0.3%
   54     201.6     0.672    0.3%
   55     206.7     2.385    1.1%
   56       207     0.923    0.4%
   57     211.9     4.592    2.1%
   58     210.8     0.948    0.4%
   59     215.1     1.111    0.5%
   60     215.7     0.712    0.3%
   61     219.1     0.626    0.2%
   62     221.3     0.731    0.3%
   63     223.4     1.035    0.4%
   64     225.1     1.325    0.5%
   65     228.1     0.713    0.3%
   66     231.8      0.64    0.2%
   67     239.9     2.474    1.0%
   68       241     1.062    0.4%
   69     243.1     0.791    0.3%
   70     240.4     0.748    0.3%
   71     242.4     0.718    0.2%
   72     243.5     0.964    0.3%
   73     248.2     0.878    0.3%
   74     251.9     1.698    0.6%
   75     252.4     0.663    0.2%
   76     256.4     2.242    0.8%
   77     257.4      0.65    0.2%
   78     259.7     0.469    0.1%
   79     262.6     1.122    0.4%
   80     264.7     0.578    0.2%
   81     266.5     1.092    0.4%
   82     269.1     0.735    0.2%
   83     271.7     0.657    0.2%
   84     271.2     0.763    0.2%
   85     274.6     1.292    0.4%
   86     277.9     0.604    0.2%
   87     289.2     11.68    4.0%
   88     287.1      8.41    2.9%
   89     285.7      1.11    0.3%
   90       288     1.447    0.5%
   91     291.8     1.159    0.3%
   92     294.8     0.904    0.3%
   93     297.2     0.613    0.2%
   94       300     2.491    0.8%
   95     299.8     0.814    0.2%
   96     301.8     1.774    0.5%
   97     306.4     3.714    1.2%
   98     308.5     1.355    0.4%
   99     310.5     1.606    0.5%
  100     312.3     1.193    0.3%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    72.27
    + s    2.412
              µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    290.3
    + n    48.08
              µs

Reads = 10 + (3 * v) + (3 * n)
Writes = 4 + (3 * v) + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
    1   100      2706     7.623    0.2%
    2   100      3017     17.71    0.5%
    3   100      3230     16.19    0.5%
    4   100      3424     16.99    0.4%
    5   100      3730     11.11    0.2%
    6   100      4024     19.45    0.4%
    7   100      4311     6.772    0.1%
    8   100      4625     26.84    0.5%
    9   100      5004     17.84    0.3%
   10     1     606.6     11.52    1.8%
   10     2     656.5     9.719    1.4%
   10     3     707.2     15.06    2.1%
   10     4     742.5     6.494    0.8%
   10     5     811.7     11.87    1.4%
   10     6     838.9     7.236    0.8%
   10     7     898.6     11.34    1.2%
   10     8     935.8     6.944    0.7%
   10     9     992.6     9.365    0.9%
   10    10      1056     16.28    1.5%
   10    11      1091     12.43    1.1%
   10    12      1129     13.71    1.2%
   10    13      1192     13.76    1.1%
   10    14      1247     11.09    0.8%
   10    15      1286     13.47    1.0%
   10    16      1344     13.31    0.9%
   10    17      1377     10.68    0.7%
   10    18      1426     13.43    0.9%
   10    19      1473     13.15    0.8%
   10    20      1539     9.348    0.6%
   10    21      1546      11.5    0.7%
   10    22      1602     15.74    0.9%
   10    23      1659     20.16    1.2%
   10    24      1700     2.562    0.1%
   10    25      1765     15.09    0.8%
   10    26      1813     14.24    0.7%
   10    27      1863     18.22    0.9%
   10    28      1917     12.82    0.6%
   10    29      1988     14.99    0.7%
   10    30      2025     14.89    0.7%
   10    31      2031     11.11    0.5%
   10    32      2126     17.76    0.8%
   10    33      2165     12.06    0.5%
   10    34      2201     9.731    0.4%
   10    35      2265     18.58    0.8%
   10    36      2309     13.72    0.5%
   10    37      2346      12.6    0.5%
   10    38      2416     10.63    0.4%
   10    39      2450     15.81    0.6%
   10    40      2515     13.26    0.5%
   10    41      2598     13.63    0.5%
   10    42      2624     8.613    0.3%
   10    43      2653     9.944    0.3%
   10    44      2737     6.472    0.2%
   10    45      2771     10.49    0.3%
   10    46      2785      7.36    0.2%
   10    47      2842     15.15    0.5%
   10    48      2909     19.29    0.6%
   10    49      2924     10.96    0.3%
   10    50      3024     11.28    0.3%
   10    51      3034     25.19    0.8%
   10    52      3100     18.61    0.6%
   10    53      3170      11.2    0.3%
   10    54      3208      7.84    0.2%
   10    55      3257     20.33    0.6%
   10    56      3296     12.22    0.3%
   10    57      3342     10.79    0.3%
   10    58      3418     18.28    0.5%
   10    59      3404     14.11    0.4%
   10    60      3516     9.373    0.2%
   10    61      3541     24.12    0.6%
   10    62      3592     13.04    0.3%
   10    63      3641     11.51    0.3%
   10    64      3687     13.58    0.3%
   10    65      3731     21.39    0.5%
   10    66      3759     16.73    0.4%
   10    67      3818     10.94    0.2%
   10    68      3855     10.34    0.2%
   10    69      3890     11.87    0.3%
   10    70      3948     15.27    0.3%
   10    71      3979     13.91    0.3%
   10    72      4070     18.39    0.4%
   10    73      4141      18.9    0.4%
   10    74      4114     11.87    0.2%
   10    75      4193      16.3    0.3%
   10    76      4235     13.72    0.3%
   10    77      4287     13.52    0.3%
   10    78      4328     12.42    0.2%
   10    79      4369     18.72    0.4%
   10    80      4420     12.22    0.2%
   10    81      4459     13.68    0.3%
   10    82      4544     11.59    0.2%
   10    83      4592     17.06    0.3%
   10    84      4586      10.9    0.2%
   10    85      4655      12.5    0.2%
   10    86      4653     17.23    0.3%
   10    87      4729     18.37    0.3%
   10    88      4736     15.51    0.3%
   10    89      4808     6.437    0.1%
   10    90      4872     7.919    0.1%
   10    91      4883      14.2    0.2%
   10    92      5038     15.72    0.3%
   10    93      5055      19.5    0.3%
   10    94      5003     9.084    0.1%
   10    95      5162     27.74    0.5%
   10    96      5152     15.27    0.2%
   10    97      5223     16.39    0.3%
   10    98      5246      11.4    0.2%
   10    99      5269     12.51    0.2%
   10   100      5299     12.22    0.2%

Quality and confidence:
param     error
v         0.923
n         0.046

Model:
Time ~=        0
    + v    307.9
    + n    47.78
              µs

Reads = 10 + (3 * v) + (3 * n)
Writes = 4 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v     26.5
    + n     28.3
    + s    47.42
              µs

Reads = 4 + (3 * v) + (3 * n) + (1 * s)
Writes = 1 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n     s   mean µs  sigma µs       %
  500  1000    20     40210     221.3    0.5%
  510  1000    20     40490     144.5    0.3%
  520  1000    20     40580     131.5    0.3%
  530  1000    20     41520     207.3    0.4%
  540  1000    20     41050     109.8    0.2%
  550  1000    20     40890     101.9    0.2%
  560  1000    20     41330     138.6    0.3%
  570  1000    20     42520     192.6    0.4%
  580  1000    20     42240     146.7    0.3%
  590  1000    20     42140     68.55    0.1%
  600  1000    20     43320     160.4    0.3%
  610  1000    20     42760     83.47    0.1%
  620  1000    20     43710     189.2    0.4%
  630  1000    20     43170     118.4    0.2%
  640  1000    20     44190     154.2    0.3%
  650  1000    20     44270     95.42    0.2%
  660  1000    20     44500     149.4    0.3%
  670  1000    20     45250       222    0.4%
  680  1000    20     44840     216.3    0.4%
  690  1000    20     44880     255.6    0.5%
  700  1000    20     45430       213    0.4%
  710  1000    20     46240     174.2    0.3%
  720  1000    20     46310     186.2    0.4%
  730  1000    20     46280     86.06    0.1%
  740  1000    20     45820     204.7    0.4%
  750  1000    20     46460     256.7    0.5%
  760  1000    20     47460       223    0.4%
  770  1000    20     47330     173.9    0.3%
  780  1000    20     46900     193.1    0.4%
  790  1000    20     48400     107.3    0.2%
  800  1000    20     47630     265.4    0.5%
  810  1000    20     47930     147.6    0.3%
  820  1000    20     48090     191.7    0.3%
  830  1000    20     48990     196.5    0.4%
  840  1000    20     48690     189.5    0.3%
  850  1000    20     49820     231.9    0.4%
  860  1000    20     50210     155.6    0.3%
  870  1000    20     49200     109.7    0.2%
  880  1000    20     49850     159.2    0.3%
  890  1000    20     50210     179.5    0.3%
  900  1000    20     50420     304.3    0.6%
  910  1000    20     50960     223.8    0.4%
  920  1000    20     50740     207.6    0.4%
  930  1000    20     51340     204.2    0.3%
  940  1000    20     51520     209.7    0.4%
  950  1000    20     52590     213.1    0.4%
  960  1000    20     52460     177.3    0.3%
  970  1000    20     52440     351.9    0.6%
  980  1000    20     52810       305    0.5%
  990  1000    20     53600     273.7    0.5%
 1000   500    20     39010     140.6    0.3%
 1000   510    20     39980     131.7    0.3%
 1000   520    20     39060     189.9    0.4%
 1000   530    20     40110       181    0.4%
 1000   540    20     40720     97.95    0.2%
 1000   550    20     40340     264.6    0.6%
 1000   560    20     41530     86.52    0.2%
 1000   570    20     40570     186.2    0.4%
 1000   580    20     41660     181.3    0.4%
 1000   590    20     41200     128.1    0.3%
 1000   600    20     41540     136.9    0.3%
 1000   610    20     42140     234.8    0.5%
 1000   620    20     42420     175.7    0.4%
 1000   630    20     42460     273.7    0.6%
 1000   640    20     42800     137.7    0.3%
 1000   650    20     43880     115.3    0.2%
 1000   660    20     43640     141.7    0.3%
 1000   670    20     44220     216.9    0.4%
 1000   680    20     43650       144    0.3%
 1000   690    20     44450     102.7    0.2%
 1000   700    20     45160     230.7    0.5%
 1000   710    20     45620     89.99    0.1%
 1000   720    20     44990     196.5    0.4%
 1000   730    20     44670     191.1    0.4%
 1000   740    20     45770     267.8    0.5%
 1000   750    20     45860     169.2    0.3%
 1000   760    20     46710     223.2    0.4%
 1000   770    20     46820     134.4    0.2%
 1000   780    20     46400     282.9    0.6%
 1000   790    20     47510       115    0.2%
 1000   800    20     47360     234.8    0.4%
 1000   810    20     47500     344.7    0.7%
 1000   820    20     48600       265    0.5%
 1000   830    20     48110     206.4    0.4%
 1000   840    20     48200       116    0.2%
 1000   850    20     48810     242.9    0.4%
 1000   860    20     48580     221.7    0.4%
 1000   870    20     49220     225.6    0.4%
 1000   880    20     49810     169.8    0.3%
 1000   890    20     49630     200.9    0.4%
 1000   900    20     49900       334    0.6%
 1000   910    20     50660     178.7    0.3%
 1000   920    20     51420     214.1    0.4%
 1000   930    20     51060     264.3    0.5%
 1000   940    20     51380     270.9    0.5%
 1000   950    20     52550     132.2    0.2%
 1000   960    20     52070     122.2    0.2%
 1000   970    20     51860     184.1    0.3%
 1000   980    20     52110     182.8    0.3%
 1000   990    20     53060     309.9    0.5%
 1000  1000     1     52760     159.5    0.3%
 1000  1000     2     52410     206.3    0.3%
 1000  1000     3     52650     156.2    0.2%
 1000  1000     4     52660     284.6    0.5%
 1000  1000     5     53190     182.8    0.3%
 1000  1000     6     52330     210.8    0.4%
 1000  1000     7     52630     226.6    0.4%
 1000  1000     8     52730     159.8    0.3%
 1000  1000     9     53320     225.8    0.4%
 1000  1000    10     53020     222.1    0.4%
 1000  1000    11     52790     242.2    0.4%
 1000  1000    12     52410     159.4    0.3%
 1000  1000    13     53260     155.2    0.2%
 1000  1000    14     52510     79.36    0.1%
 1000  1000    15     52770     291.1    0.5%
 1000  1000    16     53540     255.7    0.4%
 1000  1000    17     52790     193.7    0.3%
 1000  1000    18     52810     210.1    0.3%
 1000  1000    19     53100     183.1    0.3%
 1000  1000    20     53760       270    0.5%

Quality and confidence:
param     error
v         0.099
n         0.099
s         3.384

Model:
Time ~=        0
    + v    25.93
    + n    28.29
    + s    32.98
              µs

Reads = 4 + (3 * v) + (3 * n) + (1 * s)
Writes = 1 + (0 * v) + (0 * n) + (0 * s)
Pallet: "pallet_staking", Extrinsic: "get_npos_targets", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    11.23
              µs

Reads = 2 + (1 * v)
Writes = 1 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
  500      5531     42.29    0.7%
  510      5557     25.16    0.4%
  520      5794     25.46    0.4%
  530      5958     38.72    0.6%
  540      6089     24.79    0.4%
  550      6153      46.6    0.7%
  560      6299     30.49    0.4%
  570      6425     21.49    0.3%
  580      6526      24.6    0.3%
  590      6538     28.64    0.4%
  600      6733     22.34    0.3%
  610      6855     50.09    0.7%
  620      6944     42.55    0.6%
  630      6959     49.04    0.7%
  640      7334     62.32    0.8%
  650      7311     27.84    0.3%
  660      7434     44.05    0.5%
  670      7423     27.63    0.3%
  680      7635     45.56    0.5%
  690      7688      58.1    0.7%
  700      7890     59.87    0.7%
  710      7904      49.1    0.6%
  720      7962     21.85    0.2%
  730      8300     57.48    0.6%
  740      8198     47.99    0.5%
  750      8383     28.86    0.3%
  760      8470     32.72    0.3%
  770      8717     47.64    0.5%
  780      8671     54.96    0.6%
  790      8830     61.61    0.6%
  800      8828     38.43    0.4%
  810      9000     46.96    0.5%
  820      9329     52.01    0.5%
  830      9318     48.49    0.5%
  840      9340     34.78    0.3%
  850      9368     74.44    0.7%
  860      9572     51.65    0.5%
  870      9940     70.85    0.7%
  880      9784     44.89    0.4%
  890      9977     63.63    0.6%
  900     10220     84.88    0.8%
  910     10160     91.07    0.8%
  920     10210     62.28    0.6%
  930     10620       126    1.1%
  940     10580     50.69    0.4%
  950     10630     79.39    0.7%
  960     10690     19.48    0.1%
  970     10770     58.73    0.5%
  980     10830     51.45    0.4%
  990     11120     42.24    0.3%
 1000     11390     72.57    0.6%

Quality and confidence:
param     error
v         0.031

Model:
Time ~=        0
    + v    11.25
              µs

Reads = 2 + (1 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "set_staking_limits", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    6.401
              µs

Reads = 0
Writes = 5
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    6.401
              µs

Reads = 0
Writes = 5
Pallet: "pallet_staking", Extrinsic: "chill_other", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    57.71
              µs

Reads = 7
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    57.71
              µs

Reads = 7
Writes = 2

kianenigma · 2021-08-17T08:34:22Z

/benchmark runtime pallet pallet_election_provider_multi_phase

parity-benchapp · 2021-08-17T08:34:23Z

Benchmark Runtime Pallet for branch "kiz-remove-election-weight-api" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/election-provider-multi-phase/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_nothing", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     23.8
              µs

Reads = 8
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     23.8
              µs

Reads = 8
Writes = 0
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_signed", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    30.42
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    30.42
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    29.57
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    29.57
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_accept_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    49.24
              µs

Reads = 1
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    49.24
              µs

Reads = 1
Writes = 2
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_reject_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    32.48
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    32.48
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "create_snapshot_internal", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    12320
              µs

Reads = 0
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    12320
              µs

Reads = 0
Writes = 3
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "elect_queued", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    1.418
    + a    1.859
    + d    0.541
              µs

Reads = 7 + (0 * a) + (0 * d)
Writes = 9 + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    a     d   mean µs  sigma µs       %
 1000   800      2325      17.7    0.7%
 1060   800      2453     15.38    0.6%
 1120   800      2546     13.26    0.5%
 1180   800      2652     21.77    0.8%
 1240   800      2756     12.22    0.4%
 1300   800      2863     15.63    0.5%
 1360   800      2952     15.76    0.5%
 1420   800      3072      15.2    0.4%
 1480   800      3156     13.53    0.4%
 1540   800      3265     13.25    0.4%
 1600   800      3425      21.5    0.6%
 1660   800      3536     11.34    0.3%
 1720   800      3640     15.45    0.4%
 1780   800      3729     12.65    0.3%
 1840   800      3815     19.87    0.5%
 1900   800      3934     14.14    0.3%
 1960   800      4056     10.97    0.2%
 2020   800      4169     11.73    0.2%
 2080   800      4331      24.2    0.5%
 2140   800      4400     15.05    0.3%
 2200   800      4540     11.95    0.2%
 2260   800      4641     6.448    0.1%
 2320   800      4755      17.7    0.3%
 2380   800      4855     12.71    0.2%
 2440   800      4975     22.76    0.4%
 2500   800      5089      22.9    0.4%
 2560   800      5174     10.81    0.2%
 2620   800      5349     36.83    0.6%
 2680   800      5428     11.88    0.2%
 2740   800      5544     24.78    0.4%
 2800   800      5635     9.371    0.1%
 2860   800      5724     17.37    0.3%
 2920   800      5873     30.81    0.5%
 2980   800      5947     15.74    0.2%
 3040   800      6065     17.31    0.2%
 3100   800      6175     19.28    0.3%
 3160   800      6252     14.79    0.2%
 3220   800      6385     19.86    0.3%
 3280   800      6509     25.49    0.3%
 3340   800      6616     14.38    0.2%
 3400   800      6725     21.61    0.3%
 3460   800      6886     18.12    0.2%
 3520   800      7014     20.97    0.2%
 3580   800      7102      40.1    0.5%
 3640   800      7231     25.32    0.3%
 3700   800      7338     19.55    0.2%
 3760   800      7437     13.69    0.1%
 3820   800      7575      22.7    0.2%
 3880   800      7676     9.175    0.1%
 3940   800      7778     23.47    0.3%
 4000   400      7762     27.55    0.3%
 4000   408      7732     8.893    0.1%
 4000   416      7746     14.27    0.1%
 4000   424      7772     26.69    0.3%
 4000   432      7779     22.27    0.2%
 4000   440      7758     13.75    0.1%
 4000   448      7759     29.02    0.3%
 4000   456      7772     18.96    0.2%
 4000   464      7779     15.25    0.1%
 4000   472      7771     26.29    0.3%
 4000   480      7785     25.68    0.3%
 4000   488      7786     19.66    0.2%
 4000   496      7770     21.21    0.2%
 4000   504      7795     30.61    0.3%
 4000   512      7834      15.1    0.1%
 4000   520      7820     25.93    0.3%
 4000   528      7824     24.64    0.3%
 4000   536      7819     20.54    0.2%
 4000   544      7817     22.16    0.2%
 4000   552      7833     28.58    0.3%
 4000   560      7844     22.17    0.2%
 4000   568      7840     21.97    0.2%
 4000   576      7830     23.41    0.2%
 4000   584      7837     19.27    0.2%
 4000   592      7856     15.09    0.1%
 4000   600      7872     24.99    0.3%
 4000   608      7870     18.65    0.2%
 4000   616      7886     29.31    0.3%
 4000   624      7856     20.36    0.2%
 4000   632      7870     23.43    0.2%
 4000   640      7883     15.31    0.1%
 4000   648      7927     16.47    0.2%
 4000   656      7900     27.15    0.3%
 4000   664      7893     9.759    0.1%
 4000   672      7878     28.42    0.3%
 4000   680      7907     29.29    0.3%
 4000   688      7883     16.63    0.2%
 4000   696      7910     20.59    0.2%
 4000   704      7915     13.41    0.1%
 4000   712      7936     25.73    0.3%
 4000   720      7910      16.1    0.2%
 4000   728      7937     14.62    0.1%
 4000   736      7951     25.25    0.3%
 4000   744      7911     17.11    0.2%
 4000   752      7916     29.89    0.3%
 4000   760      7961      12.6    0.1%
 4000   768      7963     23.04    0.2%
 4000   776      7967     23.79    0.2%
 4000   784      7947      28.5    0.3%
 4000   792      7953     13.77    0.1%
 4000   800      7920     20.47    0.2%

Quality and confidence:
param     error
a         0.001
d         0.011

Model:
Time ~=    84.71
    + a    1.883
    + d     0.38
              µs

Reads = 7 + (0 * a) + (0 * d)
Writes = 9 + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    75.36
    + c    0.358
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    c   mean µs  sigma µs       %
    1     75.47     0.145    0.1%
    2     76.15     0.176    0.2%
    3     76.67     0.246    0.3%
    4     76.74     0.361    0.4%
    5     77.15     0.206    0.2%
    6     77.41     0.384    0.4%
    7     78.07     0.205    0.2%
    8     78.46     0.203    0.2%
    9     78.28     0.212    0.2%

Quality and confidence:
param     error
c         0.012

Model:
Time ~=    75.35
    + c    0.361
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    3.632
    + t        0
    + a     11.1
    + d    5.094
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     60820     84.92    0.1%
 5100  2000  4000   800     61160     65.79    0.1%
 5200  2000  4000   800     61530     50.11    0.0%
 5300  2000  4000   800     61880     56.65    0.0%
 5400  2000  4000   800     62190     48.33    0.0%
 5500  2000  4000   800     62550     48.89    0.0%
 5600  2000  4000   800     62970     62.17    0.0%
 5700  2000  4000   800     63260     129.6    0.2%
 5800  2000  4000   800     63600      45.9    0.0%
 5900  2000  4000   800     63980      54.8    0.0%
 6000  2000  4000   800     64290     55.19    0.0%
 6100  2000  4000   800     64680     67.22    0.1%
 6200  2000  4000   800     65060     49.45    0.0%
 6300  2000  4000   800     65410     48.77    0.0%
 6400  2000  4000   800     65790      31.4    0.0%
 6500  2000  4000   800     66170     41.82    0.0%
 6600  2000  4000   800     66590     99.32    0.1%
 6700  2000  4000   800     67030     69.53    0.1%
 6800  2000  4000   800     67270     65.11    0.0%
 6900  2000  4000   800     67630     57.37    0.0%
 7000  2000  4000   800     67930     75.35    0.1%
 7100  2000  4000   800     68350     77.68    0.1%
 7200  2000  4000   800     68680     75.47    0.1%
 7300  2000  4000   800     69010     68.68    0.0%
 7400  2000  4000   800     69490     95.27    0.1%
 7500  2000  4000   800     69840     61.54    0.0%
 7600  2000  4000   800     70130     54.55    0.0%
 7700  2000  4000   800     70520     98.73    0.1%
 7800  2000  4000   800     70840     47.95    0.0%
 7900  2000  4000   800     71250      80.5    0.1%
 8000  2000  4000   800     71620     66.19    0.0%
 8100  2000  4000   800     71940     82.22    0.1%
 8200  2000  4000   800     72340     79.24    0.1%
 8300  2000  4000   800     72670     61.28    0.0%
 8400  2000  4000   800     72950     54.04    0.0%
 8500  2000  4000   800     73390     43.35    0.0%
 8600  2000  4000   800     73750     50.98    0.0%
 8700  2000  4000   800     74020     63.06    0.0%
 8800  2000  4000   800     74500     60.49    0.0%
 8900  2000  4000   800     74820     63.23    0.0%
 9000  2000  4000   800     75210     66.02    0.0%
 9100  2000  4000   800     75670     38.82    0.0%
 9200  2000  4000   800     76130     75.27    0.0%
 9300  2000  4000   800     76450     55.57    0.0%
 9400  2000  4000   800     76740     53.92    0.0%
 9500  2000  4000   800     77110     94.04    0.1%
 9600  2000  4000   800     77400     69.11    0.0%
 9700  2000  4000   800     77850     52.84    0.0%
 9800  2000  4000   800     78180     43.75    0.0%
 9900  2000  4000   800     78640     91.21    0.1%
10000  1000  4000   800     79090     39.38    0.0%
10000  1020  4000   800     78990      76.1    0.0%
10000  1040  4000   800     79010     77.24    0.0%
10000  1060  4000   800     78990     27.09    0.0%
10000  1080  4000   800     78880     66.61    0.0%
10000  1100  4000   800     79010     32.19    0.0%
10000  1120  4000   800     78910     36.57    0.0%
10000  1140  4000   800     78890     23.31    0.0%
10000  1160  4000   800     78910     42.29    0.0%
10000  1180  4000   800     78870     50.61    0.0%
10000  1200  4000   800     79020     91.19    0.1%
10000  1220  4000   800     78970     37.54    0.0%
10000  1240  4000   800     78880     63.55    0.0%
10000  1260  4000   800     78950     54.89    0.0%
10000  1280  4000   800     79040     38.36    0.0%
10000  1300  4000   800     78970     70.39    0.0%
10000  1320  4000   800     78980     48.81    0.0%
10000  1340  4000   800     78930     43.81    0.0%
10000  1360  4000   800     79570     90.45    0.1%
10000  1380  4000   800     78990     47.16    0.0%
10000  1400  4000   800     79130     44.48    0.0%
10000  1420  4000   800     79100     48.61    0.0%
10000  1440  4000   800     78960     71.16    0.0%
10000  1460  4000   800     79180     88.26    0.1%
10000  1480  4000   800     79100      78.2    0.0%
10000  1500  4000   800     79060     52.28    0.0%
10000  1520  4000   800     78980     64.72    0.0%
10000  1540  4000   800     78910     72.49    0.0%
10000  1560  4000   800     78890     94.35    0.1%
10000  1580  4000   800     79020     64.74    0.0%
10000  1600  4000   800     79000     36.58    0.0%
10000  1620  4000   800     79080     38.48    0.0%
10000  1640  4000   800     78790      30.9    0.0%
10000  1660  4000   800     78950     57.92    0.0%
10000  1680  4000   800     78880     37.83    0.0%
10000  1700  4000   800     78910     51.21    0.0%
10000  1720  4000   800     78870     46.65    0.0%
10000  1740  4000   800     78820      45.6    0.0%
10000  1760  4000   800     78930     60.64    0.0%
10000  1780  4000   800     78840      36.8    0.0%
10000  1800  4000   800     79070     56.55    0.0%
10000  1820  4000   800     78890     70.28    0.0%
10000  1840  4000   800     79010     48.34    0.0%
10000  1860  4000   800     78920     45.46    0.0%
10000  1880  4000   800     79050     43.61    0.0%
10000  1900  4000   800     79000     62.38    0.0%
10000  1920  4000   800     78890     52.24    0.0%
10000  1940  4000   800     79040      84.2    0.1%
10000  1960  4000   800     78990     99.47    0.1%
10000  1980  4000   800     79150     71.19    0.0%
10000  2000  1000   800     45760     55.28    0.1%
10000  2000  1060   800     46350     46.56    0.1%
10000  2000  1120   800     47000     59.28    0.1%
10000  2000  1180   800     47580     30.54    0.0%
10000  2000  1240   800     48270      37.4    0.0%
10000  2000  1300   800     48800     41.26    0.0%
10000  2000  1360   800     49510     39.09    0.0%
10000  2000  1420   800     50600     31.74    0.0%
10000  2000  1480   800     51310     36.06    0.0%
10000  2000  1540   800     51910     44.15    0.0%
10000  2000  1600   800     52670     21.11    0.0%
10000  2000  1660   800     53360     28.21    0.0%
10000  2000  1720   800     53990     27.46    0.0%
10000  2000  1780   800     54640      29.4    0.0%
10000  2000  1840   800     55180     29.66    0.0%
10000  2000  1900   800     55980     44.48    0.0%
10000  2000  1960   800     56410     39.53    0.0%
10000  2000  2020   800     57150     49.11    0.0%
10000  2000  2080   800     57780     58.19    0.1%
10000  2000  2140   800     58390     45.91    0.0%
10000  2000  2200   800     58990     63.53    0.1%
10000  2000  2260   800     59590     56.72    0.0%
10000  2000  2320   800     60060     27.67    0.0%
10000  2000  2380   800     60710     49.16    0.0%
10000  2000  2440   800     61340     40.16    0.0%
10000  2000  2500   800     61940     57.32    0.0%
10000  2000  2560   800     62390     55.17    0.0%
10000  2000  2620   800     63030      18.1    0.0%
10000  2000  2680   800     63720     51.08    0.0%
10000  2000  2740   800     64330     52.85    0.0%
10000  2000  2800   800     64970     60.59    0.0%
10000  2000  2860   800     66640     49.08    0.0%
10000  2000  2920   800     67250      74.5    0.1%
10000  2000  2980   800     67930     51.57    0.0%
10000  2000  3040   800     68570     59.69    0.0%
10000  2000  3100   800     69260     57.26    0.0%
10000  2000  3160   800     69920     68.27    0.0%
10000  2000  3220   800     70610     36.68    0.0%
10000  2000  3280   800     71450     102.7    0.1%
10000  2000  3340   800     72000     56.23    0.0%
10000  2000  3400   800     72550     64.91    0.0%
10000  2000  3460   800     73250     59.67    0.0%
10000  2000  3520   800     73940     19.97    0.0%
10000  2000  3580   800     74630     34.56    0.0%
10000  2000  3640   800     75220     41.38    0.0%
10000  2000  3700   800     75890     36.67    0.0%
10000  2000  3760   800     76540     40.52    0.0%
10000  2000  3820   800     77100     58.29    0.0%
10000  2000  3880   800     77710     26.56    0.0%
10000  2000  3940   800     78370     95.69    0.1%
10000  2000  4000   400     76820     46.92    0.0%
10000  2000  4000   408     76950     32.28    0.0%
10000  2000  4000   416     77010     80.33    0.1%
10000  2000  4000   424     77230     47.52    0.0%
10000  2000  4000   432     77270     47.32    0.0%
10000  2000  4000   440     77250      63.5    0.0%
10000  2000  4000   448     77340     58.78    0.0%
10000  2000  4000   456     77300     75.97    0.0%
10000  2000  4000   464     77380     82.66    0.1%
10000  2000  4000   472     77300     45.95    0.0%
10000  2000  4000   480     77400     39.68    0.0%
10000  2000  4000   488     77200     67.44    0.0%
10000  2000  4000   496     77370     48.41    0.0%
10000  2000  4000   504     77270     42.71    0.0%
10000  2000  4000   512     77160     62.51    0.0%
10000  2000  4000   520     77210     42.76    0.0%
10000  2000  4000   528     77100     67.88    0.0%
10000  2000  4000   536     77070     73.34    0.0%
10000  2000  4000   544     77120     31.56    0.0%
10000  2000  4000   552     77220     99.42    0.1%
10000  2000  4000   560     77130     47.91    0.0%
10000  2000  4000   568     77210     52.28    0.0%
10000  2000  4000   576     77240     53.79    0.0%
10000  2000  4000   584     77290     34.67    0.0%
10000  2000  4000   592     77230     56.22    0.0%
10000  2000  4000   600     77270     57.86    0.0%
10000  2000  4000   608     77310     66.72    0.0%
10000  2000  4000   616     77570     33.16    0.0%
10000  2000  4000   624     77470     72.23    0.0%
10000  2000  4000   632     77730     58.27    0.0%
10000  2000  4000   640     77610     63.32    0.0%
10000  2000  4000   648     77720     51.87    0.0%
10000  2000  4000   656     77760     61.18    0.0%
10000  2000  4000   664     77930     64.18    0.0%
10000  2000  4000   672     77970     72.61    0.0%
10000  2000  4000   680     77990     52.94    0.0%
10000  2000  4000   688     77930     47.02    0.0%
10000  2000  4000   696     78130     93.91    0.1%
10000  2000  4000   704     78230     61.75    0.0%
10000  2000  4000   712     78250     53.36    0.0%
10000  2000  4000   720     78470      91.3    0.1%
10000  2000  4000   728     78420     43.39    0.0%
10000  2000  4000   736     78500     37.81    0.0%
10000  2000  4000   744     78540     49.15    0.0%
10000  2000  4000   752     79070     58.24    0.0%
10000  2000  4000   760     78680     71.46    0.0%
10000  2000  4000   768     78690     64.87    0.0%
10000  2000  4000   776     78790     61.77    0.0%
10000  2000  4000   784     78830     81.73    0.1%
10000  2000  4000   792     78870     60.41    0.0%
10000  2000  4000   800     78930     57.22    0.0%

Quality and confidence:
param     error
v         0.004
t         0.023
a         0.007
d         0.058

Model:
Time ~=        0
    + v    3.635
    + t        0
    + a    11.04
    + d    5.688
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "feasibility_check", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v     3.61
    + t        0
    + a    9.421
    + d    4.189
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     54010     47.03    0.0%
 5100  2000  4000   800     54430     74.92    0.1%
 5200  2000  4000   800     54740     32.57    0.0%
 5300  2000  4000   800     55150     59.99    0.1%
 5400  2000  4000   800     55430     45.25    0.0%
 5500  2000  4000   800     55850     42.52    0.0%
 5600  2000  4000   800     56120     33.16    0.0%
 5700  2000  4000   800     56440     64.63    0.1%
 5800  2000  4000   800     56840     78.63    0.1%
 5900  2000  4000   800     57180     40.31    0.0%
 6000  2000  4000   800     57510     34.04    0.0%
 6100  2000  4000   800     57910     20.77    0.0%
 6200  2000  4000   800     58290     58.97    0.1%
 6300  2000  4000   800     58640     41.23    0.0%
 6400  2000  4000   800     59030     71.32    0.1%
 6500  2000  4000   800     59360     54.11    0.0%
 6600  2000  4000   800     59790     63.27    0.1%
 6700  2000  4000   800     60150      62.2    0.1%
 6800  2000  4000   800     60460     38.78    0.0%
 6900  2000  4000   800     60820     51.69    0.0%
 7000  2000  4000   800     61210     61.88    0.1%
 7100  2000  4000   800     61570     35.54    0.0%
 7200  2000  4000   800     61920     53.99    0.0%
 7300  2000  4000   800     62330     48.43    0.0%
 7400  2000  4000   800     62720     73.56    0.1%
 7500  2000  4000   800     62970     65.11    0.1%
 7600  2000  4000   800     63350     52.05    0.0%
 7700  2000  4000   800     63740     51.13    0.0%
 7800  2000  4000   800     64080     46.86    0.0%
 7900  2000  4000   800     64530     66.72    0.1%
 8000  2000  4000   800     64870      68.9    0.1%
 8100  2000  4000   800     65150     50.91    0.0%
 8200  2000  4000   800     65450     46.02    0.0%
 8300  2000  4000   800     65860     77.57    0.1%
 8400  2000  4000   800     66280     61.86    0.0%
 8500  2000  4000   800     66580     72.41    0.1%
 8600  2000  4000   800     66930     44.01    0.0%
 8700  2000  4000   800     67330     55.34    0.0%
 8800  2000  4000   800     67710     50.58    0.0%
 8900  2000  4000   800     68050     65.58    0.0%
 9000  2000  4000   800     68350     53.63    0.0%
 9100  2000  4000   800     68960     55.07    0.0%
 9200  2000  4000   800     69250     46.21    0.0%
 9300  2000  4000   800     69630     48.78    0.0%
 9400  2000  4000   800     69940      33.8    0.0%
 9500  2000  4000   800     70230     47.79    0.0%
 9600  2000  4000   800     70600     78.12    0.1%
 9700  2000  4000   800     71060     56.46    0.0%
 9800  2000  4000   800     71420     36.88    0.0%
 9900  2000  4000   800     71730     64.46    0.0%
10000  1000  4000   800     72140     38.88    0.0%
10000  1020  4000   800     71980     70.37    0.0%
10000  1040  4000   800     72090     38.81    0.0%
10000  1060  4000   800     72020     63.15    0.0%
10000  1080  4000   800     72080      83.6    0.1%
10000  1100  4000   800     72090      32.1    0.0%
10000  1120  4000   800     72120     76.52    0.1%
10000  1140  4000   800     71970     47.37    0.0%
10000  1160  4000   800     72010     41.14    0.0%
10000  1180  4000   800     71990     62.11    0.0%
10000  1200  4000   800     72080     60.12    0.0%
10000  1220  4000   800     72100     68.14    0.0%
10000  1240  4000   800     72030     48.79    0.0%
10000  1260  4000   800     72070      62.1    0.0%
10000  1280  4000   800     72170     45.87    0.0%
10000  1300  4000   800     72090     28.86    0.0%
10000  1320  4000   800     72200      68.8    0.0%
10000  1340  4000   800     72000     65.64    0.0%
10000  1360  4000   800     72260     56.94    0.0%
10000  1380  4000   800     72370     87.77    0.1%
10000  1400  4000   800     72140     96.78    0.1%
10000  1420  4000   800     72240     46.51    0.0%
10000  1440  4000   800     72210     49.64    0.0%
10000  1460  4000   800     72260     34.59    0.0%
10000  1480  4000   800     72160     51.27    0.0%
10000  1500  4000   800     72080     64.66    0.0%
10000  1520  4000   800     72140     62.25    0.0%
10000  1540  4000   800     72060      83.1    0.1%
10000  1560  4000   800     72110     46.04    0.0%
10000  1580  4000   800     72210     72.54    0.1%
10000  1600  4000   800     72190     62.48    0.0%
10000  1620  4000   800     72200     59.38    0.0%
10000  1640  4000   800     71950     84.94    0.1%
10000  1660  4000   800     71990     60.96    0.0%
10000  1680  4000   800     71930     62.72    0.0%
10000  1700  4000   800     72020     28.98    0.0%
10000  1720  4000   800     72080     89.86    0.1%
10000  1740  4000   800     71990     36.02    0.0%
10000  1760  4000   800     72120     72.81    0.1%
10000  1780  4000   800     71950     91.54    0.1%
10000  1800  4000   800     72070     44.08    0.0%
10000  1820  4000   800     71920     46.34    0.0%
10000  1840  4000   800     71980     68.96    0.0%
10000  1860  4000   800     71910     42.77    0.0%
10000  1880  4000   800     71990     65.21    0.0%
10000  1900  4000   800     72120     52.42    0.0%
10000  1920  4000   800     72090     65.23    0.0%
10000  1940  4000   800     72030     111.3    0.1%
10000  1960  4000   800     71980     58.16    0.0%
10000  1980  4000   800     72130     74.23    0.1%
10000  2000  1000   800     43750     59.68    0.1%
10000  2000  1060   800     44290     96.34    0.2%
10000  2000  1120   800     44890     50.59    0.1%
10000  2000  1180   800     45270     59.37    0.1%
10000  2000  1240   800     45970     33.66    0.0%
10000  2000  1300   800     46510      64.3    0.1%
10000  2000  1360   800     47110     43.42    0.0%
10000  2000  1420   800     47630     49.75    0.1%
10000  2000  1480   800     48220     24.54    0.0%
10000  2000  1540   800     49090     425.9    0.8%
10000  2000  1600   800     49480     37.96    0.0%
10000  2000  1660   800     50100     62.24    0.1%
10000  2000  1720   800     50700     63.69    0.1%
10000  2000  1780   800     51200     87.45    0.1%
10000  2000  1840   800     51630     63.86    0.1%
10000  2000  1900   800     52310     28.03    0.0%
10000  2000  1960   800     52900     26.75    0.0%
10000  2000  2020   800     53510     59.28    0.1%
10000  2000  2080   800     54130     56.75    0.1%
10000  2000  2140   800     54510     53.07    0.0%
10000  2000  2200   800     55090     53.63    0.0%
10000  2000  2260   800     55660     62.72    0.1%
10000  2000  2320   800     56130     35.06    0.0%
10000  2000  2380   800     56680     61.61    0.1%
10000  2000  2440   800     57180     87.95    0.1%
10000  2000  2500   800     57680     31.71    0.0%
10000  2000  2560   800     58160     31.84    0.0%
10000  2000  2620   800     58730     43.48    0.0%
10000  2000  2680   800     59370     97.24    0.1%
10000  2000  2740   800     59910     53.23    0.0%
10000  2000  2800   800     60410     52.01    0.0%
10000  2000  2860   800     60980     36.56    0.0%
10000  2000  2920   800     61610     44.14    0.0%
10000  2000  2980   800     62150     57.86    0.0%
10000  2000  3040   800     62700     48.54    0.0%
10000  2000  3100   800     63360     53.18    0.0%
10000  2000  3160   800     64040     59.27    0.0%
10000  2000  3220   800     64670     77.12    0.1%
10000  2000  3280   800     65310     72.99    0.1%
10000  2000  3340   800     65840     27.23    0.0%
10000  2000  3400   800     66370     56.94    0.0%
10000  2000  3460   800     67010     48.61    0.0%
10000  2000  3520   800     67610     44.53    0.0%
10000  2000  3580   800     68180     87.31    0.1%
10000  2000  3640   800     68800     48.66    0.0%
10000  2000  3700   800     69350     26.02    0.0%
10000  2000  3760   800     69900     67.72    0.0%
10000  2000  3820   800     70330     69.59    0.0%
10000  2000  3880   800     70960     86.49    0.1%
10000  2000  3940   800     71510      40.6    0.0%
10000  2000  4000   400     70230     32.21    0.0%
10000  2000  4000   408     70250     44.53    0.0%
10000  2000  4000   416     70400     71.77    0.1%
10000  2000  4000   424     70630      65.5    0.0%
10000  2000  4000   432     70600     31.04    0.0%
10000  2000  4000   440     70670     57.88    0.0%
10000  2000  4000   448     70680     41.41    0.0%
10000  2000  4000   456     70670     57.08    0.0%
10000  2000  4000   464     70610     33.96    0.0%
10000  2000  4000   472     70650     33.69    0.0%
10000  2000  4000   480     70730     48.03    0.0%
10000  2000  4000   488     70640      66.2    0.0%
10000  2000  4000   496     70650     46.45    0.0%
10000  2000  4000   504     70670     76.56    0.1%
10000  2000  4000   512     70400     46.59    0.0%
10000  2000  4000   520     70430     61.77    0.0%
10000  2000  4000   528     70470     57.54    0.0%
10000  2000  4000   536     70420     56.18    0.0%
10000  2000  4000   544     70440     84.28    0.1%
10000  2000  4000   552     70460     74.14    0.1%
10000  2000  4000   560     70510     73.28    0.1%
10000  2000  4000   568     70440     71.59    0.1%
10000  2000  4000   576     70470     97.89    0.1%
10000  2000  4000   584     70440     64.58    0.0%
10000  2000  4000   592     70540     30.17    0.0%
10000  2000  4000   600     70620     52.58    0.0%
10000  2000  4000   608     70650      70.9    0.1%
10000  2000  4000   616     70760     42.58    0.0%
10000  2000  4000   624     70750     26.74    0.0%
10000  2000  4000   632     70780     58.52    0.0%
10000  2000  4000   640     70870     39.61    0.0%
10000  2000  4000   648     70920     66.15    0.0%
10000  2000  4000   656     71010     46.84    0.0%
10000  2000  4000   664     71020     29.93    0.0%
10000  2000  4000   672     71020     72.74    0.1%
10000  2000  4000   680     71160     26.76    0.0%
10000  2000  4000   688     71160      41.9    0.0%
10000  2000  4000   696     71270     72.58    0.1%
10000  2000  4000   704     71280     39.51    0.0%
10000  2000  4000   712     71410     74.77    0.1%
10000  2000  4000   720     71530     55.04    0.0%
10000  2000  4000   728     71440     30.26    0.0%
10000  2000  4000   736     71690     72.44    0.1%
10000  2000  4000   744     71660     78.48    0.1%
10000  2000  4000   752     71850     66.84    0.0%
10000  2000  4000   760     71780     113.1    0.1%
10000  2000  4000   768     71870     54.88    0.0%
10000  2000  4000   776     72000     53.29    0.0%
10000  2000  4000   784     71860     36.58    0.0%
10000  2000  4000   792     72080     81.59    0.1%
10000  2000  4000   800     71950     62.86    0.0%

Quality and confidence:
param     error
v         0.003
t         0.018
a         0.006
d         0.045

Model:
Time ~=        0
    + v    3.585
    + t        0
    + a    9.401
    + d    4.799
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

…ove-election-weight-api

kianenigma · 2021-08-17T11:33:28Z

/benchmark runtime pallet pallet_election_provider_multi_phase

parity-benchapp · 2021-08-17T11:33:30Z

Benchmark Runtime Pallet for branch "kiz-remove-election-weight-api" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/election-provider-multi-phase/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_nothing", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    23.58
              µs

Reads = 8
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    23.58
              µs

Reads = 8
Writes = 0
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_signed", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    30.78
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    30.78
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    29.87
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    29.87
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_accept_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    48.77
              µs

Reads = 1
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    48.77
              µs

Reads = 1
Writes = 2
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_reject_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    32.57
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    32.57
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "create_snapshot_internal", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     8863
              µs

Reads = 0
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     8863
              µs

Reads = 0
Writes = 3
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "elect_queued", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    59.46
    + a    1.819
    + d    0.527
              µs

Reads = 7 + (0 * a) + (0 * d)
Writes = 9 + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    a     d   mean µs  sigma µs       %
 1000   800      2308      13.3    0.5%
 1060   800      2417     10.35    0.4%
 1120   800      2527     17.67    0.6%
 1180   800      2629     9.791    0.3%
 1240   800      2719     11.54    0.4%
 1300   800      2870      16.3    0.5%
 1360   800      2966     17.54    0.5%
 1420   800      3054     15.03    0.4%
 1480   800      3189     21.88    0.6%
 1540   800      3268     18.22    0.5%
 1600   800      3370     16.54    0.4%
 1660   800      3486     17.13    0.4%
 1720   800      3584     6.668    0.1%
 1780   800      3684     18.23    0.4%
 1840   800      3799     7.931    0.2%
 1900   800      3908      11.9    0.3%
 1960   800      4037     19.56    0.4%
 2020   800      4142     22.73    0.5%
 2080   800      4242     17.01    0.4%
 2140   800      4338     10.85    0.2%
 2200   800      4498     19.03    0.4%
 2260   800      4591     9.789    0.2%
 2320   800      4714     12.43    0.2%
 2380   800      4810     19.23    0.3%
 2440   800      4930     15.17    0.3%
 2500   800      5049     16.81    0.3%
 2560   800      5136     13.44    0.2%
 2620   800      5259     13.34    0.2%
 2680   800      5362     7.282    0.1%
 2740   800      5468     8.038    0.1%
 2800   800      5595     6.897    0.1%
 2860   800      5746      22.9    0.3%
 2920   800      5829      10.1    0.1%
 2980   800      5942     12.86    0.2%
 3040   800      6039     18.57    0.3%
 3100   800      6156     26.92    0.4%
 3160   800      6258     15.86    0.2%
 3220   800      6348     7.654    0.1%
 3280   800      6509     19.32    0.2%
 3340   800      6627     16.89    0.2%
 3400   800      6661     13.37    0.2%
 3460   800      6741     10.76    0.1%
 3520   800      6860     12.56    0.1%
 3580   800      6962      9.22    0.1%
 3640   800      7082     26.83    0.3%
 3700   800      7164     11.85    0.1%
 3760   800      7290      22.2    0.3%
 3820   800      7410     19.41    0.2%
 3880   800      7515     18.05    0.2%
 3940   800      7627     18.87    0.2%
 4000   400      7586     18.44    0.2%
 4000   408      7587     18.82    0.2%
 4000   416      7611     21.76    0.2%
 4000   424      7576     16.63    0.2%
 4000   432      7609     25.26    0.3%
 4000   440      7611     22.36    0.2%
 4000   448      7623     29.07    0.3%
 4000   456      7607     20.72    0.2%
 4000   464      7617      14.5    0.1%
 4000   472      7603     15.88    0.2%
 4000   480      7621      13.6    0.1%
 4000   488      7629     20.32    0.2%
 4000   496      7621     15.59    0.2%
 4000   504      7645     9.441    0.1%
 4000   512      7618     28.17    0.3%
 4000   520      7644     6.349    0.0%
 4000   528      7654     18.14    0.2%
 4000   536      7649     18.46    0.2%
 4000   544      7653     18.66    0.2%
 4000   552      7660      19.3    0.2%
 4000   560      7675     12.24    0.1%
 4000   568      7703     37.82    0.4%
 4000   576      7676      13.4    0.1%
 4000   584      7705     12.07    0.1%
 4000   592      7702     23.75    0.3%
 4000   600      7703     29.61    0.3%
 4000   608      7716     24.66    0.3%
 4000   616      7722     22.32    0.2%
 4000   624      7707     25.99    0.3%
 4000   632      7695      24.5    0.3%
 4000   640      7701     21.59    0.2%
 4000   648      7723     26.01    0.3%
 4000   656      7730     13.42    0.1%
 4000   664      7719     20.61    0.2%
 4000   672      7700      16.6    0.2%
 4000   680      7753     14.22    0.1%
 4000   688      7702     25.09    0.3%
 4000   696      7741     14.21    0.1%
 4000   704      7760     20.87    0.2%
 4000   712      7754     10.28    0.1%
 4000   720      7766     14.14    0.1%
 4000   728      7760     11.64    0.1%
 4000   736      7770     12.65    0.1%
 4000   744      7781      15.5    0.1%
 4000   752      7784     34.41    0.4%
 4000   760      7787     36.35    0.4%
 4000   768      7780     15.34    0.1%
 4000   776      7776     13.62    0.1%
 4000   784      7808     19.96    0.2%
 4000   792      7787     17.31    0.2%
 4000   800      7755     15.84    0.2%

Quality and confidence:
param     error
a         0.001
d         0.008

Model:
Time ~=       92
    + a     1.83
    + d    0.461
              µs

Reads = 7 + (0 * a) + (0 * d)
Writes = 9 + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    76.92
    + c    0.373
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    c   mean µs  sigma µs       %
    1     76.99     0.193    0.2%
    2     77.62     0.192    0.2%
    3      78.4     0.234    0.2%
    4     78.23     0.227    0.2%
    5     79.17     0.219    0.2%
    6     79.11     0.183    0.2%
    7     79.63     0.129    0.1%
    8      80.1     0.193    0.2%
    9     79.98     0.146    0.1%

Quality and confidence:
param     error
c         0.012

Model:
Time ~=    76.91
    + c    0.379
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    3.647
    + t    0.222
    + a    11.18
    + d    5.092
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     60840     80.05    0.1%
 5100  2000  4000   800     61170     69.85    0.1%
 5200  2000  4000   800     61620     23.44    0.0%
 5300  2000  4000   800     61920     80.67    0.1%
 5400  2000  4000   800     62430        65    0.1%
 5500  2000  4000   800     62620     55.18    0.0%
 5600  2000  4000   800     63060     74.22    0.1%
 5700  2000  4000   800     63360     70.91    0.1%
 5800  2000  4000   800     63690     84.83    0.1%
 5900  2000  4000   800     64030     54.19    0.0%
 6000  2000  4000   800     64520     38.44    0.0%
 6100  2000  4000   800     65040     72.62    0.1%
 6200  2000  4000   800     65220     19.97    0.0%
 6300  2000  4000   800     65630     50.57    0.0%
 6400  2000  4000   800     65930     38.77    0.0%
 6500  2000  4000   800     66390     66.97    0.1%
 6600  2000  4000   800     66600     83.06    0.1%
 6700  2000  4000   800     66990     58.64    0.0%
 6800  2000  4000   800     67470     72.03    0.1%
 6900  2000  4000   800     67710     54.37    0.0%
 7000  2000  4000   800     68180     39.63    0.0%
 7100  2000  4000   800     68640     75.72    0.1%
 7200  2000  4000   800     68950     69.75    0.1%
 7300  2000  4000   800     69240     71.25    0.1%
 7400  2000  4000   800     69750     51.88    0.0%
 7500  2000  4000   800     70070     95.55    0.1%
 7600  2000  4000   800     70530     69.28    0.0%
 7700  2000  4000   800     70790     38.73    0.0%
 7800  2000  4000   800     71160     55.41    0.0%
 7900  2000  4000   800     71450     70.57    0.0%
 8000  2000  4000   800     71920     51.01    0.0%
 8100  2000  4000   800     72130     55.84    0.0%
 8200  2000  4000   800     72580     82.16    0.1%
 8300  2000  4000   800     72700     48.16    0.0%
 8400  2000  4000   800     73110     73.55    0.1%
 8500  2000  4000   800     73630     50.23    0.0%
 8600  2000  4000   800     73950     69.79    0.0%
 8700  2000  4000   800     74340     103.8    0.1%
 8800  2000  4000   800     74760     69.65    0.0%
 8900  2000  4000   800     75140     163.6    0.2%
 9000  2000  4000   800     75520     38.03    0.0%
 9100  2000  4000   800     75800     53.41    0.0%
 9200  2000  4000   800     76170     78.76    0.1%
 9300  2000  4000   800     76500     67.15    0.0%
 9400  2000  4000   800     76830     53.26    0.0%
 9500  2000  4000   800     77190     81.99    0.1%
 9600  2000  4000   800     77560     67.23    0.0%
 9700  2000  4000   800     77960     73.46    0.0%
 9800  2000  4000   800     78310      48.1    0.0%
 9900  2000  4000   800     78640     44.88    0.0%
10000  1000  4000   800     79080     55.88    0.0%
10000  1020  4000   800     79020     67.31    0.0%
10000  1040  4000   800     78860     82.88    0.1%
10000  1060  4000   800     79240     73.06    0.0%
10000  1080  4000   800     78950     56.64    0.0%
10000  1100  4000   800     78950     79.84    0.1%
10000  1120  4000   800     78950     57.91    0.0%
10000  1140  4000   800     78970     101.1    0.1%
10000  1160  4000   800     78970     48.03    0.0%
10000  1180  4000   800     78950     56.77    0.0%
10000  1200  4000   800     78960     79.65    0.1%
10000  1220  4000   800     79140     43.36    0.0%
10000  1240  4000   800     78960     59.05    0.0%
10000  1260  4000   800     78960     77.96    0.0%
10000  1280  4000   800     79100     57.06    0.0%
10000  1300  4000   800     78980     46.07    0.0%
10000  1320  4000   800     79030     77.23    0.0%
10000  1340  4000   800     79020     58.07    0.0%
10000  1360  4000   800     79560     98.06    0.1%
10000  1380  4000   800     79090     100.1    0.1%
10000  1400  4000   800     79180     62.22    0.0%
10000  1420  4000   800     79190     112.8    0.1%
10000  1440  4000   800     79080     74.54    0.0%
10000  1460  4000   800     79200     79.36    0.1%
10000  1480  4000   800     79070     70.26    0.0%
10000  1500  4000   800     79050     34.97    0.0%
10000  1520  4000   800     78990     79.25    0.1%
10000  1540  4000   800     78960     58.36    0.0%
10000  1560  4000   800     78990     56.18    0.0%
10000  1580  4000   800     79160     52.37    0.0%
10000  1600  4000   800     79120     60.56    0.0%
10000  1620  4000   800     79220     36.47    0.0%
10000  1640  4000   800     79120     92.27    0.1%
10000  1660  4000   800     79190     59.35    0.0%
10000  1680  4000   800     79080     43.17    0.0%
10000  1700  4000   800     79210     44.72    0.0%
10000  1720  4000   800     79800     74.34    0.0%
10000  1740  4000   800     79080     70.44    0.0%
10000  1760  4000   800     79160     43.27    0.0%
10000  1780  4000   800     79100     49.72    0.0%
10000  1800  4000   800     79180     74.58    0.0%
10000  1820  4000   800     79070     51.65    0.0%
10000  1840  4000   800     79150     31.05    0.0%
10000  1860  4000   800     79130     42.12    0.0%
10000  1880  4000   800     79150     70.12    0.0%
10000  1900  4000   800     79200      63.4    0.0%
10000  1920  4000   800     79250     58.03    0.0%
10000  1940  4000   800     79160     61.56    0.0%
10000  1960  4000   800     79200        55    0.0%
10000  1980  4000   800     79280     48.44    0.0%
10000  2000  1000   800     45850     34.41    0.0%
10000  2000  1060   800     46500     50.21    0.1%
10000  2000  1120   800     47190     47.03    0.0%
10000  2000  1180   800     47680     33.58    0.0%
10000  2000  1240   800     48450     55.61    0.1%
10000  2000  1300   800     48990     48.11    0.0%
10000  2000  1360   800     49700     66.24    0.1%
10000  2000  1420   800     50780     36.89    0.0%
10000  2000  1480   800     51510     22.26    0.0%
10000  2000  1540   800     52210     78.84    0.1%
10000  2000  1600   800     52910     63.15    0.1%
10000  2000  1660   800     53460     33.58    0.0%
10000  2000  1720   800     54280     60.03    0.1%
10000  2000  1780   800     54770     46.02    0.0%
10000  2000  1840   800     55330     28.78    0.0%
10000  2000  1900   800     56070     29.54    0.0%
10000  2000  1960   800     56770     49.41    0.0%
10000  2000  2020   800     57320     26.94    0.0%
10000  2000  2080   800     58010      44.3    0.0%
10000  2000  2140   800     58660     112.8    0.1%
10000  2000  2200   800     59150     64.93    0.1%
10000  2000  2260   800     59780     26.66    0.0%
10000  2000  2320   800     60370     49.42    0.0%
10000  2000  2380   800     60960      66.5    0.1%
10000  2000  2440   800     61550     53.43    0.0%
10000  2000  2500   800     62220     51.02    0.0%
10000  2000  2560   800     62720     40.48    0.0%
10000  2000  2620   800     63370     43.36    0.0%
10000  2000  2680   800     64090     58.85    0.0%
10000  2000  2740   800     64690     31.57    0.0%
10000  2000  2800   800     65290     64.32    0.0%
10000  2000  2860   800     66890      57.1    0.0%
10000  2000  2920   800     67600     41.42    0.0%
10000  2000  2980   800     68330     53.77    0.0%
10000  2000  3040   800     69000       115    0.1%
10000  2000  3100   800     69570     43.19    0.0%
10000  2000  3160   800     70320     53.88    0.0%
10000  2000  3220   800     70960     63.93    0.0%
10000  2000  3280   800     71710     49.12    0.0%
10000  2000  3340   800     72430     45.72    0.0%
10000  2000  3400   800     73000     50.28    0.0%
10000  2000  3460   800     73630     48.41    0.0%
10000  2000  3520   800     74400     40.38    0.0%
10000  2000  3580   800     75020     63.33    0.0%
10000  2000  3640   800     75670     98.47    0.1%
10000  2000  3700   800     76260     59.97    0.0%
10000  2000  3760   800     76870      77.6    0.1%
10000  2000  3820   800     77400     64.48    0.0%
10000  2000  3880   800     78020     59.56    0.0%
10000  2000  3940   800     78650     78.18    0.0%
10000  2000  4000   400     77070     63.66    0.0%
10000  2000  4000   408     77170     46.68    0.0%
10000  2000  4000   416     77370     55.42    0.0%
10000  2000  4000   424     77540     76.62    0.0%
10000  2000  4000   432     77620     43.02    0.0%
10000  2000  4000   440     77600     54.03    0.0%
10000  2000  4000   448     77620     37.59    0.0%
10000  2000  4000   456     77670      45.2    0.0%
10000  2000  4000   464     77620     37.71    0.0%
10000  2000  4000   472     77580     41.08    0.0%
10000  2000  4000   480     77750     44.85    0.0%
10000  2000  4000   488     77570     58.07    0.0%
10000  2000  4000   496     77620     69.86    0.0%
10000  2000  4000   504     77720     65.32    0.0%
10000  2000  4000   512     77510     53.69    0.0%
10000  2000  4000   520     77430     43.58    0.0%
10000  2000  4000   528     77430     87.73    0.1%
10000  2000  4000   536     77340      62.5    0.0%
10000  2000  4000   544     77560      56.5    0.0%
10000  2000  4000   552     77560     55.24    0.0%
10000  2000  4000   560     77490     39.31    0.0%
10000  2000  4000   568     77590     43.47    0.0%
10000  2000  4000   576     77480     66.21    0.0%
10000  2000  4000   584     77600     42.79    0.0%
10000  2000  4000   592     77490     37.92    0.0%
10000  2000  4000   600     77720     79.39    0.1%
10000  2000  4000   608     77710     45.39    0.0%
10000  2000  4000   616     77880     85.31    0.1%
10000  2000  4000   624     77840     48.81    0.0%
10000  2000  4000   632     77970     66.88    0.0%
10000  2000  4000   640     78050     57.81    0.0%
10000  2000  4000   648     78080     40.17    0.0%
10000  2000  4000   656     78080     53.67    0.0%
10000  2000  4000   664     78140     46.21    0.0%
10000  2000  4000   672     78340     65.37    0.0%
10000  2000  4000   680     78360     29.33    0.0%
10000  2000  4000   688     78460      88.1    0.1%
10000  2000  4000   696     78540     44.09    0.0%
10000  2000  4000   704     78560     101.5    0.1%
10000  2000  4000   712     78600     68.45    0.0%
10000  2000  4000   720     78680     72.33    0.0%
10000  2000  4000   728     78660      35.8    0.0%
10000  2000  4000   736     78890     34.62    0.0%
10000  2000  4000   744     78820     72.62    0.0%
10000  2000  4000   752     79450     57.09    0.0%
10000  2000  4000   760     79070     43.73    0.0%
10000  2000  4000   768     79060     51.41    0.0%
10000  2000  4000   776     79110     45.93    0.0%
10000  2000  4000   784     79140     43.38    0.0%
10000  2000  4000   792     79270     63.74    0.0%
10000  2000  4000   800     79200     72.76    0.0%

Quality and confidence:
param     error
v         0.004
t         0.024
a         0.008
d          0.06

Model:
Time ~=        0
    + v    3.678
    + t    0.203
    + a    11.08
    + d    5.608
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "feasibility_check", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    3.646
    + t        0
    + a    9.442
    + d    4.314
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     54090      75.2    0.1%
 5100  2000  4000   800     54450     59.01    0.1%
 5200  2000  4000   800     54790     52.77    0.0%
 5300  2000  4000   800     55090     60.74    0.1%
 5400  2000  4000   800     55490     45.08    0.0%
 5500  2000  4000   800     55780     39.08    0.0%
 5600  2000  4000   800     56210     72.55    0.1%
 5700  2000  4000   800     56500      64.4    0.1%
 5800  2000  4000   800     56960     32.54    0.0%
 5900  2000  4000   800     57250     44.76    0.0%
 6000  2000  4000   800     57730     59.03    0.1%
 6100  2000  4000   800     57920     49.84    0.0%
 6200  2000  4000   800     58320     42.95    0.0%
 6300  2000  4000   800     58660     56.17    0.0%
 6400  2000  4000   800     59020     63.08    0.1%
 6500  2000  4000   800     59400     52.62    0.0%
 6600  2000  4000   800     59700     51.71    0.0%
 6700  2000  4000   800     60170     47.73    0.0%
 6800  2000  4000   800     60430     66.71    0.1%
 6900  2000  4000   800     60830     57.83    0.0%
 7000  2000  4000   800     61210     38.18    0.0%
 7100  2000  4000   800     61840     54.97    0.0%
 7200  2000  4000   800     62020     55.23    0.0%
 7300  2000  4000   800     62420     69.99    0.1%
 7400  2000  4000   800     62750     50.62    0.0%
 7500  2000  4000   800     63150     41.77    0.0%
 7600  2000  4000   800     63490     47.22    0.0%
 7700  2000  4000   800     63830     64.79    0.1%
 7800  2000  4000   800     64190     64.13    0.0%
 7900  2000  4000   800     64580     53.16    0.0%
 8000  2000  4000   800     65000     77.09    0.1%
 8100  2000  4000   800     65350     53.38    0.0%
 8200  2000  4000   800     65720     74.17    0.1%
 8300  2000  4000   800     66140     83.08    0.1%
 8400  2000  4000   800     66430     45.52    0.0%
 8500  2000  4000   800     66670      62.6    0.0%
 8600  2000  4000   800     67030     78.24    0.1%
 8700  2000  4000   800     67430     48.51    0.0%
 8800  2000  4000   800     67800     54.12    0.0%
 8900  2000  4000   800     68030     44.85    0.0%
 9000  2000  4000   800     68560     68.23    0.0%
 9100  2000  4000   800     69030      21.4    0.0%
 9200  2000  4000   800     69400     44.21    0.0%
 9300  2000  4000   800     69760     91.81    0.1%
 9400  2000  4000   800     70100     84.43    0.1%
 9500  2000  4000   800     70510     59.31    0.0%
 9600  2000  4000   800     70770     78.61    0.1%
 9700  2000  4000   800     71200     69.75    0.0%
 9800  2000  4000   800     71520     66.94    0.0%
 9900  2000  4000   800     71860     64.14    0.0%
10000  1000  4000   800     72180     47.13    0.0%
10000  1020  4000   800     72190     77.98    0.1%
10000  1040  4000   800     72240     74.41    0.1%
10000  1060  4000   800     72170      58.6    0.0%
10000  1080  4000   800     72020     90.71    0.1%
10000  1100  4000   800     72190     83.44    0.1%
10000  1120  4000   800     72280     45.45    0.0%
10000  1140  4000   800     72080     58.11    0.0%
10000  1160  4000   800     72130     60.62    0.0%
10000  1180  4000   800     72180     45.15    0.0%
10000  1200  4000   800     72220     61.45    0.0%
10000  1220  4000   800     72170     82.93    0.1%
10000  1240  4000   800     71990     68.77    0.0%
10000  1260  4000   800     72140     46.23    0.0%
10000  1280  4000   800     72110     100.1    0.1%
10000  1300  4000   800     72080     46.15    0.0%
10000  1320  4000   800     72070     69.45    0.0%
10000  1340  4000   800     72090     63.32    0.0%
10000  1360  4000   800     72330     57.65    0.0%
10000  1380  4000   800     72150     54.14    0.0%
10000  1400  4000   800     72120     64.61    0.0%
10000  1420  4000   800     72290     46.64    0.0%
10000  1440  4000   800     72140     47.53    0.0%
10000  1460  4000   800     72350     56.93    0.0%
10000  1480  4000   800     72090     68.44    0.0%
10000  1500  4000   800     72130     58.74    0.0%
10000  1520  4000   800     72100     28.89    0.0%
10000  1540  4000   800     72040     70.44    0.0%
10000  1560  4000   800     72080     56.07    0.0%
10000  1580  4000   800     72140     56.16    0.0%
10000  1600  4000   800     72250     83.95    0.1%
10000  1620  4000   800     72290     85.41    0.1%
10000  1640  4000   800     72140     31.93    0.0%
10000  1660  4000   800     72200     115.1    0.1%
10000  1680  4000   800     72110     59.59    0.0%
10000  1700  4000   800     72070     40.26    0.0%
10000  1720  4000   800     72140     33.66    0.0%
10000  1740  4000   800     72030     53.67    0.0%
10000  1760  4000   800     72140     50.73    0.0%
10000  1780  4000   800     72000     81.32    0.1%
10000  1800  4000   800     72140     88.53    0.1%
10000  1820  4000   800     72050     77.69    0.1%
10000  1840  4000   800     72100     54.06    0.0%
10000  1860  4000   800     72040     53.73    0.0%
10000  1880  4000   800     72170     65.84    0.0%
10000  1900  4000   800     72140     77.47    0.1%
10000  1920  4000   800     72230     50.52    0.0%
10000  1940  4000   800     72160     46.62    0.0%
10000  1960  4000   800     72160     52.64    0.0%
10000  1980  4000   800     72250      87.5    0.1%
10000  2000  1000   800     43840     39.68    0.0%
10000  2000  1060   800     44440     59.44    0.1%
10000  2000  1120   800     45010     47.26    0.1%
10000  2000  1180   800     45520     51.77    0.1%
10000  2000  1240   800     46130     38.64    0.0%
10000  2000  1300   800     46700     52.81    0.1%
10000  2000  1360   800     47240     44.31    0.0%
10000  2000  1420   800     47710     37.48    0.0%
10000  2000  1480   800     48510     70.94    0.1%
10000  2000  1540   800     48880     51.63    0.1%
10000  2000  1600   800     49660     88.61    0.1%
10000  2000  1660   800     50200     31.38    0.0%
10000  2000  1720   800     50750     64.22    0.1%
10000  2000  1780   800     51380     45.53    0.0%
10000  2000  1840   800     51780     35.95    0.0%
10000  2000  1900   800     52550     34.54    0.0%
10000  2000  1960   800     52950     83.96    0.1%
10000  2000  2020   800     53590     49.95    0.0%
10000  2000  2080   800     54160     48.64    0.0%
10000  2000  2140   800     54670     71.02    0.1%
10000  2000  2200   800     55200     48.88    0.0%
10000  2000  2260   800     55740      28.8    0.0%
10000  2000  2320   800     56200     117.2    0.2%
10000  2000  2380   800     56770     29.88    0.0%
10000  2000  2440   800     57470     87.14    0.1%
10000  2000  2500   800     57830     43.65    0.0%
10000  2000  2560   800     58280      39.7    0.0%
10000  2000  2620   800     58880     57.39    0.0%
10000  2000  2680   800     59410     52.21    0.0%
10000  2000  2740   800     60070     96.88    0.1%
10000  2000  2800   800     60540     68.13    0.1%
10000  2000  2860   800     61170     55.54    0.0%
10000  2000  2920   800     61740     43.81    0.0%
10000  2000  2980   800     62350     88.07    0.1%
10000  2000  3040   800     62890     37.29    0.0%
10000  2000  3100   800     63510     45.78    0.0%
10000  2000  3160   800     64170     53.14    0.0%
10000  2000  3220   800     64750     49.79    0.0%
10000  2000  3280   800     65450     44.44    0.0%
10000  2000  3340   800     66010     69.36    0.1%
10000  2000  3400   800     66520     25.84    0.0%
10000  2000  3460   800     67080     48.73    0.0%
10000  2000  3520   800     67790     55.16    0.0%
10000  2000  3580   800     68330     48.75    0.0%
10000  2000  3640   800     68960     48.71    0.0%
10000  2000  3700   800     69450     39.58    0.0%
10000  2000  3760   800     70060     35.56    0.0%
10000  2000  3820   800     70590      56.1    0.0%
10000  2000  3880   800     71180     69.02    0.0%
10000  2000  3940   800     71620     60.41    0.0%
10000  2000  4000   400     70370     28.87    0.0%
10000  2000  4000   408     70510     81.31    0.1%
10000  2000  4000   416     70600     86.01    0.1%
10000  2000  4000   424     70700     77.57    0.1%
10000  2000  4000   432     70780     64.84    0.0%
10000  2000  4000   440     70880     99.71    0.1%
10000  2000  4000   448     70760     55.84    0.0%
10000  2000  4000   456     70780     84.77    0.1%
10000  2000  4000   464     70870     56.47    0.0%
10000  2000  4000   472     70760     59.15    0.0%
10000  2000  4000   480     70880     67.13    0.0%
10000  2000  4000   488     70750     66.67    0.0%
10000  2000  4000   496     70720     51.39    0.0%
10000  2000  4000   504     70750     72.28    0.1%
10000  2000  4000   512     70580     58.36    0.0%
10000  2000  4000   520     70630     68.94    0.0%
10000  2000  4000   528     70580     81.67    0.1%
10000  2000  4000   536     70620     57.53    0.0%
10000  2000  4000   544     70630     70.28    0.0%
10000  2000  4000   552     70620     31.78    0.0%
10000  2000  4000   560     70690     51.79    0.0%
10000  2000  4000   568     70640     74.26    0.1%
10000  2000  4000   576     70650     44.64    0.0%
10000  2000  4000   584     70670      66.5    0.0%
10000  2000  4000   592     70620     54.19    0.0%
10000  2000  4000   600     70770     99.11    0.1%
10000  2000  4000   608     70770     47.23    0.0%
10000  2000  4000   616     70910     26.01    0.0%
10000  2000  4000   624     70820     46.71    0.0%
10000  2000  4000   632     71000     75.34    0.1%
10000  2000  4000   640     70980      58.2    0.0%
10000  2000  4000   648     71120     41.29    0.0%
10000  2000  4000   656     71130     53.74    0.0%
10000  2000  4000   664     71170     48.88    0.0%
10000  2000  4000   672     71210     75.76    0.1%
10000  2000  4000   680     71370     55.82    0.0%
10000  2000  4000   688     71350      54.9    0.0%
10000  2000  4000   696     71420     63.98    0.0%
10000  2000  4000   704     71510     68.74    0.0%
10000  2000  4000   712     71580     25.47    0.0%
10000  2000  4000   720     71680     41.63    0.0%
10000  2000  4000   728     71720     38.34    0.0%
10000  2000  4000   736     71890        61    0.0%
10000  2000  4000   744     71760     38.74    0.0%
10000  2000  4000   752     72100     75.67    0.1%
10000  2000  4000   760     72040     53.92    0.0%
10000  2000  4000   768     71950     61.37    0.0%
10000  2000  4000   776     71970     52.33    0.0%
10000  2000  4000   784     72040     57.38    0.0%
10000  2000  4000   792     72210     52.55    0.0%
10000  2000  4000   800     72210     58.37    0.0%

Quality and confidence:
param     error
v         0.003
t         0.017
a         0.005
d         0.044

Model:
Time ~=        0
    + v     3.61
    + t        0
    + a    9.413
    + d    4.774
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

frame/staking/src/pallet/impls.rs

shawntabrizi · 2021-08-17T15:26:34Z

frame/staking/src/weights.rs

@@ -18,22 +18,22 @@
 //! Autogenerated weights for pallet_staking
 //!
 //! THIS FILE WAS AUTO-GENERATED USING THE SUBSTRATE BENCHMARK CLI VERSION 4.0.0-dev
-//! DATE: 2021-08-07, STEPS: `50`, REPEAT: 20, LOW RANGE: `[]`, HIGH RANGE: `[]`
-//! EXECUTION: Some(Wasm), WASM-EXECUTION: Compiled, CHAIN: Some("dev"), DB CACHE: 128


These are numbers that I ran locally, I am waiting for the bot to override them.

…path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic=* --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/election-provider-multi-phase/src/weights.rs --template=./.maintain/frame-weight-template.hbs

frame/election-provider-multi-phase/src/benchmarking.rs

shawntabrizi · 2021-08-18T09:46:12Z

frame/election-provider-multi-phase/src/benchmarking.rs

@@ -303,7 +307,8 @@ frame_benchmarking::benchmarks! {
 			..Default::default()
 		};

-		MultiPhase::<T>::on_initialize_open_signed().expect("should be ok to start signed phase");
+		<MultiPhase<T>>::create_snapshot().unwrap();


why not have all these unwraps be a little more descriptive about what went wrong?

either with an Err or an expect

Unless if the expect is going to a multi-line, comprehensive description of why something failed, writing some rudimentary .expect(<foo failed>) is not at all more descriptive than the standard error message of unwrap.

Err would have been nicer, but not in this case because most of these unwraps are not on dispatchables, therefore their error is not Into<&'static str> and needs a map_err or an implementation of that just for benchmarks.

I will look into the second option, though my opinion is still that unwrap is fine in benchmark setup.

with the help of strum_macros: e6eb8b0 (#9569)

…h/substrate into kiz-remove-election-weight-api

shawntabrizi · 2021-08-18T10:56:38Z

frame/election-provider-multi-phase/src/weights.rs

+			.saturating_add(RocksDbWeight::get().reads(1 as Weight))
+			.saturating_add(RocksDbWeight::get().writes(1 as Weight))


its not clear to me where all these reads and writes went to

this benchmark used to be: create snapshot, and open signed phase. Now it is only "open the signed phase", and therefore way less storage.

The snapshotting operation itself has become self-weighing, and we no longer track it here.

shawntabrizi

overall looks good.

…ove-election-weight-api

kianenigma · 2021-08-18T13:24:23Z

/benchmark runtime pallet pallet_election_provider_multi_phase

parity-benchapp · 2021-08-18T13:24:24Z

Benchmark Runtime Pallet for branch "kiz-remove-election-weight-api" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/election-provider-multi-phase/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_nothing", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    23.87
              µs

Reads = 8
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    23.87
              µs

Reads = 8
Writes = 0
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_signed", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    34.54
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    34.54
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    33.56
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    33.56
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_accept_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    50.59
              µs

Reads = 1
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    50.59
              µs

Reads = 1
Writes = 2
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "finalize_signed_phase_reject_solution", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    33.38
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    33.38
              µs

Reads = 1
Writes = 1
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "create_snapshot_internal", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     8835
              µs

Reads = 0
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     8835
              µs

Reads = 0
Writes = 3
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "elect_queued", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + a    1.736
    + d    0.551
              µs

Reads = 6 + (0 * a) + (0 * d)
Writes = 8 + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    a     d   mean µs  sigma µs       %
 1000   800      2194     14.35    0.6%
 1060   800      2276     4.169    0.1%
 1120   800      2395     17.19    0.7%
 1180   800      2483     14.02    0.5%
 1240   800      2576     10.06    0.3%
 1300   800      2707     10.99    0.4%
 1360   800      2767     8.007    0.2%
 1420   800      2868     14.96    0.5%
 1480   800      2948      10.7    0.3%
 1540   800      3082     18.75    0.6%
 1600   800      3202      15.9    0.4%
 1660   800      3300     10.92    0.3%
 1720   800      3417     10.24    0.2%
 1780   800      3481     21.97    0.6%
 1840   800      3608     21.98    0.6%
 1900   800      3714     9.183    0.2%
 1960   800      3772     12.87    0.3%
 2020   800      3854     12.79    0.3%
 2080   800      3994     13.09    0.3%
 2140   800      4070     14.53    0.3%
 2200   800      4201     13.38    0.3%
 2260   800      4311     12.24    0.2%
 2320   800      4412     18.02    0.4%
 2380   800      4508      13.1    0.2%
 2440   800      4583     12.27    0.2%
 2500   800      4672     12.85    0.2%
 2560   800      4797     18.11    0.3%
 2620   800      4962     12.52    0.2%
 2680   800      5034     10.55    0.2%
 2740   800      5146     13.33    0.2%
 2800   800      5265     24.91    0.4%
 2860   800      5349     11.28    0.2%
 2920   800      5461     23.71    0.4%
 2980   800      5564     19.88    0.3%
 3040   800      5669     14.98    0.2%
 3100   800      5816     14.85    0.2%
 3160   800      5897     18.89    0.3%
 3220   800      5994     23.07    0.3%
 3280   800      6058     9.902    0.1%
 3340   800      6188     23.25    0.3%
 3400   800      6298     24.77    0.3%
 3460   800      6387     27.58    0.4%
 3520   800      6509     8.915    0.1%
 3580   800      6661     13.04    0.1%
 3640   800      6709     24.32    0.3%
 3700   800      6840      13.2    0.1%
 3760   800      6939     12.15    0.1%
 3820   800      7072      19.7    0.2%
 3880   800      7175     27.67    0.3%
 3940   800      7283     12.39    0.1%
 4000   400      7244     14.61    0.2%
 4000   408      7297     25.21    0.3%
 4000   416      7243     7.727    0.1%
 4000   424      7248     15.15    0.2%
 4000   432      7296     20.99    0.2%
 4000   440      7247     25.76    0.3%
 4000   448      7302      26.8    0.3%
 4000   456      7286     19.35    0.2%
 4000   464      7287     21.04    0.2%
 4000   472      7296     12.81    0.1%
 4000   480      7315      17.1    0.2%
 4000   488      7294     13.19    0.1%
 4000   496      7306     24.87    0.3%
 4000   504      7308     14.29    0.1%
 4000   512      7335     18.67    0.2%
 4000   520      7311     16.72    0.2%
 4000   528      7320     11.24    0.1%
 4000   536      7327     17.54    0.2%
 4000   544      7341     16.57    0.2%
 4000   552      7341     14.72    0.2%
 4000   560      7343      30.2    0.4%
 4000   568      7351     21.59    0.2%
 4000   576      7351     20.41    0.2%
 4000   584      7348     15.14    0.2%
 4000   592      7373     10.94    0.1%
 4000   600      7353     14.77    0.2%
 4000   608      7365     18.96    0.2%
 4000   616      7358     14.62    0.1%
 4000   624      7387     13.35    0.1%
 4000   632      7390     26.83    0.3%
 4000   640      7394     14.92    0.2%
 4000   648      7403     16.32    0.2%
 4000   656      7399     22.81    0.3%
 4000   664      7421     20.77    0.2%
 4000   672      7415      18.6    0.2%
 4000   680      7400     14.23    0.1%
 4000   688      7420     9.289    0.1%
 4000   696      7396     19.89    0.2%
 4000   704      7443     18.34    0.2%
 4000   712      7431     16.54    0.2%
 4000   720      7419     17.89    0.2%
 4000   728      7456     17.28    0.2%
 4000   736      7446     14.29    0.1%
 4000   744      7481     28.11    0.3%
 4000   752      7452     17.34    0.2%
 4000   760      7451     16.55    0.2%
 4000   768      7456     15.89    0.2%
 4000   776      7437     11.42    0.1%
 4000   784      7500     31.66    0.4%
 4000   792      7476     17.37    0.2%
 4000   800      7456     25.26    0.3%

Quality and confidence:
param     error
a         0.001
d         0.013

Model:
Time ~=    82.39
    + a    1.769
    + d     0.32
              µs

Reads = 6 + (0 * a) + (0 * d)
Writes = 8 + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    77.35
    + c    0.368
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    c   mean µs  sigma µs       %
    1     77.71     0.263    0.3%
    2     78.08     0.126    0.1%
    3     78.66     0.169    0.2%
    4     78.69     0.255    0.3%
    5     79.18     0.197    0.2%
    6     79.61     0.211    0.2%
    7     79.93     0.168    0.2%
    8     80.28     0.222    0.2%
    9     80.73     0.149    0.1%

Quality and confidence:
param     error
c         0.009

Model:
Time ~=    77.36
    + c    0.369
              µs

Reads = 5 + (0 * c)
Writes = 3 + (0 * c)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit_unsigned", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    3.527
    + t    0.206
    + a    10.69
    + d    5.467
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     58610     45.09    0.0%
 5100  2000  4000   800     58900     62.83    0.1%
 5200  2000  4000   800     59190     78.71    0.1%
 5300  2000  4000   800     59600     99.67    0.1%
 5400  2000  4000   800     59970     60.33    0.1%
 5500  2000  4000   800     60400     38.18    0.0%
 5600  2000  4000   800     60760     40.99    0.0%
 5700  2000  4000   800     61100     53.83    0.0%
 5800  2000  4000   800     61520     86.98    0.1%
 5900  2000  4000   800     61840     35.34    0.0%
 6000  2000  4000   800     62240     63.83    0.1%
 6100  2000  4000   800     62480     51.35    0.0%
 6200  2000  4000   800     62850     20.98    0.0%
 6300  2000  4000   800     63170     38.47    0.0%
 6400  2000  4000   800     63520     65.16    0.1%
 6500  2000  4000   800     63870     57.06    0.0%
 6600  2000  4000   800     64190     94.31    0.1%
 6700  2000  4000   800     64700     32.15    0.0%
 6800  2000  4000   800     64920     46.85    0.0%
 6900  2000  4000   800     65370     89.66    0.1%
 7000  2000  4000   800     65700     39.92    0.0%
 7100  2000  4000   800     66060      66.6    0.1%
 7200  2000  4000   800     66400     86.15    0.1%
 7300  2000  4000   800     66700     34.11    0.0%
 7400  2000  4000   800     67030     50.15    0.0%
 7500  2000  4000   800     67440     42.77    0.0%
 7600  2000  4000   800     67730      79.9    0.1%
 7700  2000  4000   800     68080     74.92    0.1%
 7800  2000  4000   800     68560     113.1    0.1%
 7900  2000  4000   800     68770     82.44    0.1%
 8000  2000  4000   800     69180     56.71    0.0%
 8100  2000  4000   800     69590     63.11    0.0%
 8200  2000  4000   800     69940     57.86    0.0%
 8300  2000  4000   800     70320     27.16    0.0%
 8400  2000  4000   800     70490     89.95    0.1%
 8500  2000  4000   800     70930     55.16    0.0%
 8600  2000  4000   800     71200     63.85    0.0%
 8700  2000  4000   800     71660     44.08    0.0%
 8800  2000  4000   800     72000     38.72    0.0%
 8900  2000  4000   800     72350     70.06    0.0%
 9000  2000  4000   800     72650      61.6    0.0%
 9100  2000  4000   800     72980     42.16    0.0%
 9200  2000  4000   800     73480     49.88    0.0%
 9300  2000  4000   800     73800      63.7    0.0%
 9400  2000  4000   800     74030      57.2    0.0%
 9500  2000  4000   800     74400     27.58    0.0%
 9600  2000  4000   800     74780     44.16    0.0%
 9700  2000  4000   800     75210     50.75    0.0%
 9800  2000  4000   800     75420     59.86    0.0%
 9900  2000  4000   800     75760     62.39    0.0%
10000  1000  4000   800     76260     57.83    0.0%
10000  1020  4000   800     76260      71.9    0.0%
10000  1040  4000   800     76210     49.11    0.0%
10000  1060  4000   800     76340     65.42    0.0%
10000  1080  4000   800     76070     61.05    0.0%
10000  1100  4000   800     76190     53.63    0.0%
10000  1120  4000   800     76300     62.63    0.0%
10000  1140  4000   800     76180     86.17    0.1%
10000  1160  4000   800     76180     77.18    0.1%
10000  1180  4000   800     76220      34.9    0.0%
10000  1200  4000   800     76220     38.31    0.0%
10000  1220  4000   800     76270     71.11    0.0%
10000  1240  4000   800     76170     75.67    0.0%
10000  1260  4000   800     76240     75.36    0.0%
10000  1280  4000   800     76360     36.57    0.0%
10000  1300  4000   800     76330     90.79    0.1%
10000  1320  4000   800     76240     38.99    0.0%
10000  1340  4000   800     76380     93.39    0.1%
10000  1360  4000   800     76730     62.32    0.0%
10000  1380  4000   800     76380     51.08    0.0%
10000  1400  4000   800     76270        80    0.1%
10000  1420  4000   800     76390     70.42    0.0%
10000  1440  4000   800     76270     26.13    0.0%
10000  1460  4000   800     76570      51.4    0.0%
10000  1480  4000   800     76300     54.14    0.0%
10000  1500  4000   800     76370     42.22    0.0%
10000  1520  4000   800     76310      46.4    0.0%
10000  1540  4000   800     76320     48.14    0.0%
10000  1560  4000   800     76300     64.99    0.0%
10000  1580  4000   800     76370      33.1    0.0%
10000  1600  4000   800     76430     50.33    0.0%
10000  1620  4000   800     76460     63.95    0.0%
10000  1640  4000   800     76380     57.65    0.0%
10000  1660  4000   800     76400     54.88    0.0%
10000  1680  4000   800     76290     67.68    0.0%
10000  1700  4000   800     76470     57.07    0.0%
10000  1720  4000   800     76430     63.41    0.0%
10000  1740  4000   800     76300     70.82    0.0%
10000  1760  4000   800     76480     88.78    0.1%
10000  1780  4000   800     76370     59.27    0.0%
10000  1800  4000   800     76380     64.91    0.0%
10000  1820  4000   800     76250     35.11    0.0%
10000  1840  4000   800     76450     91.84    0.1%
10000  1860  4000   800     76290     81.41    0.1%
10000  1880  4000   800     76410      58.1    0.0%
10000  1900  4000   800     76370     61.47    0.0%
10000  1920  4000   800     76520     51.95    0.0%
10000  1940  4000   800     76490     66.98    0.0%
10000  1960  4000   800     76420     38.12    0.0%
10000  1980  4000   800     76550      57.3    0.0%
10000  2000  1000   800     44470     42.97    0.0%
10000  2000  1060   800     45070     39.75    0.0%
10000  2000  1120   800     45720     25.28    0.0%
10000  2000  1180   800     46290     45.45    0.0%
10000  2000  1240   800     46840     26.38    0.0%
10000  2000  1300   800     47400     58.96    0.1%
10000  2000  1360   800     48110     57.69    0.1%
10000  2000  1420   800     49220     28.29    0.0%
10000  2000  1480   800     49830     22.56    0.0%
10000  2000  1540   800     50390     27.71    0.0%
10000  2000  1600   800     51250     49.16    0.0%
10000  2000  1660   800     51790     33.68    0.0%
10000  2000  1720   800     52430     55.39    0.1%
10000  2000  1780   800     53220     49.93    0.0%
10000  2000  1840   800     53490     21.69    0.0%
10000  2000  1900   800     54240     59.84    0.1%
10000  2000  1960   800     54700     42.27    0.0%
10000  2000  2020   800     55430     81.68    0.1%
10000  2000  2080   800     55980     40.56    0.0%
10000  2000  2140   800     56640     57.67    0.1%
10000  2000  2200   800     57220     31.56    0.0%
10000  2000  2260   800     57750     61.79    0.1%
10000  2000  2320   800     58220     77.27    0.1%
10000  2000  2380   800     58960     37.59    0.0%
10000  2000  2440   800     59430      39.8    0.0%
10000  2000  2500   800     60060     73.27    0.1%
10000  2000  2560   800     60530     20.25    0.0%
10000  2000  2620   800     61130     55.46    0.0%
10000  2000  2680   800     61750     46.14    0.0%
10000  2000  2740   800     62330     66.19    0.1%
10000  2000  2800   800     62910     40.93    0.0%
10000  2000  2860   800     64610     30.38    0.0%
10000  2000  2920   800     65200     62.48    0.0%
10000  2000  2980   800     65840     37.12    0.0%
10000  2000  3040   800     66430      48.2    0.0%
10000  2000  3100   800     67130     78.06    0.1%
10000  2000  3160   800     67810     41.32    0.0%
10000  2000  3220   800     68400     59.38    0.0%
10000  2000  3280   800     69150     116.9    0.1%
10000  2000  3340   800     69790        67    0.0%
10000  2000  3400   800     70280     64.05    0.0%
10000  2000  3460   800     71000     48.09    0.0%
10000  2000  3520   800     71720     53.74    0.0%
10000  2000  3580   800     72250     37.52    0.0%
10000  2000  3640   800     72960     82.46    0.1%
10000  2000  3700   800     73500     62.01    0.0%
10000  2000  3760   800     74060     45.21    0.0%
10000  2000  3820   800     74650     57.97    0.0%
10000  2000  3880   800     75290     49.82    0.0%
10000  2000  3940   800     75760     52.52    0.0%
10000  2000  4000   400     74130     40.51    0.0%
10000  2000  4000   408     74160     66.55    0.0%
10000  2000  4000   416     74280     57.29    0.0%
10000  2000  4000   424     74490      75.9    0.1%
10000  2000  4000   432     74560     44.97    0.0%
10000  2000  4000   440     74500     45.56    0.0%
10000  2000  4000   448     74570     88.51    0.1%
10000  2000  4000   456     74610     41.07    0.0%
10000  2000  4000   464     74520     75.97    0.1%
10000  2000  4000   472     74580     63.38    0.0%
10000  2000  4000   480     74700     43.33    0.0%
10000  2000  4000   488     74530     59.53    0.0%
10000  2000  4000   496     74570     63.65    0.0%
10000  2000  4000   504     74640     59.57    0.0%
10000  2000  4000   512     74420     66.19    0.0%
10000  2000  4000   520     74530     17.91    0.0%
10000  2000  4000   528     74430     54.43    0.0%
10000  2000  4000   536     74570     117.9    0.1%
10000  2000  4000   544     74540     75.76    0.1%
10000  2000  4000   552     74560     36.52    0.0%
10000  2000  4000   560     74500     34.85    0.0%
10000  2000  4000   568     74540     64.54    0.0%
10000  2000  4000   576     74510     53.37    0.0%
10000  2000  4000   584     74510     69.03    0.0%
10000  2000  4000   592     74550     40.46    0.0%
10000  2000  4000   600     74660     65.65    0.0%
10000  2000  4000   608     74630     68.15    0.0%
10000  2000  4000   616     74810     79.88    0.1%
10000  2000  4000   624     74800     63.25    0.0%
10000  2000  4000   632     74900      76.3    0.1%
10000  2000  4000   640     75010     62.45    0.0%
10000  2000  4000   648     75130     67.92    0.0%
10000  2000  4000   656     75180     22.07    0.0%
10000  2000  4000   664     75210     77.35    0.1%
10000  2000  4000   672     75410     63.65    0.0%
10000  2000  4000   680     75380     48.02    0.0%
10000  2000  4000   688     75350     94.09    0.1%
10000  2000  4000   696     75580     40.58    0.0%
10000  2000  4000   704     75530     79.99    0.1%
10000  2000  4000   712     75740     103.5    0.1%
10000  2000  4000   720     75810     42.14    0.0%
10000  2000  4000   728     75730     34.22    0.0%
10000  2000  4000   736     75940      30.2    0.0%
10000  2000  4000   744     75870     64.83    0.0%
10000  2000  4000   752     76360      53.1    0.0%
10000  2000  4000   760     76110     63.75    0.0%
10000  2000  4000   768     76130      81.8    0.1%
10000  2000  4000   776     76150     76.08    0.0%
10000  2000  4000   784     76230      91.9    0.1%
10000  2000  4000   792     76320     41.98    0.0%
10000  2000  4000   800     76370     68.79    0.0%

Quality and confidence:
param     error
v         0.004
t         0.023
a         0.007
d         0.059

Model:
Time ~=        0
    + v    3.553
    + t    0.035
    + a     10.6
    + d    6.128
              µs

Reads = 7 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 1 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "feasibility_check", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    3.499
    + t     0.16
    + a    8.966
    + d    4.586
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     t     a     d   mean µs  sigma µs       %
 5000  2000  4000   800     51680     73.04    0.1%
 5100  2000  4000   800     52010     41.57    0.0%
 5200  2000  4000   800     52430     68.19    0.1%
 5300  2000  4000   800     52730     69.77    0.1%
 5400  2000  4000   800     53130     57.69    0.1%
 5500  2000  4000   800     53550      54.9    0.1%
 5600  2000  4000   800     53770     42.76    0.0%
 5700  2000  4000   800     54150     58.27    0.1%
 5800  2000  4000   800     54540     54.79    0.1%
 5900  2000  4000   800     54830     37.37    0.0%
 6000  2000  4000   800     55220     39.21    0.0%
 6100  2000  4000   800     55630     72.99    0.1%
 6200  2000  4000   800     55890     27.47    0.0%
 6300  2000  4000   800     56300     62.72    0.1%
 6400  2000  4000   800     56640     56.37    0.0%
 6500  2000  4000   800     56980     34.05    0.0%
 6600  2000  4000   800     57350     61.03    0.1%
 6700  2000  4000   800     57700     46.55    0.0%
 6800  2000  4000   800     58040      51.6    0.0%
 6900  2000  4000   800     58390     32.38    0.0%
 7000  2000  4000   800     58790     55.98    0.0%
 7100  2000  4000   800     59080     41.15    0.0%
 7200  2000  4000   800     59380     34.47    0.0%
 7300  2000  4000   800     59750     54.05    0.0%
 7400  2000  4000   800     60140     63.52    0.1%
 7500  2000  4000   800     60420      55.2    0.0%
 7600  2000  4000   800     60750     58.56    0.0%
 7700  2000  4000   800     61160     57.25    0.0%
 7800  2000  4000   800     61560     81.34    0.1%
 7900  2000  4000   800     61820     76.68    0.1%
 8000  2000  4000   800     62340     54.61    0.0%
 8100  2000  4000   800     62600     50.93    0.0%
 8200  2000  4000   800     62920     57.34    0.0%
 8300  2000  4000   800     63310     66.74    0.1%
 8400  2000  4000   800     63540      37.6    0.0%
 8500  2000  4000   800     63960     54.22    0.0%
 8600  2000  4000   800     64230     57.22    0.0%
 8700  2000  4000   800     64650     64.04    0.0%
 8800  2000  4000   800     65120     68.92    0.1%
 8900  2000  4000   800     65270     42.29    0.0%
 9000  2000  4000   800     65760     55.42    0.0%
 9100  2000  4000   800     65950     44.82    0.0%
 9200  2000  4000   800     66360     68.16    0.1%
 9300  2000  4000   800     66720     87.26    0.1%
 9400  2000  4000   800     67080     42.15    0.0%
 9500  2000  4000   800     67500     36.01    0.0%
 9600  2000  4000   800     67840        48    0.0%
 9700  2000  4000   800     68240     38.34    0.0%
 9800  2000  4000   800     68530     72.76    0.1%
 9900  2000  4000   800     68830     57.43    0.0%
10000  1000  4000   800     69130     27.63    0.0%
10000  1020  4000   800     69170     117.1    0.1%
10000  1040  4000   800     69150     29.32    0.0%
10000  1060  4000   800     69230     70.38    0.1%
10000  1080  4000   800     68990     86.44    0.1%
10000  1100  4000   800     69070     74.45    0.1%
10000  1120  4000   800     69260     105.6    0.1%
10000  1140  4000   800     69060     60.96    0.0%
10000  1160  4000   800     69040     40.05    0.0%
10000  1180  4000   800     69160     89.55    0.1%
10000  1200  4000   800     69230     82.65    0.1%
10000  1220  4000   800     69130     56.92    0.0%
10000  1240  4000   800     69070     51.21    0.0%
10000  1260  4000   800     69130     77.49    0.1%
10000  1280  4000   800     69190     67.42    0.0%
10000  1300  4000   800     69100     58.28    0.0%
10000  1320  4000   800     69100     43.75    0.0%
10000  1340  4000   800     69140     41.43    0.0%
10000  1360  4000   800     69340      55.3    0.0%
10000  1380  4000   800     69240     97.49    0.1%
10000  1400  4000   800     69260     84.93    0.1%
10000  1420  4000   800     69310     69.21    0.0%
10000  1440  4000   800     69060      49.1    0.0%
10000  1460  4000   800     69320      42.8    0.0%
10000  1480  4000   800     69170     58.04    0.0%
10000  1500  4000   800     69250     101.3    0.1%
10000  1520  4000   800     69180     66.56    0.0%
10000  1540  4000   800     69100     41.59    0.0%
10000  1560  4000   800     69130      76.2    0.1%
10000  1580  4000   800     69220     55.45    0.0%
10000  1600  4000   800     69250     67.22    0.0%
10000  1620  4000   800     69280     60.48    0.0%
10000  1640  4000   800     69170     44.49    0.0%
10000  1660  4000   800     69220     65.43    0.0%
10000  1680  4000   800     69160     39.23    0.0%
10000  1700  4000   800     69200     48.68    0.0%
10000  1720  4000   800     69300     57.74    0.0%
10000  1740  4000   800     69190     59.15    0.0%
10000  1760  4000   800     69250     45.45    0.0%
10000  1780  4000   800     69130     54.77    0.0%
10000  1800  4000   800     69200      73.1    0.1%
10000  1820  4000   800     69180     33.73    0.0%
10000  1840  4000   800     69310      64.9    0.0%
10000  1860  4000   800     69210     60.17    0.0%
10000  1880  4000   800     69310        33    0.0%
10000  1900  4000   800     69260     60.63    0.0%
10000  1920  4000   800     69320      67.9    0.0%
10000  1940  4000   800     69260     54.89    0.0%
10000  1960  4000   800     69240     63.99    0.0%
10000  1980  4000   800     69420     87.57    0.1%
10000  2000  1000   800     42370     56.15    0.1%
10000  2000  1060   800     42960     82.59    0.1%
10000  2000  1120   800     43460     36.63    0.0%
10000  2000  1180   800     43990     59.91    0.1%
10000  2000  1240   800     44520     40.04    0.0%
10000  2000  1300   800     44950     37.16    0.0%
10000  2000  1360   800     45490     43.25    0.0%
10000  2000  1420   800     46130     96.52    0.2%
10000  2000  1480   800     46600     39.51    0.0%
10000  2000  1540   800     47240     44.98    0.0%
10000  2000  1600   800     47850     41.84    0.0%
10000  2000  1660   800     48410     30.78    0.0%
10000  2000  1720   800     48960     46.73    0.0%
10000  2000  1780   800     49480     52.81    0.1%
10000  2000  1840   800     49880     31.42    0.0%
10000  2000  1900   800     50350     24.06    0.0%
10000  2000  1960   800     51000     21.65    0.0%
10000  2000  2020   800     51580     45.23    0.0%
10000  2000  2080   800     52190      91.3    0.1%
10000  2000  2140   800     52570     33.83    0.0%
10000  2000  2200   800     53070     48.02    0.0%
10000  2000  2260   800     53640      42.3    0.0%
10000  2000  2320   800     54040     60.36    0.1%
10000  2000  2380   800     54570     38.48    0.0%
10000  2000  2440   800     55090     50.23    0.0%
10000  2000  2500   800     55500     31.26    0.0%
10000  2000  2560   800     56170     80.36    0.1%
10000  2000  2620   800     56590     38.57    0.0%
10000  2000  2680   800     57070     21.13    0.0%
10000  2000  2740   800     57570     42.65    0.0%
10000  2000  2800   800     58170     38.85    0.0%
10000  2000  2860   800     58770     48.05    0.0%
10000  2000  2920   800     59280     54.07    0.0%
10000  2000  2980   800     59850     58.25    0.0%
10000  2000  3040   800     60470     76.94    0.1%
10000  2000  3100   800     61050     55.47    0.0%
10000  2000  3160   800     61640     48.86    0.0%
10000  2000  3220   800     62250     52.47    0.0%
10000  2000  3280   800     62780     57.83    0.0%
10000  2000  3340   800     63410     49.24    0.0%
10000  2000  3400   800     63940     53.51    0.0%
10000  2000  3460   800     64520     56.64    0.0%
10000  2000  3520   800     65070     66.06    0.1%
10000  2000  3580   800     65620     75.51    0.1%
10000  2000  3640   800     66210     48.87    0.0%
10000  2000  3700   800     66730     43.56    0.0%
10000  2000  3760   800     67130     59.21    0.0%
10000  2000  3820   800     67880     101.2    0.1%
10000  2000  3880   800     68270     39.68    0.0%
10000  2000  3940   800     68730     54.66    0.0%
10000  2000  4000   400     67390     79.21    0.1%
10000  2000  4000   408     67380     45.98    0.0%
10000  2000  4000   416     67410     49.82    0.0%
10000  2000  4000   424     67600     26.97    0.0%
10000  2000  4000   432     67680     41.85    0.0%
10000  2000  4000   440     67680     33.88    0.0%
10000  2000  4000   448     67740     56.52    0.0%
10000  2000  4000   456     67800     66.69    0.0%
10000  2000  4000   464     67780     38.21    0.0%
10000  2000  4000   472     67710     33.56    0.0%
10000  2000  4000   480     67890     91.85    0.1%
10000  2000  4000   488     67630     39.12    0.0%
10000  2000  4000   496     67720     44.73    0.0%
10000  2000  4000   504     67740     48.62    0.0%
10000  2000  4000   512     67530     38.33    0.0%
10000  2000  4000   520     67460     67.34    0.0%
10000  2000  4000   528     67470      40.3    0.0%
10000  2000  4000   536     67520     75.84    0.1%
10000  2000  4000   544     67540     43.71    0.0%
10000  2000  4000   552     67540     55.24    0.0%
10000  2000  4000   560     67560     66.54    0.0%
10000  2000  4000   568     67530     79.39    0.1%
10000  2000  4000   576     67440        57    0.0%
10000  2000  4000   584     67620      53.5    0.0%
10000  2000  4000   592     67560     47.97    0.0%
10000  2000  4000   600     67720     92.59    0.1%
10000  2000  4000   608     67660     70.85    0.1%
10000  2000  4000   616     67750     89.46    0.1%
10000  2000  4000   624     67890     74.93    0.1%
10000  2000  4000   632     67950     62.17    0.0%
10000  2000  4000   640     67930     23.14    0.0%
10000  2000  4000   648     68070     42.07    0.0%
10000  2000  4000   656     68120     77.43    0.1%
10000  2000  4000   664     68200     33.38    0.0%
10000  2000  4000   672     68280     50.94    0.0%
10000  2000  4000   680     68260     76.23    0.1%
10000  2000  4000   688     68400     55.28    0.0%
10000  2000  4000   696     68280     66.09    0.0%
10000  2000  4000   704     68420     58.29    0.0%
10000  2000  4000   712     68490     46.54    0.0%
10000  2000  4000   720     68750     48.93    0.0%
10000  2000  4000   728     68640     71.69    0.1%
10000  2000  4000   736     68800     37.19    0.0%
10000  2000  4000   744     68780     59.07    0.0%
10000  2000  4000   752     69090     66.87    0.0%
10000  2000  4000   760     68870      39.7    0.0%
10000  2000  4000   768     68950     42.95    0.0%
10000  2000  4000   776     68950     85.51    0.1%
10000  2000  4000   784     69110     31.46    0.0%
10000  2000  4000   792     69170     63.39    0.0%
10000  2000  4000   800     69250      57.1    0.0%

Quality and confidence:
param     error
v         0.003
t         0.018
a         0.006
d         0.047

Model:
Time ~=        0
    + v    3.478
    + t        0
    + a     8.93
    + d    5.199
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

kianenigma · 2021-08-18T13:24:32Z

/benchmark runtime pallet pallet_staking

parity-benchapp · 2021-08-18T13:24:33Z

Benchmark Runtime Pallet for branch "kiz-remove-election-weight-api" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    73.52
              µs

Reads = 5
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    73.52
              µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    58.12
              µs

Reads = 3
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    58.12
              µs

Reads = 3
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    61.54
              µs

Reads = 6
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    61.54
              µs

Reads = 6
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    53.02
    + s    0.054
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     52.52     0.177    0.3%
    2      53.4      0.15    0.2%
    4     53.48     0.063    0.1%
    6     53.78     0.189    0.3%
    8     52.98     0.095    0.1%
   10     54.73     1.248    2.2%
   12     53.27     0.095    0.1%
   14     53.49     0.145    0.2%
   16     54.92     0.148    0.2%
   18     54.12     0.119    0.2%
   20     53.85      0.23    0.4%
   22     54.45     0.529    0.9%
   24     53.96     0.241    0.4%
   26     54.98     0.428    0.7%
   28     54.41     0.231    0.4%
   30      54.7     0.264    0.4%
   32     54.33     0.142    0.2%
   34     55.92     0.115    0.2%
   36      54.9     0.152    0.2%
   38     54.79     0.135    0.2%
   40     54.95     0.124    0.2%
   42     55.31     0.093    0.1%
   44     55.26     0.114    0.2%
   46      55.7     0.125    0.2%
   48     55.56     0.156    0.2%
   50     55.66     0.244    0.4%
   52     55.54     0.189    0.3%
   54     55.91     0.176    0.3%
   56      55.9     0.389    0.6%
   58     56.35     0.156    0.2%
   60     56.33     0.114    0.2%
   62     56.71      0.18    0.3%
   64     56.76     0.385    0.6%
   66     56.84     0.246    0.4%
   68     56.79     0.187    0.3%
   70      57.5     0.189    0.3%
   72     57.21     0.486    0.8%
   74     57.14     0.238    0.4%
   76     57.55     0.119    0.2%
   78      57.8     0.151    0.2%
   80      57.4     0.308    0.5%
   82     57.39      0.13    0.2%
   84     57.46     0.225    0.3%
   86     57.82     0.097    0.1%
   88     57.51     0.235    0.4%
   90     57.57     0.223    0.3%
   92     58.06     0.163    0.2%
   94     57.47     0.156    0.2%
   96     57.87      0.25    0.4%
   98     58.42     0.249    0.4%
  100     58.24     0.387    0.6%

Quality and confidence:
param     error
s             0

Model:
Time ~=    53.16
    + s    0.053
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    86.11
    + s    2.448
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     80.58     0.305    0.3%
    2     89.66     0.169    0.1%
    4     95.81     1.048    1.0%
    6     100.8     0.861    0.8%
    8     107.7     0.132    0.1%
   10     109.4     0.117    0.1%
   12       117     0.463    0.3%
   14     120.3     0.138    0.1%
   16     124.7     0.176    0.1%
   18     129.9     0.201    0.1%
   20     134.7     0.318    0.2%
   22       140      0.46    0.3%
   24     145.1       0.4    0.2%
   26     150.7     0.594    0.3%
   28     154.3     0.239    0.1%
   30     159.4      0.21    0.1%
   32     165.7     0.301    0.1%
   34     169.1     0.344    0.2%
   36     174.8     0.223    0.1%
   38     179.5     0.386    0.2%
   40     185.1      0.59    0.3%
   42     189.6     0.295    0.1%
   44     193.7     0.214    0.1%
   46     199.2      0.48    0.2%
   48     204.7     0.444    0.2%
   50     208.3     0.509    0.2%
   52     212.6      0.52    0.2%
   54     217.8      0.41    0.1%
   56     223.8     0.481    0.2%
   58     228.8     0.311    0.1%
   60     232.2     0.516    0.2%
   62     238.1     0.261    0.1%
   64     242.2     0.894    0.3%
   66     246.6     0.637    0.2%
   68     251.8     0.657    0.2%
   70     256.6     0.434    0.1%
   72     261.2     0.614    0.2%
   74     267.1     0.774    0.2%
   76     271.3     0.831    0.3%
   78     277.3     0.675    0.2%
   80     280.5     0.737    0.2%
   82     285.6     0.759    0.2%
   84     293.2     2.814    0.9%
   86     295.8     0.456    0.1%
   88     301.4     0.287    0.0%
   90     305.9     2.215    0.7%
   92       312     0.788    0.2%
   94     317.6     0.941    0.2%
   96     320.9     1.033    0.3%
   98     326.7     0.579    0.1%
  100     331.9      0.48    0.1%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    85.82
    + s    2.453
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    34.93
              µs

Reads = 6
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    34.93
              µs

Reads = 6
Writes = 2
Pallet: "pallet_staking", Extrinsic: "kick", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    26.76
    + k     16.6
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    k   mean µs  sigma µs       %
    1     42.98     0.675    1.5%
    3     79.17     0.199    0.2%
    5     110.6     0.232    0.2%
    7     143.1     1.373    0.9%
    9     171.1     1.786    1.0%
   11     210.8     0.402    0.1%
   13     240.1     2.458    1.0%
   15     272.3     0.623    0.2%
   17     308.5     1.095    0.3%
   19     340.8     0.968    0.2%
   21       374     1.147    0.3%
   23     396.2     0.792    0.1%
   25     457.4     3.706    0.8%
   27     477.1     1.901    0.3%
   29       503     4.465    0.8%
   31     531.2     1.554    0.2%
   33     575.7     1.646    0.2%
   35     606.4     3.387    0.5%
   37     653.1      9.04    1.3%
   39     675.5     1.823    0.2%
   41       704      5.79    0.8%
   43     750.9     9.252    1.2%
   45     772.4     2.182    0.2%
   47     803.8     4.073    0.5%
   49     841.7     2.055    0.2%
   51     866.6     8.303    0.9%
   53     922.3     7.216    0.7%
   55     959.5     2.582    0.2%
   57     974.6     2.165    0.2%
   59     990.3      8.81    0.8%
   61      1038     9.962    0.9%
   63      1064     2.678    0.2%
   65      1103     8.971    0.8%
   67      1140     2.329    0.2%
   69      1166     6.857    0.5%
   71      1212     8.285    0.6%
   73      1220     8.122    0.6%
   75      1244     2.392    0.1%
   77      1309     2.837    0.2%
   79      1311     5.674    0.4%
   81      1349      9.42    0.6%
   83      1380     5.933    0.4%
   85      1420     10.75    0.7%
   87      1438     3.072    0.2%
   89      1504     3.282    0.2%
   91      1519     7.324    0.4%
   93      1552     12.96    0.8%
   95      1617        13    0.8%
   97      1655     11.99    0.7%
   99      1641     12.78    0.7%
  101      1687     12.51    0.7%
  103      1746     12.89    0.7%
  105      1788     12.78    0.7%
  107      1787     12.93    0.7%
  109      1823     11.38    0.6%
  111      1899     11.75    0.6%
  113      1922     5.912    0.3%
  115      1933     10.91    0.5%
  117      1960     13.19    0.6%
  119      2004     11.86    0.5%
  121      2059     12.59    0.6%
  123      2100     10.93    0.5%
  125      2117     21.17    1.0%
  127      2148     10.46    0.4%

Quality and confidence:
param     error
k         0.017

Model:
Time ~=    23.49
    + k    16.63
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    41.66
    + n    5.847
              µs

Reads = 7 + (1 * n)
Writes = 2 + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     46.74     0.175    0.3%
    2     53.25     0.189    0.3%
    3     58.85     0.147    0.2%
    4     64.72     0.107    0.1%
    5      71.1     0.162    0.2%
    6     76.89     0.254    0.3%
    7     83.04     0.146    0.1%
    8     89.33     0.314    0.3%
    9     95.79     0.206    0.2%
   10     100.2     0.467    0.4%
   11     105.7      0.37    0.3%
   12     111.8     0.228    0.2%
   13     117.9     0.302    0.2%
   14     123.5     0.306    0.2%
   15     128.2     0.186    0.1%
   16     134.6     0.316    0.2%

Quality and confidence:
param     error
n         0.011

Model:
Time ~=    41.73
    + n     5.84
              µs

Reads = 7 + (1 * n)
Writes = 2 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     17.9
              µs

Reads = 3
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     17.9
              µs

Reads = 3
Writes = 0
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.76
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.76
              µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    28.38
              µs

Reads = 3
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    28.38
              µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.537
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.537
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.749
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.749
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.834
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.834
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=      2.8
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=      2.8
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    3.434
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
    0     2.873     0.034    1.1%
   20     4.431     0.025    0.5%
   40     5.646     0.031    0.5%
   60     6.804     0.041    0.6%
   80     7.977     0.047    0.5%
  100     9.106     0.031    0.3%
  120     10.27     0.053    0.5%
  140     11.33     0.044    0.3%
  160     12.48     0.033    0.2%
  180     13.73     0.067    0.4%
  200     14.72      0.06    0.4%
  220     15.95      0.03    0.1%
  240     17.08     0.023    0.1%
  260     18.14     0.032    0.1%
  280     19.24     0.183    0.9%
  300     20.37     0.026    0.1%
  320     21.65     0.056    0.2%
  340     22.19      0.04    0.1%
  360     23.37     0.169    0.7%
  380     25.02     0.052    0.2%
  400     25.65     0.173    0.6%
  420     26.81     0.067    0.2%
  440     27.96     0.041    0.1%
  460     29.02     0.041    0.1%
  480     30.13      0.04    0.1%
  500     31.24     0.195    0.6%
  520     33.13     0.649    1.9%
  540     33.47     0.061    0.1%
  560     34.83     0.078    0.2%
  580     35.55     0.062    0.1%
  600     37.08     0.374    1.0%
  620     37.96     0.099    0.2%
  640     39.04     0.063    0.1%
  660     41.02     0.043    0.1%
  680     41.36      0.08    0.1%
  700     43.44     0.097    0.2%
  720     43.67     0.034    0.0%
  740     44.87     0.038    0.0%
  760     46.01     0.056    0.1%
  780     47.05     0.035    0.0%
  800      48.2      0.05    0.1%
  820     49.36     0.086    0.1%
  840     50.43     0.057    0.1%
  860     51.59     0.071    0.1%
  880      52.7     0.085    0.1%
  900     53.97     0.097    0.1%
  920     54.92     0.076    0.1%
  940     56.03     0.041    0.0%
  960     57.33     0.051    0.0%
  980     58.45     0.064    0.1%
 1000     59.59     0.062    0.1%

Quality and confidence:
param     error
v             0

Model:
Time ~=    3.429
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    62.09
    + s    2.444
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     57.06     0.104    0.1%
    2     67.08     0.166    0.2%
    4     70.63      0.17    0.2%
    6     76.61     0.359    0.4%
    8     81.47     0.194    0.2%
   10      86.9     1.001    1.1%
   12     90.75     0.209    0.2%
   14     95.99     0.173    0.1%
   16     101.3     0.074    0.0%
   18     106.1     0.159    0.1%
   20     110.9     0.196    0.1%
   22     115.8     0.209    0.1%
   24     121.1      0.27    0.2%
   26     127.5     1.125    0.8%
   28     130.2      0.31    0.2%
   30       135     0.496    0.3%
   32     140.7     0.384    0.2%
   34     145.5     0.199    0.1%
   36     150.7     0.382    0.2%
   38     155.5     0.309    0.1%
   40     160.1     0.164    0.1%
   42     165.6     0.204    0.1%
   44     169.7     0.537    0.3%
   46     175.2     0.225    0.1%
   48     179.2     0.364    0.2%
   50     184.7     1.293    0.6%
   52     188.2     0.401    0.2%
   54     193.9     0.485    0.2%
   56     198.8     0.367    0.1%
   58     204.2     0.413    0.2%
   60     207.6     0.619    0.2%
   62       216     5.062    2.3%
   64     217.7     0.616    0.2%
   66     223.3     0.798    0.3%
   68     230.3     6.205    2.6%
   70     234.6     1.493    0.6%
   72     237.7     0.505    0.2%
   74     243.3     0.546    0.2%
   76       249     2.561    1.0%
   78     252.8      0.46    0.1%
   80     259.6     3.072    1.1%
   82     261.9       0.5    0.1%
   84     266.6     0.294    0.1%
   86     272.1     1.938    0.7%
   88       277      0.35    0.1%
   90     280.7     0.537    0.1%
   92       288     0.607    0.2%
   94       292      0.45    0.1%
   96     296.8     1.084    0.3%
   98     300.2     0.706    0.2%
  100     306.6     0.846    0.2%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    61.79
    + s    2.451
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     3803
    + s    20.01
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1       245     0.265    0.1%
   20     999.3     15.14    1.5%
   39      1728     13.72    0.7%
   58      2438     14.62    0.5%
   77      3149     10.23    0.3%
   96      3823     14.73    0.3%
  115      4502     16.84    0.3%
  134      5156     14.56    0.2%
  153      5812     11.92    0.2%
  172      6428     8.973    0.1%
  191      7047     26.29    0.3%
  210      7636     18.11    0.2%
  229      8244     9.003    0.1%
  248      8796     14.62    0.1%
  267      9355     15.23    0.1%
  286      9905      22.4    0.2%
  305     10430     30.25    0.2%
  324     10930     19.33    0.1%
  343     11430     30.34    0.2%
  362     11950     29.79    0.2%
  381     12400     30.41    0.2%
  400     12860     13.98    0.1%
  419     13300     23.02    0.1%
  438     13740     21.45    0.1%
  457     14130      27.3    0.1%
  476     14540     46.96    0.3%
  495     14930     14.68    0.0%
  514     15310     35.26    0.2%
  533     15690     19.71    0.1%
  552     16010     26.38    0.1%
  571     16330     38.57    0.2%
  590     16630     22.28    0.1%
  609     16970     23.81    0.1%
  628     17230     28.36    0.1%
  647     17530     38.35    0.2%
  666     17810     45.78    0.2%
  685     18030     37.11    0.2%
  704     18250     32.23    0.1%
  723     18480     24.02    0.1%
  742     18680     22.55    0.1%
  761     18870     38.43    0.2%
  780     19010     15.31    0.0%
  799     19200     26.75    0.1%
  818     19330     21.87    0.1%
  837     19460     19.15    0.0%
  856     19600     40.13    0.2%
  875     19670     14.89    0.0%
  894     19790     36.61    0.1%
  913     19850     35.31    0.1%
  932     19910     35.47    0.1%
  951     19940     31.28    0.1%
  970     19950     23.65    0.1%
  989     19940     18.01    0.0%

Quality and confidence:
param     error
s         0.223

Model:
Time ~=     3383
    + s    19.98
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    124.2
    + n    47.55
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     163.4     0.548    0.3%
    6     403.6     1.068    0.2%
   11     644.1     8.517    1.3%
   16     884.7     8.965    1.0%
   21      1120     10.99    0.9%
   26      1413     14.88    1.0%
   31      1587     11.52    0.7%
   36      1845     13.29    0.7%
   41      2089     10.57    0.5%
   46      2299     8.622    0.3%
   51      2548     13.98    0.5%
   56      2808     10.62    0.3%
   61      3015     9.594    0.3%
   66      3267     15.16    0.4%
   71      3509      19.6    0.5%
   76      3756     12.72    0.3%
   81      3985     15.73    0.3%
   86      4194     7.794    0.1%
   91      4455     18.24    0.4%
   96      4705     16.11    0.3%
  101      4925     14.79    0.3%
  106      5145     16.21    0.3%
  111      5395     9.292    0.1%
  116      5615     12.88    0.2%
  121      5916     15.65    0.2%
  126      6084     28.33    0.4%
  131      6313        18    0.2%
  136      6565     20.37    0.3%
  141      6800     14.65    0.2%
  146      7058     14.04    0.1%
  151      7288     18.17    0.2%
  156      7519        18    0.2%
  161      7739     17.49    0.2%
  166      7997     14.11    0.1%
  171      8296     12.25    0.1%
  176      8509     29.76    0.3%
  181      8761      16.3    0.1%
  186      9034     23.79    0.2%
  191      9323     21.83    0.2%
  196      9442     15.81    0.1%
  201      9724     28.43    0.2%
  206      9996     18.03    0.1%
  211     10140     17.08    0.1%
  216     10430     20.93    0.2%
  221     10620      20.9    0.1%
  226     10890     27.79    0.2%
  231     11160      35.5    0.3%
  236     11370     40.69    0.3%
  241     11490     10.52    0.0%
  246     11750      21.1    0.1%
  251     12050      24.7    0.2%
  256     12270     25.78    0.2%

Quality and confidence:
param     error
n         0.023

Model:
Time ~=    124.7
    + n    47.57
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    161.2
    + n    61.28
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     214.4     0.594    0.2%
    6     524.4     6.254    1.1%
   11     827.4     7.774    0.9%
   16      1137        10    0.8%
   21      1453     6.784    0.4%
   26      1768     13.87    0.7%
   31      2047     13.33    0.6%
   36      2372     6.026    0.2%
   41      2679     9.806    0.3%
   46      2964     9.092    0.3%
   51      3279     9.739    0.2%
   56      3627     10.61    0.2%
   61      3896     15.84    0.4%
   66      4172     12.99    0.3%
   71      4488     15.79    0.3%
   76      4818     17.27    0.3%
   81      5161     43.67    0.8%
   86      5430     7.218    0.1%
   91      5721     21.13    0.3%
   96      6065     11.56    0.1%
  101      6368     32.84    0.5%
  106      6689     14.14    0.2%
  111      6966     9.282    0.1%
  116      7241     14.75    0.2%
  121      7574     9.224    0.1%
  126      7868     12.17    0.1%
  131      8193     22.94    0.2%
  136      8530     20.79    0.2%
  141      8864     17.16    0.1%
  146      9099     28.01    0.3%
  151      9467     22.47    0.2%
  156      9717     12.27    0.1%
  161     10030     22.31    0.2%
  166     10250     22.24    0.2%
  171     10600     22.23    0.2%
  176     10900     27.56    0.2%
  181     11290     28.73    0.2%
  186     11600     24.45    0.2%
  191     11830     12.88    0.1%
  196     12230     26.56    0.2%
  201     12460     26.87    0.2%
  206     12770     30.65    0.2%
  211     13140     42.12    0.3%
  216     13490     31.47    0.2%
  221     13710     37.95    0.2%
  226     13980     33.46    0.2%
  231     14370        40    0.2%
  236     14620     50.37    0.3%
  241     14860     30.41    0.2%
  246     15310     36.66    0.2%
  251     15500     34.21    0.2%
  256     15790     27.63    0.1%

Quality and confidence:
param     error
n         0.024

Model:
Time ~=    160.2
    + n    61.32
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    49.76
    + l    0.079
              µs

Reads = 3 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    l   mean µs  sigma µs       %
    1     48.64     0.125    0.2%
    2      49.2     0.126    0.2%
    3     48.87     0.091    0.1%
    4     49.32     0.295    0.5%
    5     50.58     0.177    0.3%
    6     50.55     0.162    0.3%
    7     50.42     0.119    0.2%
    8     50.37      0.15    0.2%
    9     50.78     0.096    0.1%
   10      50.3     0.567    1.1%
   11      51.1     0.104    0.2%
   12     51.27     0.146    0.2%
   13     51.19     0.083    0.1%
   14      50.9     0.144    0.2%
   15     50.22     0.128    0.2%
   16     50.48     0.502    0.9%
   17     51.88     0.184    0.3%
   18     51.39     0.158    0.3%
   19     50.71     0.312    0.6%
   20     51.57     0.134    0.2%
   21     50.51      0.17    0.3%
   22     51.44      0.37    0.7%
   23     51.95     0.108    0.2%
   24     51.71      0.12    0.2%
   25     51.69     0.115    0.2%
   26     51.81     0.193    0.3%
   27     50.47     0.117    0.2%
   28     51.31     0.332    0.6%
   29     51.79     0.273    0.5%
   30     50.92     0.295    0.5%
   31      52.2     0.207    0.3%
   32     52.45     0.382    0.7%

Quality and confidence:
param     error
l         0.003

Model:
Time ~=    49.59
    + l    0.078
              µs

Reads = 3 + (0 * l)
Writes = 3 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + e    35.05
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    e   mean µs  sigma µs       %
    1     43.45     0.076    0.1%
    2     71.75     0.195    0.2%
    3     95.54     0.261    0.2%
    4     124.4     0.867    0.6%
    5     149.8     0.374    0.2%
    6     175.2     1.067    0.6%
    7     202.8     0.459    0.2%
    8       228     0.443    0.1%
    9     253.5     0.411    0.1%
   10     283.9     0.454    0.1%
   11       311      0.45    0.1%
   12     337.9     0.567    0.1%
   13     366.6     0.574    0.1%
   14     395.4     0.566    0.1%
   15     425.7     1.095    0.2%
   16     452.8     0.779    0.1%
   17     482.2      0.71    0.1%
   18     511.2     0.797    0.1%
   19     541.5     0.864    0.1%
   20       569     1.058    0.1%
   21     602.9     6.622    1.0%
   22     630.4      1.54    0.2%
   23     663.2     0.714    0.1%
   24     694.1      3.06    0.4%
   25     732.4     9.832    1.3%
   26     756.9     1.046    0.1%
   27     797.9     7.288    0.9%
   28     828.8     9.251    1.1%
   29     861.5     11.16    1.2%
   30     898.2     13.22    1.4%
   31     928.6     12.64    1.3%
   32     958.8     13.09    1.3%
   33     981.3     9.941    1.0%
   34      1011     3.625    0.3%
   35      1051     11.17    1.0%
   36      1074     3.942    0.3%
   37      1115     13.72    1.2%
   38      1141      10.1    0.8%
   39      1165     9.955    0.8%
   40      1193     7.543    0.6%
   41      1239     11.63    0.9%
   42      1273     9.302    0.7%
   43      1307     15.64    1.1%
   44      1335     8.224    0.6%
   45      1376     4.305    0.3%
   46      1410      11.7    0.8%
   47      1461     12.87    0.8%
   48      1483     7.075    0.4%
   49      1521     12.21    0.8%
   50      1538     3.423    0.2%
   51      1581     4.712    0.2%
   52      1663     6.694    0.4%
   53      1674     16.69    0.9%
   54      1695     16.56    0.9%
   55      1738     8.793    0.5%
   56      1783     16.86    0.9%
   57      1799     9.383    0.5%
   58      1844     12.79    0.6%
   59      1877     12.86    0.6%
   60      1915     15.81    0.8%
   61      1958     14.13    0.7%
   62      1995     11.81    0.5%
   63      2024     13.53    0.6%
   64      2055     10.43    0.5%
   65      2104     14.86    0.7%
   66      2149     12.55    0.5%
   67      2184     18.39    0.8%
   68      2217     13.56    0.6%
   69      2255     12.26    0.5%
   70      2283     12.65    0.5%
   71      2335     13.58    0.5%
   72      2367     12.56    0.5%
   73      2437     12.67    0.5%
   74      2438      12.5    0.5%
   75      2496     13.84    0.5%
   76      2523     12.47    0.4%
   77      2550     12.67    0.4%
   78      2616     11.99    0.4%
   79      2658     10.41    0.3%
   80      2686     17.65    0.6%
   81      2708     8.885    0.3%
   82      2744     7.736    0.2%
   83      2807     10.66    0.3%
   84      2865     6.841    0.2%
   85      2869     10.42    0.3%
   86      2896     11.94    0.4%
   87      2984        16    0.5%
   88      3016     18.45    0.6%
   89      3076     8.951    0.2%
   90      3070     11.23    0.3%
   91      3142     12.38    0.3%
   92      3201     13.09    0.4%
   93      3276     23.63    0.7%
   94      3250     7.221    0.2%
   95      3317      11.6    0.3%
   96      3331     11.58    0.3%
   97      3378     5.266    0.1%
   98      3428     10.74    0.3%
   99      3504     13.14    0.3%
  100      3501     11.97    0.3%

Quality and confidence:
param     error
e         0.071

Model:
Time ~=        0
    + e    35.23
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    72.82
    + s    2.443
              µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1     73.52     0.186    0.2%
    2     76.34     0.256    0.3%
    3      78.8     0.091    0.1%
    4     81.94     0.181    0.2%
    5     84.64     0.154    0.1%
    6     86.59     0.183    0.2%
    7     89.67     0.193    0.2%
    8        92     0.187    0.2%
    9     94.27     0.256    0.2%
   10     96.81     0.225    0.2%
   11     99.43     0.171    0.1%
   12     102.2     0.236    0.2%
   13     104.9     0.175    0.1%
   14     107.4     0.237    0.2%
   15     109.8     0.206    0.1%
   16     112.1     0.138    0.1%
   17     114.5     0.171    0.1%
   18     117.2     0.206    0.1%
   19     119.4     0.141    0.1%
   20     121.8     0.226    0.1%
   21     125.2     0.243    0.1%
   22     127.2     0.237    0.1%
   23     129.4     0.264    0.2%
   24     131.9     0.411    0.3%
   25     134.9     0.288    0.2%
   26       136     0.177    0.1%
   27     139.2     0.261    0.1%
   28     140.7     0.333    0.2%
   29     142.9     0.298    0.2%
   30     146.3     0.376    0.2%
   31     148.5     0.223    0.1%
   32     150.5     0.503    0.3%
   33     153.4     0.449    0.2%
   34     156.2     0.204    0.1%
   35     159.2     0.396    0.2%
   36       161      0.16    0.0%
   37     162.9     0.564    0.3%
   38     166.4     0.366    0.2%
   39     169.5     0.225    0.1%
   40     171.6     0.516    0.3%
   41     173.6     0.337    0.1%
   42     176.3     0.316    0.1%
   43     178.4     0.346    0.1%
   44     180.5     0.257    0.1%
   45     183.4     0.526    0.2%
   46     185.3     0.426    0.2%
   47     187.4     0.342    0.1%
   48     190.3     0.466    0.2%
   49     192.4     0.441    0.2%
   50     194.2      0.35    0.1%
   51     195.7     0.318    0.1%
   52     199.2     0.331    0.1%
   53     202.2     1.165    0.5%
   54       204     0.469    0.2%
   55     207.4      0.36    0.1%
   56     209.3     0.592    0.2%
   57     212.4     0.647    0.3%
   58     214.5     0.396    0.1%
   59     217.3     0.295    0.1%
   60     218.2     0.285    0.1%
   61     222.6     0.476    0.2%
   62     224.9      0.54    0.2%
   63     226.8      0.37    0.1%
   64     228.5     0.599    0.2%
   65     231.6     0.491    0.2%
   66     233.7     0.353    0.1%
   67     236.6     0.477    0.2%
   68     237.7     0.468    0.1%
   69     240.7     0.385    0.1%
   70     243.2     0.431    0.1%
   71     245.7     0.624    0.2%
   72     246.8     0.473    0.1%
   73     250.3     0.612    0.2%
   74     253.4     0.645    0.2%
   75     255.3     0.784    0.3%
   76     258.5      0.74    0.2%
   77     259.8     1.498    0.5%
   78     263.3     0.475    0.1%
   79     265.3     0.675    0.2%
   80       267     0.399    0.1%
   81     269.2     0.718    0.2%
   82       272     0.523    0.1%
   83     275.3     0.541    0.1%
   84       280     8.487    3.0%
   85     280.2     0.836    0.2%
   86     288.7     13.04    4.5%
   87     285.6     0.739    0.2%
   88     287.3     0.338    0.1%
   89     291.9     4.315    1.4%
   90     291.3     0.771    0.2%
   91     295.3     0.695    0.2%
   92     298.6     0.674    0.2%
   93     300.5     0.704    0.2%
   94     301.7     0.806    0.2%
   95     304.7     0.718    0.2%
   96     307.7     0.464    0.1%
   97     313.7     5.603    1.7%
   98     315.3     2.381    0.7%
   99     316.4     0.473    0.1%
  100     320.3     4.815    1.5%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    72.48
    + s    2.452
              µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    285.9
    + n    48.13
              µs

Reads = 9 + (3 * v) + (3 * n)
Writes = 3 + (3 * v) + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
    1   100      2755     10.22    0.3%
    2   100      3018     14.41    0.4%
    3   100      3268     20.22    0.6%
    4   100      3476     13.84    0.3%
    5   100      3794     13.93    0.3%
    6   100      4027     14.77    0.3%
    7   100      4375     18.63    0.4%
    8   100      4603     13.09    0.2%
    9   100      5036     20.74    0.4%
   10     1     617.6     6.963    1.1%
   10     2     671.9     9.582    1.4%
   10     3     713.4     6.177    0.8%
   10     4     761.7     7.859    1.0%
   10     5     813.3     10.45    1.2%
   10     6     857.1      11.4    1.3%
   10     7     916.7     14.67    1.6%
   10     8     962.4     11.92    1.2%
   10     9      1003     13.12    1.3%
   10    10      1057     11.85    1.1%
   10    11      1099     10.04    0.9%
   10    12      1148     13.26    1.1%
   10    13      1213     13.74    1.1%
   10    14      1260     16.31    1.2%
   10    15      1320     12.01    0.9%
   10    16      1354     14.47    1.0%
   10    17      1388     13.71    0.9%
   10    18      1438     13.95    0.9%
   10    19      1471     17.46    1.1%
   10    20      1524     15.69    1.0%
   10    21      1551     11.24    0.7%
   10    22      1613     12.91    0.8%
   10    23      1669     9.758    0.5%
   10    24      1738     10.75    0.6%
   10    25      1755     9.028    0.5%
   10    26      1819     11.66    0.6%
   10    27      1859     14.08    0.7%
   10    28      1928     11.65    0.6%
   10    29      1986     9.545    0.4%
   10    30      2001     12.79    0.6%
   10    31      2055     11.71    0.5%
   10    32      2112     14.08    0.6%
   10    33      2182     9.354    0.4%
   10    34      2209     9.749    0.4%
   10    35      2262     15.36    0.6%
   10    36      2309     10.17    0.4%
   10    37      2338     13.54    0.5%
   10    38      2424     13.43    0.5%
   10    39      2474     8.623    0.3%
   10    40      2514     8.227    0.3%
   10    41      2588      12.9    0.4%
   10    42      2604     11.66    0.4%
   10    43      2664     12.39    0.4%
   10    44      2722     10.93    0.4%
   10    45      2773     15.74    0.5%
   10    46      2814     12.28    0.4%
   10    47      2848     10.27    0.3%
   10    48      2935     16.93    0.5%
   10    49      2942     13.35    0.4%
   10    50      3019     22.38    0.7%
   10    51      3048     13.37    0.4%
   10    52      3119     15.64    0.5%
   10    53      3173     11.13    0.3%
   10    54      3166     19.42    0.6%
   10    55      3280     17.67    0.5%
   10    56      3310     20.63    0.6%
   10    57      3339     13.02    0.3%
   10    58      3417     16.65    0.4%
   10    59      3471     8.246    0.2%
   10    60      3481     13.66    0.3%
   10    61      3554     25.16    0.7%
   10    62      3618     13.43    0.3%
   10    63      3656     12.08    0.3%
   10    64      3705     10.23    0.2%
   10    65      3741     20.16    0.5%
   10    66      3802     14.36    0.3%
   10    67      3825      17.8    0.4%
   10    68      3888     13.74    0.3%
   10    69      3905     12.88    0.3%
   10    70      3954      7.53    0.1%
   10    71      3986     16.18    0.4%
   10    72      4082     15.29    0.3%
   10    73      4111     25.05    0.6%
   10    74      4116     11.37    0.2%
   10    75      4172     9.341    0.2%
   10    76      4222     15.62    0.3%
   10    77      4290     16.16    0.3%
   10    78      4308     8.365    0.1%
   10    79      4383     18.25    0.4%
   10    80      4445     19.25    0.4%
   10    81      4486      15.8    0.3%
   10    82      4541     11.74    0.2%
   10    83      4604     25.63    0.5%
   10    84      4596     14.11    0.3%
   10    85      4626      11.8    0.2%
   10    86      4664     10.62    0.2%
   10    87      4757     17.42    0.3%
   10    88      4806     14.28    0.2%
   10    89      4828     22.51    0.4%
   10    90      4907     15.68    0.3%
   10    91      4927     21.76    0.4%
   10    92      4976     16.84    0.3%
   10    93      5007     13.68    0.2%
   10    94      5068     11.53    0.2%
   10    95      5146     16.01    0.3%
   10    96      5224     21.84    0.4%
   10    97      5271     23.45    0.4%
   10    98      5279     12.96    0.2%
   10    99      5336     8.223    0.1%
   10   100      5322     27.88    0.5%

Quality and confidence:
param     error
v         0.856
n         0.043

Model:
Time ~=        0
    + v      305
    + n    47.89
              µs

Reads = 9 + (3 * v) + (3 * n)
Writes = 3 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    25.04
    + n    28.58
    + s    4.745
              µs

Reads = 3 + (3 * v) + (3 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n     s   mean µs  sigma µs       %
  500  1000    20     41060     171.7    0.4%
  510  1000    20     40730     145.2    0.3%
  520  1000    20     41350     222.7    0.5%
  530  1000    20     41740     154.6    0.3%
  540  1000    20     42080     188.6    0.4%
  550  1000    20     42000     224.9    0.5%
  560  1000    20     42440     113.1    0.2%
  570  1000    20     42420     194.6    0.4%
  580  1000    20     42950     210.9    0.4%
  590  1000    20     42950     198.4    0.4%
  600  1000    20     42930     245.4    0.5%
  610  1000    20     44120     164.4    0.3%
  620  1000    20     43890     149.4    0.3%
  630  1000    20     44300     210.5    0.4%
  640  1000    20     44460     153.4    0.3%
  650  1000    20     44080     154.6    0.3%
  660  1000    20     45580     154.6    0.3%
  670  1000    20     45780     132.7    0.2%
  680  1000    20     45370       185    0.4%
  690  1000    20     46070     196.3    0.4%
  700  1000    20     45990     165.2    0.3%
  710  1000    20     45780     136.6    0.2%
  720  1000    20     46150     166.3    0.3%
  730  1000    20     46740     174.7    0.3%
  740  1000    20     46380     172.2    0.3%
  750  1000    20     46670     149.8    0.3%
  760  1000    20     47850     191.6    0.4%
  770  1000    20     47890     168.2    0.3%
  780  1000    20     47610     184.1    0.3%
  790  1000    20     48130     147.4    0.3%
  800  1000    20     48620     153.7    0.3%
  810  1000    20     48240       109    0.2%
  820  1000    20     49120     128.9    0.2%
  830  1000    20     48890     133.2    0.2%
  840  1000    20     48930     155.1    0.3%
  850  1000    20     49230       130    0.2%
  860  1000    20     49590     191.7    0.3%
  870  1000    20     50860     185.2    0.3%
  880  1000    20     51070     245.6    0.4%
  890  1000    20     51110     212.8    0.4%
  900  1000    20     50580     281.2    0.5%
  910  1000    20     50760       160    0.3%
  920  1000    20     51510     309.1    0.6%
  930  1000    20     50960     112.6    0.2%
  940  1000    20     51610     160.4    0.3%
  950  1000    20     52760     200.3    0.3%
  960  1000    20     52790     159.5    0.3%
  970  1000    20     52650     140.6    0.2%
  980  1000    20     52590     147.4    0.2%
  990  1000    20     53570     219.7    0.4%
 1000   500    20     39040     123.2    0.3%
 1000   510    20     39350     169.9    0.4%
 1000   520    20     39830     154.7    0.3%
 1000   530    20     40470     113.4    0.2%
 1000   540    20     40200     88.93    0.2%
 1000   550    20     41270       122    0.2%
 1000   560    20     41860     116.3    0.2%
 1000   570    20     42180     128.9    0.3%
 1000   580    20     41720     144.8    0.3%
 1000   590    20     42560     199.9    0.4%
 1000   600    20     41620     126.9    0.3%
 1000   610    20     42530     204.5    0.4%
 1000   620    20     42690     134.4    0.3%
 1000   630    20     42850     195.7    0.4%
 1000   640    20     43230     144.9    0.3%
 1000   650    20     44060       153    0.3%
 1000   660    20     44040     128.5    0.2%
 1000   670    20     44460     151.6    0.3%
 1000   680    20     44700       170    0.3%
 1000   690    20     45060     177.2    0.3%
 1000   700    20     45160     236.2    0.5%
 1000   710    20     45290     283.8    0.6%
 1000   720    20     45380     139.8    0.3%
 1000   730    20     45950     138.9    0.3%
 1000   740    20     46790     182.7    0.3%
 1000   750    20     46610     240.1    0.5%
 1000   760    20     46650     150.6    0.3%
 1000   770    20     46900     122.5    0.2%
 1000   780    20     48160     297.5    0.6%
 1000   790    20     46810     100.9    0.2%
 1000   800    20     48570     257.3    0.5%
 1000   810    20     47690     136.2    0.2%
 1000   820    20     49410     205.8    0.4%
 1000   830    20     49130     132.7    0.2%
 1000   840    20     49100     145.8    0.2%
 1000   850    20     49310     186.5    0.3%
 1000   860    20     50450     339.6    0.6%
 1000   870    20     50120     234.6    0.4%
 1000   880    20     50860       212    0.4%
 1000   890    20     50930     233.9    0.4%
 1000   900    20     51340     220.4    0.4%
 1000   910    20     51270     253.9    0.4%
 1000   920    20     51810     93.93    0.1%
 1000   930    20     51670     116.1    0.2%
 1000   940    20     51720     353.3    0.6%
 1000   950    20     52140     186.3    0.3%
 1000   960    20     52310     159.3    0.3%
 1000   970    20     53160     187.4    0.3%
 1000   980    20     53490     210.1    0.3%
 1000   990    20     53170       119    0.2%
 1000  1000     1     52700     152.1    0.2%
 1000  1000     2     53150     125.8    0.2%
 1000  1000     3     53880     169.9    0.3%
 1000  1000     4     53080     146.7    0.2%
 1000  1000     5     53730     179.5    0.3%
 1000  1000     6     54070     270.5    0.5%
 1000  1000     7     53480       222    0.4%
 1000  1000     8     53130     311.9    0.5%
 1000  1000     9     52550     276.4    0.5%
 1000  1000    10     53070       171    0.3%
 1000  1000    11     53650     274.5    0.5%
 1000  1000    12     53750     251.5    0.4%
 1000  1000    13     53640     158.1    0.2%
 1000  1000    14     53480       165    0.3%
 1000  1000    15     53290     209.9    0.3%
 1000  1000    16     53530     218.8    0.4%
 1000  1000    17     53310     231.8    0.4%
 1000  1000    18     53340       235    0.4%
 1000  1000    19     53650     164.8    0.3%
 1000  1000    20     53320     194.9    0.3%

Quality and confidence:
param     error
v         0.098
n         0.098
s         3.346

Model:
Time ~=        0
    + v    25.61
    + n    28.06
    + s    18.12
              µs

Reads = 3 + (3 * v) + (3 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Pallet: "pallet_staking", Extrinsic: "get_npos_targets", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    50.86
    + v    11.22
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
  500      5703     16.79    0.2%
  510      5727     23.61    0.4%
  520      5870     39.26    0.6%
  530      5966     39.02    0.6%
  540      6005     47.01    0.7%
  550      6133     24.17    0.3%
  560      6385      34.3    0.5%
  570      6574      27.6    0.4%
  580      6540     40.54    0.6%
  590      6717     31.01    0.4%
  600      6819     28.82    0.4%
  610      6794     27.86    0.4%
  620      7013     24.91    0.3%
  630      7152     52.94    0.7%
  640      7257     25.05    0.3%
  650      7339     18.33    0.2%
  660      7447     58.76    0.7%
  670      7595     61.21    0.8%
  680      7756      37.5    0.4%
  690      7858     32.78    0.4%
  700      8005     25.71    0.3%
  710      8028     28.69    0.3%
  720      8075     46.27    0.5%
  730      8459     47.88    0.5%
  740      8507     27.07    0.3%
  750      8386     31.64    0.3%
  760      8493     24.03    0.2%
  770      8601     28.92    0.3%
  780      8660     68.96    0.7%
  790      8786     63.36    0.7%
  800      9197     68.03    0.7%
  810      9100     92.52    1.0%
  820      9079     51.26    0.5%
  830      9321     39.94    0.4%
  840      9612     46.95    0.4%
  850      9648      78.6    0.8%
  860      9635      35.1    0.3%
  870      9715     53.27    0.5%
  880      9673     46.42    0.4%
  890     10040     58.89    0.5%
  900     10100     43.61    0.4%
  910     10250     35.75    0.3%
  920     10330      59.7    0.5%
  930     10450     90.73    0.8%
  940     10740     30.44    0.2%
  950     10800      65.3    0.6%
  960     11010     71.96    0.6%
  970     11170     51.96    0.4%
  980     11050     50.58    0.4%
  990     11100     37.74    0.3%
 1000     11190     75.79    0.6%

Quality and confidence:
param     error
v         0.033

Model:
Time ~=    30.42
    + v    11.25
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "set_staking_limits", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    6.486
              µs

Reads = 0
Writes = 5
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    6.486
              µs

Reads = 0
Writes = 5
Pallet: "pallet_staking", Extrinsic: "chill_other", Lowest values: [], Highest values: [], Steps: 50, Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    58.22
              µs

Reads = 7
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    58.22
              µs

Reads = 7
Writes = 2

…path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic=* --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/election-provider-multi-phase/src/weights.rs --template=./.maintain/frame-weight-template.hbs

… kiz-remove-election-weight-api

…path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic=* --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

…h/substrate into kiz-remove-election-weight-api

kianenigma · 2021-08-19T07:45:49Z

bot merge

ghost · 2021-08-19T07:45:54Z

Trying merge.

* Fix weights * Fix more * update Substrate * fmt Co-authored-by: parity-processbot <>

remove the uselsss weight return type from election provider API

1873a7a

kianenigma mentioned this pull request Aug 24, 2023

Tracking Issue for multi-block election + dedicated election system parachain paritytech/polkadot-sdk#461

Open

19 tasks

Merge branch 'master' of github.com:paritytech/substrate into kiz-rem…

bda35d5

…ove-election-weight-api

kianenigma added the A3-in_progress Pull request is in progress. No review needed at this stage. label Aug 17, 2021

fix everything, should be ready for final benchmark

101b5e8

simplify on_init a bit furhter

b71433c

kianenigma marked this pull request as ready for review August 17, 2021 11:31

kianenigma requested a review from andresilva as a code owner August 17, 2021 11:31

Merge branch 'master' of github.com:paritytech/substrate into kiz-rem…

87c2416

…ove-election-weight-api

kianenigma requested review from emostov and removed request for andresilva August 17, 2021 11:33

kianenigma commented Aug 17, 2021

View reviewed changes

frame/staking/src/pallet/impls.rs Show resolved Hide resolved

kianenigma requested review from shawntabrizi and gui1117 August 17, 2021 11:42

shawntabrizi reviewed Aug 17, 2021

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emostov reviewed Aug 17, 2021

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shawntabrizi reviewed Aug 18, 2021

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shawntabrizi reviewed Aug 18, 2021

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kianenigma added 2 commits August 18, 2021 12:42

remove unwraps

e6eb8b0

Merge branch 'kiz-remove-election-weight-api' of github.com:paritytec…

924b884

…h/substrate into kiz-remove-election-weight-api

shawntabrizi reviewed Aug 18, 2021

View reviewed changes

shawntabrizi approved these changes Aug 18, 2021

View reviewed changes

kianenigma added 4 commits August 18, 2021 13:05

fmt

d3f4cc5

Merge branch 'master' of github.com:paritytech/substrate into kiz-rem…

ca0568b

…ove-election-weight-api

Update lock file

1ce23e6

whitelist block weight

731c4b2

Parity Benchmarking Bot and others added 5 commits August 18, 2021 16:32

Merge branch 'master' of https://github.com/paritytech/substrate into…

faa09b5

… kiz-remove-election-weight-api

fix warning

c1962c8

Merge branch 'kiz-remove-election-weight-api' of github.com:paritytec…

e5a0e12

…h/substrate into kiz-remove-election-weight-api

ghost merged commit 44ee839 into master Aug 19, 2021

ghost deleted the kiz-remove-election-weight-api branch August 19, 2021 07:45

kianenigma added a commit to paritytech/polkadot that referenced this pull request Aug 19, 2021

Companion for paritytech/substrate#9569 (#3662)

f95e308

* Fix weights * Fix more * update Substrate * fmt Co-authored-by: parity-processbot <>

hackfisher mentioned this pull request Nov 16, 2021

Staking Election darwinia-network/darwinia-common#930

Merged

ggwpez pushed a commit to ggwpez/runtimes that referenced this pull request Mar 10, 2023

Companion for paritytech/substrate#9569 (#3662)

e2eb9bc

* Fix weights * Fix more * update Substrate * fmt Co-authored-by: parity-processbot <>

ggwpez pushed a commit to ggwpez/runtimes that referenced this pull request Jul 13, 2023

Companion for paritytech/substrate#9569 (#3662)

ea06162

* Fix weights * Fix more * update Substrate * fmt Co-authored-by: parity-processbot <>

This pull request was closed.

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remove the uselsss weight return type from election provider API #9569

remove the uselsss weight return type from election provider API #9569

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ghost commented Aug 19, 2021

		.saturating_add(RocksDbWeight::get().reads(1 as Weight))
		.saturating_add(RocksDbWeight::get().writes(1 as Weight))

remove the uselsss weight return type from election provider API #9569

remove the uselsss weight return type from election provider API #9569

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