Store election snapshot in a more memory-friendly way. by kianenigma · Pull Request #9275 · paritytech/substrate

kianenigma · 2021-07-05T13:42:46Z

Will change the storage write of snapshot to a more efficient way. This will allow us to use our heap max limit more efficiently and store larger snapshots.

Since this is not a logical change, I will not mark for audit.

kianenigma · 2021-07-05T17:28:13Z

bot merge

ghost · 2021-07-05T17:28:16Z

Waiting for commit status.

kianenigma · 2021-07-05T17:29:32Z

bot merge abort

kianenigma · 2021-07-05T17:29:40Z

bot merge cancel

ghost · 2021-07-05T17:29:41Z

Merge cancelled.

kianenigma · 2021-07-05T17:29:46Z

bot cancel

kianenigma · 2021-07-05T17:29:51Z

bot stop

kianenigma · 2021-07-05T17:30:13Z

\benchmark pallet pallet_election_provider_multi_phase

kianenigma · 2021-07-05T17:30:38Z

/benchmark pallet pallet_election_provider_multi_phase

ghost · 2021-07-05T17:30:39Z

Starting benchmark for branch: kiz-rewrite-snapshot-put (vs master)

Comment will be updated.

kianenigma · 2021-07-06T07:56:34Z

/benchmark pallet pallet_election_provider_multi_phase

ghost · 2021-07-06T07:56:37Z

Starting benchmark for branch: kiz-rewrite-snapshot-put (vs master)

Comment will be updated.

Co-authored-by: Guillaume Thiolliere <gui.thiolliere@gmail.com>

kianenigma · 2021-07-07T08:27:34Z

/benchmark runtime pallet pallet_election_provider_multi_phase

ghost · 2021-07-07T08:27:36Z

Benchmark Runtime Pallet for branch "kiz-rewrite-snapshot-put" with command cargo run --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 ~=    34.61
              µs

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

Model:
Time ~=    34.61
              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 ~=    151.7
              µs

Reads = 10
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    151.7
              µs

Reads = 10
Writes = 4
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_unsigned_with_snapshot", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    150.1
              µs

Reads = 10
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    150.1
              µs

Reads = 10
Writes = 4
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 ~=    61.26
              µs

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

Model:
Time ~=    61.26
              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 ~=    40.57
              µs

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

Model:
Time ~=    40.57
              µs

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

Model:
Time ~=     48.2
              µs

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

Model:
Time ~=     48.2
              µs

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

Model:
Time ~=     6260
              µs

Reads = 6
Writes = 8
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6260
              µs

Reads = 6
Writes = 8
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    80.42
    + c    0.759
              µs

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

Data points distribution:
    c   mean µs  sigma µs       %
    1     80.96     0.245    0.3%
    2     82.24     0.095    0.1%
    3     82.55      0.21    0.2%
    4     83.15     0.121    0.1%
    5     84.57     0.773    0.9%
    6     85.48      0.11    0.1%
    7     85.74     0.183    0.2%
    8     86.71     0.199    0.2%
    9     87.11     0.139    0.1%

Quality and confidence:
param     error
c         0.016

Model:
Time ~=    80.39
    + c    0.778
              µs

Reads = 4 + (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    3.508
    + t     0.24
    + a    11.33
    + d    4.585
              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       %
 4000  1600  3000   800     49040     68.86    0.1%
 4040  1600  3000   800     49110     34.78    0.0%
 4080  1600  3000   800     49370     53.39    0.1%
 4120  1600  3000   800     49470     63.42    0.1%
 4160  1600  3000   800     49670     119.8    0.2%
 4200  1600  3000   800     49780     70.88    0.1%
 4240  1600  3000   800     49980     72.56    0.1%
 4280  1600  3000   800     50070     80.76    0.1%
 4320  1600  3000   800     50210     47.17    0.0%
 4360  1600  3000   800     50240       105    0.2%
 4400  1600  3000   800     50480     89.57    0.1%
 4440  1600  3000   800     50690     139.4    0.2%
 4480  1600  3000   800     50730     86.77    0.1%
 4520  1600  3000   800     50930     88.34    0.1%
 4560  1600  3000   800     51100     152.5    0.2%
 4600  1600  3000   800     51120     70.67    0.1%
 4640  1600  3000   800     51390     102.4    0.1%
 4680  1600  3000   800     51410     136.8    0.2%
 4720  1600  3000   800     51590     42.48    0.0%
 4760  1600  3000   800     51760     129.6    0.2%
 4800  1600  3000   800     51950     73.52    0.1%
 4840  1600  3000   800     52020     106.1    0.2%
 4880  1600  3000   800     52320     125.8    0.2%
 4920  1600  3000   800     52350     85.04    0.1%
 4960  1600  3000   800     52600     110.7    0.2%
 5000  1600  3000   800     52620     110.3    0.2%
 5040  1600  3000   800     52860     91.49    0.1%
 5080  1600  3000   800     52890     140.1    0.2%
 5120  1600  3000   800     53090     98.27    0.1%
 5160  1600  3000   800     53010     80.29    0.1%
 5200  1600  3000   800     53350     66.37    0.1%
 5240  1600  3000   800     53360     82.67    0.1%
 5280  1600  3000   800     53680       132    0.2%
 5320  1600  3000   800     53520     49.85    0.0%
 5360  1600  3000   800     53840      91.6    0.1%
 5400  1600  3000   800     53900     141.2    0.2%
 5440  1600  3000   800     54050      52.6    0.0%
 5480  1600  3000   800     54220     123.5    0.2%
 5520  1600  3000   800     54270     53.26    0.0%
 5560  1600  3000   800     54490       108    0.1%
 5600  1600  3000   800     54670     101.4    0.1%
 5640  1600  3000   800     54760     101.3    0.1%
 5680  1600  3000   800     54920     61.95    0.1%
 5720  1600  3000   800     55230     139.2    0.2%
 5760  1600  3000   800     55310        50    0.0%
 5800  1600  3000   800     55240     55.51    0.1%
 5840  1600  3000   800     55540      51.2    0.0%
 5880  1600  3000   800     55660     94.25    0.1%
 5920  1600  3000   800     55720     44.26    0.0%
 5960  1600  3000   800     55990     253.2    0.4%
 6000  1000  3000   800     56160     93.93    0.1%
 6000  1012  3000   800     56060     57.86    0.1%
 6000  1024  3000   800     56040     80.21    0.1%
 6000  1036  3000   800     56060     54.27    0.0%
 6000  1048  3000   800     55950     75.51    0.1%
 6000  1060  3000   800     56070      98.4    0.1%
 6000  1072  3000   800     56070       136    0.2%
 6000  1084  3000   800     56230     184.6    0.3%
 6000  1096  3000   800     56150       111    0.1%
 6000  1108  3000   800     56000     128.5    0.2%
 6000  1120  3000   800     56100     76.08    0.1%
 6000  1132  3000   800     56050     61.33    0.1%
 6000  1144  3000   800     56070     94.85    0.1%
 6000  1156  3000   800     56160     48.61    0.0%
 6000  1168  3000   800     56070     67.07    0.1%
 6000  1180  3000   800     56060     57.78    0.1%
 6000  1192  3000   800     55970       100    0.1%
 6000  1204  3000   800     56190     130.7    0.2%
 6000  1216  3000   800     56060     61.71    0.1%
 6000  1228  3000   800     56040     60.27    0.1%
 6000  1240  3000   800     56130     137.4    0.2%
 6000  1252  3000   800     56110      42.7    0.0%
 6000  1264  3000   800     56010     64.88    0.1%
 6000  1276  3000   800     56170     55.66    0.0%
 6000  1288  3000   800     55870     49.83    0.0%
 6000  1300  3000   800     56080     124.2    0.2%
 6000  1312  3000   800     56180     95.29    0.1%
 6000  1324  3000   800     56130     31.27    0.0%
 6000  1336  3000   800     55960     98.44    0.1%
 6000  1348  3000   800     56090     39.98    0.0%
 6000  1360  3000   800     56380     124.9    0.2%
 6000  1372  3000   800     56170     57.03    0.1%
 6000  1384  3000   800     55990     62.02    0.1%
 6000  1396  3000   800     56220     96.66    0.1%
 6000  1408  3000   800     56360     171.4    0.3%
 6000  1420  3000   800     56160     129.6    0.2%
 6000  1432  3000   800     56070     68.19    0.1%
 6000  1444  3000   800     56420     56.44    0.1%
 6000  1456  3000   800     56090     58.01    0.1%
 6000  1468  3000   800     56150     98.16    0.1%
 6000  1480  3000   800     56200     125.1    0.2%
 6000  1492  3000   800     56130     77.97    0.1%
 6000  1504  3000   800     56060      87.8    0.1%
 6000  1516  3000   800     56170     89.07    0.1%
 6000  1528  3000   800     56130       103    0.1%
 6000  1540  3000   800     56170     52.95    0.0%
 6000  1552  3000   800     56160     90.03    0.1%
 6000  1564  3000   800     56100     87.73    0.1%
 6000  1576  3000   800     56300     225.7    0.4%
 6000  1588  3000   800     56220       141    0.2%
 6000  1600  1000   800     32920     152.7    0.4%
 6000  1600  1040   800     33580       214    0.6%
 6000  1600  1080   800     33870     188.9    0.5%
 6000  1600  1120   800     34320     81.91    0.2%
 6000  1600  1160   800     34620     51.87    0.1%
 6000  1600  1200   800     35130     92.85    0.2%
 6000  1600  1240   800     35600     108.4    0.3%
 6000  1600  1280   800     36020     78.87    0.2%
 6000  1600  1320   800     36300     48.57    0.1%
 6000  1600  1360   800     36940     91.95    0.2%
 6000  1600  1400   800     37820     106.6    0.2%
 6000  1600  1440   800     38250     77.85    0.2%
 6000  1600  1480   800     38760     46.89    0.1%
 6000  1600  1520   800     39210     89.22    0.2%
 6000  1600  1560   800     39790     114.4    0.2%
 6000  1600  1600   800     40100     61.97    0.1%
 6000  1600  1640   800     40770     164.4    0.4%
 6000  1600  1680   800     41090     139.3    0.3%
 6000  1600  1720   800     41560     177.1    0.4%
 6000  1600  1760   800     41870     61.37    0.1%
 6000  1600  1800   800     42530     113.9    0.2%
 6000  1600  1840   800     42860     122.5    0.2%
 6000  1600  1880   800     43220     42.53    0.0%
 6000  1600  1920   800     43750     87.73    0.2%
 6000  1600  1960   800     44320     215.1    0.4%
 6000  1600  2000   800     44600        83    0.1%
 6000  1600  2040   800     45090     118.4    0.2%
 6000  1600  2080   800     45510      97.1    0.2%
 6000  1600  2120   800     45960     138.9    0.3%
 6000  1600  2160   800     46340     93.07    0.2%
 6000  1600  2200   800     46670     74.65    0.1%
 6000  1600  2240   800     47260     134.2    0.2%
 6000  1600  2280   800     47470     44.13    0.0%
 6000  1600  2320   800     48090       160    0.3%
 6000  1600  2360   800     48300     72.62    0.1%
 6000  1600  2400   800     48720     100.6    0.2%
 6000  1600  2440   800     49220     185.9    0.3%
 6000  1600  2480   800     49530      91.2    0.1%
 6000  1600  2520   800     50080     186.2    0.3%
 6000  1600  2560   800     50400     88.49    0.1%
 6000  1600  2600   800     50770     66.71    0.1%
 6000  1600  2640   800     51400       189    0.3%
 6000  1600  2680   800     51620     60.46    0.1%
 6000  1600  2720   800     52110     112.1    0.2%
 6000  1600  2760   800     52540     60.59    0.1%
 6000  1600  2800   800     53040     174.7    0.3%
 6000  1600  2840   800     53480     76.46    0.1%
 6000  1600  2880   800     54870     58.58    0.1%
 6000  1600  2920   800     55350     51.75    0.0%
 6000  1600  2960   800     55850     145.2    0.2%
 6000  1600  3000   400     54600     49.02    0.0%
 6000  1600  3000   408     54590     65.28    0.1%
 6000  1600  3000   416     54830       161    0.2%
 6000  1600  3000   424     54670     49.15    0.0%
 6000  1600  3000   432     54770     131.6    0.2%
 6000  1600  3000   440     54850     126.6    0.2%
 6000  1600  3000   448     54650     61.73    0.1%
 6000  1600  3000   456     54810      66.1    0.1%
 6000  1600  3000   464     55000     148.8    0.2%
 6000  1600  3000   472     54990      71.2    0.1%
 6000  1600  3000   480     55030     68.46    0.1%
 6000  1600  3000   488     54940     46.93    0.0%
 6000  1600  3000   496     55090     93.04    0.1%
 6000  1600  3000   504     55250      70.5    0.1%
 6000  1600  3000   512     55410     142.3    0.2%
 6000  1600  3000   520     55350     50.44    0.0%
 6000  1600  3000   528     55400     83.84    0.1%
 6000  1600  3000   536     55510     60.14    0.1%
 6000  1600  3000   544     55580     108.5    0.1%
 6000  1600  3000   552     55650     72.06    0.1%
 6000  1600  3000   560     55570     47.46    0.0%
 6000  1600  3000   568     55730     78.91    0.1%
 6000  1600  3000   576     55670     61.78    0.1%
 6000  1600  3000   584     55760     87.84    0.1%
 6000  1600  3000   592     55860     150.5    0.2%
 6000  1600  3000   600     56060     52.04    0.0%
 6000  1600  3000   608     55970     62.57    0.1%
 6000  1600  3000   616     56040     54.25    0.0%
 6000  1600  3000   624     56010     102.7    0.1%
 6000  1600  3000   632     56120     105.2    0.1%
 6000  1600  3000   640     56110     76.98    0.1%
 6000  1600  3000   648     56140     61.43    0.1%
 6000  1600  3000   656     56230     199.9    0.3%
 6000  1600  3000   664     56230     72.83    0.1%
 6000  1600  3000   672     56350     154.5    0.2%
 6000  1600  3000   680     56330     62.42    0.1%
 6000  1600  3000   688     56240      93.9    0.1%
 6000  1600  3000   696     56300     72.49    0.1%
 6000  1600  3000   704     56260     65.52    0.1%
 6000  1600  3000   712     56210     29.17    0.0%
 6000  1600  3000   720     56330     125.3    0.2%
 6000  1600  3000   728     56340     64.24    0.1%
 6000  1600  3000   736     56330       104    0.1%
 6000  1600  3000   744     56250     45.61    0.0%
 6000  1600  3000   752     56330     116.1    0.2%
 6000  1600  3000   760     56350     86.58    0.1%
 6000  1600  3000   768     56240     172.3    0.3%
 6000  1600  3000   776     56230     80.55    0.1%
 6000  1600  3000   784     56350     125.5    0.2%
 6000  1600  3000   792     56410     68.23    0.1%
 6000  1600  3000   800     56230     95.01    0.1%

Quality and confidence:
param     error
v         0.013
t         0.046
a         0.013
d         0.069

Model:
Time ~=        0
    + v    3.563
    + t    0.183
    + a    11.62
    + d    2.927
              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    3.495
    + t    0.327
    + a    9.679
    + d     4.12
              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       %
 4000  1600  3000   800     43490      31.6    0.0%
 4040  1600  3000   800     43560     55.05    0.1%
 4080  1600  3000   800     43690     61.39    0.1%
 4120  1600  3000   800     43880     94.74    0.2%
 4160  1600  3000   800     44030      91.8    0.2%
 4200  1600  3000   800     44030     30.51    0.0%
 4240  1600  3000   800     44170     33.87    0.0%
 4280  1600  3000   800     44370     104.9    0.2%
 4320  1600  3000   800     44610     66.02    0.1%
 4360  1600  3000   800     44690     67.04    0.1%
 4400  1600  3000   800     44780     49.29    0.1%
 4440  1600  3000   800     44860     27.26    0.0%
 4480  1600  3000   800     45200     93.54    0.2%
 4520  1600  3000   800     45270      70.4    0.1%
 4560  1600  3000   800     45330     40.64    0.0%
 4600  1600  3000   800     45430     54.22    0.1%
 4640  1600  3000   800     45700     58.83    0.1%
 4680  1600  3000   800     45810     71.51    0.1%
 4720  1600  3000   800     45910     63.89    0.1%
 4760  1600  3000   800     46060      51.8    0.1%
 4800  1600  3000   800     46290     128.8    0.2%
 4840  1600  3000   800     46320      54.1    0.1%
 4880  1600  3000   800     46500     96.41    0.2%
 4920  1600  3000   800     46560     107.7    0.2%
 4960  1600  3000   800     46830     41.84    0.0%
 5000  1600  3000   800     46840     91.08    0.1%
 5040  1600  3000   800     47080     75.77    0.1%
 5080  1600  3000   800     47160     76.62    0.1%
 5120  1600  3000   800     47440     138.2    0.2%
 5160  1600  3000   800     47410     114.8    0.2%
 5200  1600  3000   800     47720     131.3    0.2%
 5240  1600  3000   800     47720     57.49    0.1%
 5280  1600  3000   800     48040     103.5    0.2%
 5320  1600  3000   800     47890     35.83    0.0%
 5360  1600  3000   800     48160     34.81    0.0%
 5400  1600  3000   800     48230     32.97    0.0%
 5440  1600  3000   800     48530     154.3    0.3%
 5480  1600  3000   800     48550     79.48    0.1%
 5520  1600  3000   800     48570     58.55    0.1%
 5560  1600  3000   800     48880     118.6    0.2%
 5600  1600  3000   800     48920      68.2    0.1%
 5640  1600  3000   800     49030     43.28    0.0%
 5680  1600  3000   800     49170     61.17    0.1%
 5720  1600  3000   800     49370     52.17    0.1%
 5760  1600  3000   800     49680     68.71    0.1%
 5800  1600  3000   800     49680     81.52    0.1%
 5840  1600  3000   800     49970       116    0.2%
 5880  1600  3000   800     50050     143.7    0.2%
 5920  1600  3000   800     50190     48.32    0.0%
 5960  1600  3000   800     50260      55.7    0.1%
 6000  1000  3000   800     50360     78.47    0.1%
 6000  1012  3000   800     50310     102.6    0.2%
 6000  1024  3000   800     50280     133.9    0.2%
 6000  1036  3000   800     50250     75.25    0.1%
 6000  1048  3000   800     50200      47.7    0.0%
 6000  1060  3000   800     50230     63.19    0.1%
 6000  1072  3000   800     50170     80.57    0.1%
 6000  1084  3000   800     50290     123.8    0.2%
 6000  1096  3000   800     50310     43.93    0.0%
 6000  1108  3000   800     50330     140.4    0.2%
 6000  1120  3000   800     50310      65.4    0.1%
 6000  1132  3000   800     50200     74.09    0.1%
 6000  1144  3000   800     50310     193.2    0.3%
 6000  1156  3000   800     50320     121.1    0.2%
 6000  1168  3000   800     50360     104.9    0.2%
 6000  1180  3000   800     50380     122.4    0.2%
 6000  1192  3000   800     50280     128.3    0.2%
 6000  1204  3000   800     50500     152.7    0.3%
 6000  1216  3000   800     50420     147.1    0.2%
 6000  1228  3000   800     50530     205.1    0.4%
 6000  1240  3000   800     50520     166.9    0.3%
 6000  1252  3000   800     50390     76.43    0.1%
 6000  1264  3000   800     50300     57.61    0.1%
 6000  1276  3000   800     50390     82.89    0.1%
 6000  1288  3000   800     50330     90.53    0.1%
 6000  1300  3000   800     50350     108.4    0.2%
 6000  1312  3000   800     50490     123.3    0.2%
 6000  1324  3000   800     50360     93.77    0.1%
 6000  1336  3000   800     50290     70.07    0.1%
 6000  1348  3000   800     50470     277.4    0.5%
 6000  1360  3000   800     50570     124.9    0.2%
 6000  1372  3000   800     50370     89.14    0.1%
 6000  1384  3000   800     50330     135.5    0.2%
 6000  1396  3000   800     50360     60.63    0.1%
 6000  1408  3000   800     50540      60.8    0.1%
 6000  1420  3000   800     50410     70.13    0.1%
 6000  1432  3000   800     50370     79.64    0.1%
 6000  1444  3000   800     50540     100.6    0.1%
 6000  1456  3000   800     50440     110.8    0.2%
 6000  1468  3000   800     50440     157.5    0.3%
 6000  1480  3000   800     50610     104.6    0.2%
 6000  1492  3000   800     50320     59.59    0.1%
 6000  1504  3000   800     50400     46.48    0.0%
 6000  1516  3000   800     50410     135.1    0.2%
 6000  1528  3000   800     50630     124.6    0.2%
 6000  1540  3000   800     50430     94.71    0.1%
 6000  1552  3000   800     50410     45.81    0.0%
 6000  1564  3000   800     50470     89.63    0.1%
 6000  1576  3000   800     50570     169.1    0.3%
 6000  1588  3000   800     50420     78.05    0.1%
 6000  1600  1000   800     30960     104.8    0.3%
 6000  1600  1040   800     31410     38.03    0.1%
 6000  1600  1080   800     31850     98.75    0.3%
 6000  1600  1120   800     32310     227.2    0.7%
 6000  1600  1160   800     32650     184.8    0.5%
 6000  1600  1200   800     32990     95.58    0.2%
 6000  1600  1240   800     33300     107.4    0.3%
 6000  1600  1280   800     33770     168.8    0.4%
 6000  1600  1320   800     34210       121    0.3%
 6000  1600  1360   800     34460     95.46    0.2%
 6000  1600  1400   800     34780     51.39    0.1%
 6000  1600  1440   800     35340     66.76    0.1%
 6000  1600  1480   800     35820     149.2    0.4%
 6000  1600  1520   800     36030      71.6    0.1%
 6000  1600  1560   800     36430     54.29    0.1%
 6000  1600  1600   800     36890     66.41    0.1%
 6000  1600  1640   800     37410     124.4    0.3%
 6000  1600  1680   800     37690     82.34    0.2%
 6000  1600  1720   800     38170     59.73    0.1%
 6000  1600  1760   800     38650     127.6    0.3%
 6000  1600  1800   800     39010     93.64    0.2%
 6000  1600  1840   800     39320     47.34    0.1%
 6000  1600  1880   800     39840       144    0.3%
 6000  1600  1920   800     40330     180.4    0.4%
 6000  1600  1960   800     40640     114.6    0.2%
 6000  1600  2000   800     40880     60.82    0.1%
 6000  1600  2040   800     41310     92.88    0.2%
 6000  1600  2080   800     41730     75.29    0.1%
 6000  1600  2120   800     42170      98.8    0.2%
 6000  1600  2160   800     42470     62.15    0.1%
 6000  1600  2200   800     42890     140.4    0.3%
 6000  1600  2240   800     43220     112.6    0.2%
 6000  1600  2280   800     43570     76.32    0.1%
 6000  1600  2320   800     43930      41.3    0.0%
 6000  1600  2360   800     44260     89.13    0.2%
 6000  1600  2400   800     44620     95.76    0.2%
 6000  1600  2440   800     45030     41.39    0.0%
 6000  1600  2480   800     45510     139.2    0.3%
 6000  1600  2520   800     45770     47.82    0.1%
 6000  1600  2560   800     46180     117.6    0.2%
 6000  1600  2600   800     46340     66.11    0.1%
 6000  1600  2640   800     46900     51.59    0.1%
 6000  1600  2680   800     47280     55.67    0.1%
 6000  1600  2720   800     47810     112.8    0.2%
 6000  1600  2760   800     48140     145.6    0.3%
 6000  1600  2800   800     48430     142.7    0.2%
 6000  1600  2840   800     48780     57.78    0.1%
 6000  1600  2880   800     49270     70.02    0.1%
 6000  1600  2920   800     49610     59.13    0.1%
 6000  1600  2960   800     50040     96.18    0.1%
 6000  1600  3000   400     49050     114.9    0.2%
 6000  1600  3000   408     49020     195.3    0.3%
 6000  1600  3000   416     48930     147.4    0.3%
 6000  1600  3000   424     49170     148.6    0.3%
 6000  1600  3000   432     49180     194.3    0.3%
 6000  1600  3000   440     49070     169.6    0.3%
 6000  1600  3000   448     49010     106.6    0.2%
 6000  1600  3000   456     49070     57.15    0.1%
 6000  1600  3000   464     49310     182.9    0.3%
 6000  1600  3000   472     49200     49.25    0.1%
 6000  1600  3000   480     49350     166.3    0.3%
 6000  1600  3000   488     49350      83.5    0.1%
 6000  1600  3000   496     49270     60.47    0.1%
 6000  1600  3000   504     49470     48.18    0.0%
 6000  1600  3000   512     49490     53.99    0.1%
 6000  1600  3000   520     49600     70.39    0.1%
 6000  1600  3000   528     49750      89.9    0.1%
 6000  1600  3000   536     49740     64.14    0.1%
 6000  1600  3000   544     49750      50.1    0.1%
 6000  1600  3000   552     49800     129.8    0.2%
 6000  1600  3000   560     49930      74.5    0.1%
 6000  1600  3000   568     49960     103.4    0.2%
 6000  1600  3000   576     50200      91.7    0.1%
 6000  1600  3000   584     50050     84.02    0.1%
 6000  1600  3000   592     50090     118.9    0.2%
 6000  1600  3000   600     50180     104.6    0.2%
 6000  1600  3000   608     50390     191.2    0.3%
 6000  1600  3000   616     50320      75.5    0.1%
 6000  1600  3000   624     50230     71.17    0.1%
 6000  1600  3000   632     50270     92.92    0.1%
 6000  1600  3000   640     50350     73.17    0.1%
 6000  1600  3000   648     50380     59.57    0.1%
 6000  1600  3000   656     50310     46.17    0.0%
 6000  1600  3000   664     50440     110.4    0.2%
 6000  1600  3000   672     50500     57.66    0.1%
 6000  1600  3000   680     50500     57.69    0.1%
 6000  1600  3000   688     50490     102.6    0.2%
 6000  1600  3000   696     50460     65.82    0.1%
 6000  1600  3000   704     50470     58.28    0.1%
 6000  1600  3000   712     50480     43.54    0.0%
 6000  1600  3000   720     50620     153.5    0.3%
 6000  1600  3000   728     50570     149.1    0.2%
 6000  1600  3000   736     50610     116.8    0.2%
 6000  1600  3000   744     50410     48.09    0.0%
 6000  1600  3000   752     50440     62.49    0.1%
 6000  1600  3000   760     50460     75.34    0.1%
 6000  1600  3000   768     50310     44.62    0.0%
 6000  1600  3000   776     50380     100.2    0.1%
 6000  1600  3000   784     50520     91.52    0.1%
 6000  1600  3000   792     50570       116    0.2%
 6000  1600  3000   800     50440     77.84    0.1%

Quality and confidence:
param     error
v         0.009
t          0.03
a         0.009
d         0.045

Model:
Time ~=        0
    + v    3.606
    + t    0.514
    + a    9.736
    + d    3.337
              µs

Reads = 4 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
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 ~=    34.13
              µs

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

Model:
Time ~=    34.13
              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 ~=    151.7
              µs

Reads = 10
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    151.7
              µs

Reads = 10
Writes = 4
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "on_initialize_open_unsigned_with_snapshot", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    148.7
              µs

Reads = 10
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    148.7
              µs

Reads = 10
Writes = 4
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 ~=    62.06
              µs

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

Model:
Time ~=    62.06
              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 ~=    41.39
              µs

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

Model:
Time ~=    41.39
              µs

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

Model:
Time ~=    30.86
              µs

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

Model:
Time ~=    30.86
              µs

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

Model:
Time ~=     6138
              µs

Reads = 6
Writes = 8
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6138
              µs

Reads = 6
Writes = 8
Pallet: "pallet_election_provider_multi_phase", Extrinsic: "submit", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    80.01
    + c    0.619
              µs

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

Data points distribution:
    c   mean µs  sigma µs       %
    1     79.38     0.313    0.3%
    2     80.12      0.12    0.1%
    3     83.32     0.138    0.1%
    4     83.25     0.113    0.1%
    5      83.9     0.103    0.1%
    6     83.51     0.118    0.1%
    7     84.09     0.197    0.2%
    8     84.41     0.121    0.1%
    9     85.74     0.127    0.1%

Quality and confidence:
param     error
c         0.035

Model:
Time ~=    79.74
    + c    0.668
              µs

Reads = 4 + (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    3.533
    + t    0.266
    + a    11.33
    + d     4.78
              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       %
 4000  1600  3000   800     49450     76.16    0.1%
 4040  1600  3000   800     49430     103.8    0.2%
 4080  1600  3000   800     49480     153.4    0.3%
 4120  1600  3000   800     49710     110.9    0.2%
 4160  1600  3000   800     49710     57.17    0.1%
 4200  1600  3000   800     49830     32.84    0.0%
 4240  1600  3000   800     50060     83.15    0.1%
 4280  1600  3000   800     50340     114.1    0.2%
 4320  1600  3000   800     50370     68.54    0.1%
 4360  1600  3000   800     50500     89.15    0.1%
 4400  1600  3000   800     50670       117    0.2%
 4440  1600  3000   800     50810     96.32    0.1%
 4480  1600  3000   800     51130       121    0.2%
 4520  1600  3000   800     51050      67.6    0.1%
 4560  1600  3000   800     51150     84.17    0.1%
 4600  1600  3000   800     51330     83.95    0.1%
 4640  1600  3000   800     51540     81.38    0.1%
 4680  1600  3000   800     51570     81.73    0.1%
 4720  1600  3000   800     51650     77.31    0.1%
 4760  1600  3000   800     51800     42.41    0.0%
 4800  1600  3000   800     51950     54.76    0.1%
 4840  1600  3000   800     52090     55.14    0.1%
 4880  1600  3000   800     52350     131.3    0.2%
 4920  1600  3000   800     52420     53.16    0.1%
 4960  1600  3000   800     52550     85.74    0.1%
 5000  1600  3000   800     52760     130.1    0.2%
 5040  1600  3000   800     52790     90.51    0.1%
 5080  1600  3000   800     53020     149.2    0.2%
 5120  1600  3000   800     53220     120.3    0.2%
 5160  1600  3000   800     53270     65.56    0.1%
 5200  1600  3000   800     53390     109.7    0.2%
 5240  1600  3000   800     53490     84.16    0.1%
 5280  1600  3000   800     53710     86.16    0.1%
 5320  1600  3000   800     53820     41.43    0.0%
 5360  1600  3000   800     53910     70.14    0.1%
 5400  1600  3000   800     54170     89.78    0.1%
 5440  1600  3000   800     54340     115.5    0.2%
 5480  1600  3000   800     54370      89.7    0.1%
 5520  1600  3000   800     54580     102.3    0.1%
 5560  1600  3000   800     54660     49.48    0.0%
 5600  1600  3000   800     54890     113.7    0.2%
 5640  1600  3000   800     54920     105.2    0.1%
 5680  1600  3000   800     55220     99.73    0.1%
 5720  1600  3000   800     55320     38.08    0.0%
 5760  1600  3000   800     55690     136.1    0.2%
 5800  1600  3000   800     55410     84.02    0.1%
 5840  1600  3000   800     55870     108.2    0.1%
 5880  1600  3000   800     55840     70.18    0.1%
 5920  1600  3000   800     56010     48.15    0.0%
 5960  1600  3000   800     56110     68.99    0.1%
 6000  1000  3000   800     56390     94.07    0.1%
 6000  1012  3000   800     56210     77.88    0.1%
 6000  1024  3000   800     56170     62.29    0.1%
 6000  1036  3000   800     56200     105.2    0.1%
 6000  1048  3000   800     56160     159.7    0.2%
 6000  1060  3000   800     56180     103.3    0.1%
 6000  1072  3000   800     56110     85.47    0.1%
 6000  1084  3000   800     56250     75.05    0.1%
 6000  1096  3000   800     56350     96.12    0.1%
 6000  1108  3000   800     56110     83.95    0.1%
 6000  1120  3000   800     56370     178.7    0.3%
 6000  1132  3000   800     56130     73.86    0.1%
 6000  1144  3000   800     56240     84.16    0.1%
 6000  1156  3000   800     56270     132.1    0.2%
 6000  1168  3000   800     56260     73.64    0.1%
 6000  1180  3000   800     56280     88.68    0.1%
 6000  1192  3000   800     56260     90.72    0.1%
 6000  1204  3000   800     56490     108.8    0.1%
 6000  1216  3000   800     56230     42.01    0.0%
 6000  1228  3000   800     56170     38.56    0.0%
 6000  1240  3000   800     56230     55.71    0.0%
 6000  1252  3000   800     56270     148.2    0.2%
 6000  1264  3000   800     56200     59.73    0.1%
 6000  1276  3000   800     56340     170.5    0.3%
 6000  1288  3000   800     56140     61.37    0.1%
 6000  1300  3000   800     56190     19.62    0.0%
 6000  1312  3000   800     56420     106.7    0.1%
 6000  1324  3000   800     56390     179.3    0.3%
 6000  1336  3000   800     56310     42.16    0.0%
 6000  1348  3000   800     56300     52.27    0.0%
 6000  1360  3000   800     56600     65.57    0.1%
 6000  1372  3000   800     56440     144.9    0.2%
 6000  1384  3000   800     56290     48.24    0.0%
 6000  1396  3000   800     56340     75.12    0.1%
 6000  1408  3000   800     56540     140.1    0.2%
 6000  1420  3000   800     56340     93.37    0.1%
 6000  1432  3000   800     56430     48.89    0.0%
 6000  1444  3000   800     56690     170.5    0.3%
 6000  1456  3000   800     56410     88.12    0.1%
 6000  1468  3000   800     56240     75.19    0.1%
 6000  1480  3000   800     56310     74.65    0.1%
 6000  1492  3000   800     56170     78.52    0.1%
 6000  1504  3000   800     56320     143.3    0.2%
 6000  1516  3000   800     56160     113.5    0.2%
 6000  1528  3000   800     56200     47.71    0.0%
 6000  1540  3000   800     56200     56.89    0.1%
 6000  1552  3000   800     56300     121.9    0.2%
 6000  1564  3000   800     56400     100.9    0.1%
 6000  1576  3000   800     56420     90.36    0.1%
 6000  1588  3000   800     56340      48.2    0.0%
 6000  1600  1000   800     33010     33.91    0.1%
 6000  1600  1040   800     33630     107.5    0.3%
 6000  1600  1080   800     33940     50.06    0.1%
 6000  1600  1120   800     34420     50.34    0.1%
 6000  1600  1160   800     34790     54.83    0.1%
 6000  1600  1200   800     35240     95.79    0.2%
 6000  1600  1240   800     35660     54.45    0.1%
 6000  1600  1280   800     36110     76.35    0.2%
 6000  1600  1320   800     36580     50.96    0.1%
 6000  1600  1360   800     37020     76.07    0.2%
 6000  1600  1400   800     37960     59.86    0.1%
 6000  1600  1440   800     38500     89.12    0.2%
 6000  1600  1480   800     38850     30.88    0.0%
 6000  1600  1520   800     39300     38.57    0.0%
 6000  1600  1560   800     39790     51.79    0.1%
 6000  1600  1600   800     40230     40.43    0.1%
 6000  1600  1640   800     40730     48.67    0.1%
 6000  1600  1680   800     41200     67.15    0.1%
 6000  1600  1720   800     41680     114.7    0.2%
 6000  1600  1760   800     42100     60.76    0.1%
 6000  1600  1800   800     42560     122.8    0.2%
 6000  1600  1840   800     42990     49.07    0.1%
 6000  1600  1880   800     43500     67.78    0.1%
 6000  1600  1920   800     43990     158.4    0.3%
 6000  1600  1960   800     44460     213.2    0.4%
 6000  1600  2000   800     44700     94.36    0.2%
 6000  1600  2040   800     45090     60.47    0.1%
 6000  1600  2080   800     45570     42.42    0.0%
 6000  1600  2120   800     46010     65.07    0.1%
 6000  1600  2160   800     46430     42.54    0.0%
 6000  1600  2200   800     46840      46.5    0.0%
 6000  1600  2240   800     47240     61.53    0.1%
 6000  1600  2280   800     47650     61.47    0.1%
 6000  1600  2320   800     48070     56.41    0.1%
 6000  1600  2360   800     48410     35.92    0.0%
 6000  1600  2400   800     48980      83.2    0.1%
 6000  1600  2440   800     49280     47.15    0.0%
 6000  1600  2480   800     49820     78.67    0.1%
 6000  1600  2520   800     50070     65.79    0.1%
 6000  1600  2560   800     50610     57.73    0.1%
 6000  1600  2600   800     50850     43.73    0.0%
 6000  1600  2640   800     51440     109.8    0.2%
 6000  1600  2680   800     51770     92.36    0.1%
 6000  1600  2720   800     52260     143.6    0.2%
 6000  1600  2760   800     52580     91.29    0.1%
 6000  1600  2800   800     53050     66.06    0.1%
 6000  1600  2840   800     53500       103    0.1%
 6000  1600  2880   800     55020     84.34    0.1%
 6000  1600  2920   800     55400     47.36    0.0%
 6000  1600  2960   800     56040     151.3    0.2%
 6000  1600  3000   400     54620     63.84    0.1%
 6000  1600  3000   408     54650     117.1    0.2%
 6000  1600  3000   416     54780     56.67    0.1%
 6000  1600  3000   424     54690     58.78    0.1%
 6000  1600  3000   432     54960       188    0.3%
 6000  1600  3000   440     54710     31.39    0.0%
 6000  1600  3000   448     54860      65.8    0.1%
 6000  1600  3000   456     54860     61.02    0.1%
 6000  1600  3000   464     54970     132.4    0.2%
 6000  1600  3000   472     55100     212.9    0.3%
 6000  1600  3000   480     55020      50.5    0.0%
 6000  1600  3000   488     54980     102.4    0.1%
 6000  1600  3000   496     55230     157.6    0.2%
 6000  1600  3000   504     55190     87.06    0.1%
 6000  1600  3000   512     55340     74.19    0.1%
 6000  1600  3000   520     55450     136.8    0.2%
 6000  1600  3000   528     55390     39.92    0.0%
 6000  1600  3000   536     55360      49.5    0.0%
 6000  1600  3000   544     55590     140.5    0.2%
 6000  1600  3000   552     55710     178.2    0.3%
 6000  1600  3000   560     55610     52.04    0.0%
 6000  1600  3000   568     55700     183.4    0.3%
 6000  1600  3000   576     55740     36.16    0.0%
 6000  1600  3000   584     55910       120    0.2%
 6000  1600  3000   592     55850     62.58    0.1%
 6000  1600  3000   600     55950     86.52    0.1%
 6000  1600  3000   608     56090     73.87    0.1%
 6000  1600  3000   616     55930     78.19    0.1%
 6000  1600  3000   624     56110     89.04    0.1%
 6000  1600  3000   632     56300     160.2    0.2%
 6000  1600  3000   640     56150     64.57    0.1%
 6000  1600  3000   648     56060     73.37    0.1%
 6000  1600  3000   656     56230     98.12    0.1%
 6000  1600  3000   664     56250     182.2    0.3%
 6000  1600  3000   672     56370     47.66    0.0%
 6000  1600  3000   680     56310     84.32    0.1%
 6000  1600  3000   688     56270     67.48    0.1%
 6000  1600  3000   696     56330      95.8    0.1%
 6000  1600  3000   704     56260     70.57    0.1%
 6000  1600  3000   712     56300     47.41    0.0%
 6000  1600  3000   720     56470     122.4    0.2%
 6000  1600  3000   728     56430       145    0.2%
 6000  1600  3000   736     56410     107.2    0.1%
 6000  1600  3000   744     56400     49.16    0.0%
 6000  1600  3000   752     56390     69.24    0.1%
 6000  1600  3000   760     56460     147.7    0.2%
 6000  1600  3000   768     56290     43.81    0.0%
 6000  1600  3000   776     56260     65.49    0.1%
 6000  1600  3000   784     56460      67.3    0.1%
 6000  1600  3000   792     56450     131.6    0.2%
 6000  1600  3000   800     56380     82.75    0.1%

Quality and confidence:
param     error
v         0.013
t         0.045
a         0.013
d         0.068

Model:
Time ~=        0
    + v    3.546
    + t    0.081
    + a    11.64
    + d    3.315
              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    3.478
    + t    0.147
    + a    9.711
    + d    4.238
              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       %
 4000  1600  3000   800     43530     157.3    0.3%
 4040  1600  3000   800     43580     118.4    0.2%
 4080  1600  3000   800     43630     102.8    0.2%
 4120  1600  3000   800     43750     42.58    0.0%
 4160  1600  3000   800     44130     101.7    0.2%
 4200  1600  3000   800     44120     65.01    0.1%
 4240  1600  3000   800     44270     50.52    0.1%
 4280  1600  3000   800     44460     115.8    0.2%
 4320  1600  3000   800     44700     103.9    0.2%
 4360  1600  3000   800     44680     45.28    0.1%
 4400  1600  3000   800     44890     60.71    0.1%
 4440  1600  3000   800     45040     65.04    0.1%
 4480  1600  3000   800     45210      89.5    0.1%
 4520  1600  3000   800     45340     104.7    0.2%
 4560  1600  3000   800     45470     74.63    0.1%
 4600  1600  3000   800     45540     37.69    0.0%
 4640  1600  3000   800     45600     40.98    0.0%
 4680  1600  3000   800     45900     110.8    0.2%
 4720  1600  3000   800     45950     61.75    0.1%
 4760  1600  3000   800     46100     78.33    0.1%
 4800  1600  3000   800     46320      89.3    0.1%
 4840  1600  3000   800     46430     121.9    0.2%
 4880  1600  3000   800     46510     52.18    0.1%
 4920  1600  3000   800     46660     112.2    0.2%
 4960  1600  3000   800     46810     94.95    0.2%
 5000  1600  3000   800     47000     157.4    0.3%
 5040  1600  3000   800     47180       126    0.2%
 5080  1600  3000   800     47100     51.47    0.1%
 5120  1600  3000   800     47390     67.63    0.1%
 5160  1600  3000   800     47440     92.47    0.1%
 5200  1600  3000   800     47610     82.99    0.1%
 5240  1600  3000   800     47690     61.45    0.1%
 5280  1600  3000   800     47940     115.1    0.2%
 5320  1600  3000   800     48050     49.11    0.1%
 5360  1600  3000   800     48140     52.26    0.1%
 5400  1600  3000   800     48260      66.4    0.1%
 5440  1600  3000   800     48330     36.96    0.0%
 5480  1600  3000   800     48490     67.55    0.1%
 5520  1600  3000   800     48650     54.39    0.1%
 5560  1600  3000   800     48840     62.08    0.1%
 5600  1600  3000   800     49050     58.16    0.1%
 5640  1600  3000   800     49040      64.3    0.1%
 5680  1600  3000   800     49240      59.7    0.1%
 5720  1600  3000   800     49360     54.92    0.1%
 5760  1600  3000   800     49690     64.65    0.1%
 5800  1600  3000   800     49620     43.02    0.0%
 5840  1600  3000   800     49990      52.5    0.1%
 5880  1600  3000   800     50040     40.83    0.0%
 5920  1600  3000   800     50280     89.22    0.1%
 5960  1600  3000   800     50270     75.66    0.1%
 6000  1000  3000   800     50470      58.5    0.1%
 6000  1012  3000   800     50360     47.25    0.0%
 6000  1024  3000   800     50410     64.77    0.1%
 6000  1036  3000   800     50550     105.6    0.2%
 6000  1048  3000   800     50420     80.01    0.1%
 6000  1060  3000   800     50510     179.7    0.3%
 6000  1072  3000   800     50350     50.87    0.1%
 6000  1084  3000   800     50440     60.08    0.1%
 6000  1096  3000   800     50480     51.22    0.1%
 6000  1108  3000   800     50450     56.55    0.1%
 6000  1120  3000   800     50520     40.71    0.0%
 6000  1132  3000   800     50460     77.65    0.1%
 6000  1144  3000   800     50470     62.44    0.1%
 6000  1156  3000   800     50560     73.94    0.1%
 6000  1168  3000   800     50460     43.32    0.0%
 6000  1180  3000   800     50550      60.2    0.1%
 6000  1192  3000   800     50350       113    0.2%
 6000  1204  3000   800     50690     160.7    0.3%
 6000  1216  3000   800     50480     82.88    0.1%
 6000  1228  3000   800     50480     80.25    0.1%
 6000  1240  3000   800     50430     98.15    0.1%
 6000  1252  3000   800     50540     153.7    0.3%
 6000  1264  3000   800     50370     66.69    0.1%
 6000  1276  3000   800     50360     61.01    0.1%
 6000  1288  3000   800     50420     48.97    0.0%
 6000  1300  3000   800     50490     73.27    0.1%
 6000  1312  3000   800     50500     51.55    0.1%
 6000  1324  3000   800     50500     133.1    0.2%
 6000  1336  3000   800     50500     66.33    0.1%
 6000  1348  3000   800     50460     77.22    0.1%
 6000  1360  3000   800     50690     148.5    0.2%
 6000  1372  3000   800     50450     69.93    0.1%
 6000  1384  3000   800     50510       133    0.2%
 6000  1396  3000   800     50580     150.6    0.2%
 6000  1408  3000   800     50540     28.02    0.0%
 6000  1420  3000   800     50550     80.21    0.1%
 6000  1432  3000   800     50520     56.18    0.1%
 6000  1444  3000   800     50780     183.7    0.3%
 6000  1456  3000   800     50430     65.29    0.1%
 6000  1468  3000   800     50460     38.48    0.0%
 6000  1480  3000   800     50510     84.54    0.1%
 6000  1492  3000   800     50500     58.21    0.1%
 6000  1504  3000   800     50460     115.8    0.2%
 6000  1516  3000   800     50480     181.6    0.3%
 6000  1528  3000   800     50510     44.46    0.0%
 6000  1540  3000   800     50510     87.29    0.1%
 6000  1552  3000   800     50500     55.21    0.1%
 6000  1564  3000   800     50630     65.54    0.1%
 6000  1576  3000   800     50700     113.4    0.2%
 6000  1588  3000   800     50560     77.01    0.1%
 6000  1600  1000   800     30980     48.04    0.1%
 6000  1600  1040   800     31410     35.59    0.1%
 6000  1600  1080   800     31780      48.5    0.1%
 6000  1600  1120   800     32150     34.12    0.1%
 6000  1600  1160   800     32590     71.04    0.2%
 6000  1600  1200   800     32940     48.22    0.1%
 6000  1600  1240   800     33370     86.32    0.2%
 6000  1600  1280   800     33810     103.5    0.3%
 6000  1600  1320   800     34180     132.5    0.3%
 6000  1600  1360   800     34590     185.2    0.5%
 6000  1600  1400   800     34940     41.72    0.1%
 6000  1600  1440   800     35340     61.96    0.1%
 6000  1600  1480   800     35650        19    0.0%
 6000  1600  1520   800     36180     150.5    0.4%
 6000  1600  1560   800     36650     101.5    0.2%
 6000  1600  1600   800     36990     69.79    0.1%
 6000  1600  1640   800     37400     62.41    0.1%
 6000  1600  1680   800     37840     104.4    0.2%
 6000  1600  1720   800     38220     92.09    0.2%
 6000  1600  1760   800     38620      71.9    0.1%
 6000  1600  1800   800     38980     57.72    0.1%
 6000  1600  1840   800     39540     128.5    0.3%
 6000  1600  1880   800     40060     175.3    0.4%
 6000  1600  1920   800     40170     32.41    0.0%
 6000  1600  1960   800     40590     49.26    0.1%
 6000  1600  2000   800     40970     109.5    0.2%
 6000  1600  2040   800     41480     109.9    0.2%
 6000  1600  2080   800     41880       175    0.4%
 6000  1600  2120   800     42180     47.26    0.1%
 6000  1600  2160   800     42520     53.44    0.1%
 6000  1600  2200   800     42970     178.7    0.4%
 6000  1600  2240   800     43300     44.29    0.1%
 6000  1600  2280   800     43680     79.07    0.1%
 6000  1600  2320   800     44000     64.39    0.1%
 6000  1600  2360   800     44530     135.7    0.3%
 6000  1600  2400   800     44780     46.53    0.1%
 6000  1600  2440   800     45120     63.15    0.1%
 6000  1600  2480   800     45460     80.45    0.1%
 6000  1600  2520   800     45840     51.56    0.1%
 6000  1600  2560   800     46200     55.38    0.1%
 6000  1600  2600   800     46500     80.14    0.1%
 6000  1600  2640   800     47120     199.4    0.4%
 6000  1600  2680   800     47310     38.57    0.0%
 6000  1600  2720   800     47680      51.7    0.1%
 6000  1600  2760   800     48160     176.2    0.3%
 6000  1600  2800   800     48580     73.63    0.1%
 6000  1600  2840   800     48860     59.18    0.1%
 6000  1600  2880   800     49370     88.75    0.1%
 6000  1600  2920   800     49820     163.7    0.3%
 6000  1600  2960   800     50090     94.49    0.1%
 6000  1600  3000   400     49130     117.4    0.2%
 6000  1600  3000   408     48920     51.78    0.1%
 6000  1600  3000   416     48990     48.04    0.0%
 6000  1600  3000   424     48980     61.68    0.1%
 6000  1600  3000   432     49170      96.2    0.1%
 6000  1600  3000   440     49060     54.94    0.1%
 6000  1600  3000   448     49130     48.42    0.0%
 6000  1600  3000   456     49090     24.32    0.0%
 6000  1600  3000   464     49310     162.7    0.3%
 6000  1600  3000   472     49290     60.79    0.1%
 6000  1600  3000   480     49220     24.74    0.0%
 6000  1600  3000   488     49480       166    0.3%
 6000  1600  3000   496     49380     47.66    0.0%
 6000  1600  3000   504     49420     27.23    0.0%
 6000  1600  3000   512     49560     61.44    0.1%
 6000  1600  3000   520     49720     98.59    0.1%
 6000  1600  3000   528     49740     102.6    0.2%
 6000  1600  3000   536     49740     84.86    0.1%
 6000  1600  3000   544     49800     161.6    0.3%
 6000  1600  3000   552     49970     160.6    0.3%
 6000  1600  3000   560     49970     68.21    0.1%
 6000  1600  3000   568     50010     40.59    0.0%
 6000  1600  3000   576     50180     97.32    0.1%
 6000  1600  3000   584     50100     74.42    0.1%
 6000  1600  3000   592     50230     123.1    0.2%
 6000  1600  3000   600     50250      74.4    0.1%
 6000  1600  3000   608     50290     25.86    0.0%
 6000  1600  3000   616     50350     174.9    0.3%
 6000  1600  3000   624     50420     81.47    0.1%
 6000  1600  3000   632     50440     98.36    0.1%
 6000  1600  3000   640     50360     79.92    0.1%
 6000  1600  3000   648     50350     57.39    0.1%
 6000  1600  3000   656     50410     57.45    0.1%
 6000  1600  3000   664     50440     44.17    0.0%
 6000  1600  3000   672     50510     76.43    0.1%
 6000  1600  3000   680     50670     167.5    0.3%
 6000  1600  3000   688     50490     41.18    0.0%
 6000  1600  3000   696     50480     55.95    0.1%
 6000  1600  3000   704     50470     27.61    0.0%
 6000  1600  3000   712     50590     114.8    0.2%
 6000  1600  3000   720     50590     134.5    0.2%
 6000  1600  3000   728     50510     51.59    0.1%
 6000  1600  3000   736     50640     70.98    0.1%
 6000  1600  3000   744     50480     58.93    0.1%
 6000  1600  3000   752     50500     50.14    0.0%
 6000  1600  3000   760     50470     72.39    0.1%
 6000  1600  3000   768     50460     72.66    0.1%
 6000  1600  3000   776     50460     84.78    0.1%
 6000  1600  3000   784     50570     78.35    0.1%
 6000  1600  3000   792     50590       109    0.2%
 6000  1600  3000   800     50480     76.44    0.1%

Quality and confidence:
param     error
v         0.009
t          0.03
a         0.009
d         0.045

Model:
Time ~=        0
    + v    3.619
    + t    0.327
    + a    9.745
    + d    3.436
              µs

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

… kiz-rewrite-snapshot-put

…/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

kianenigma · 2021-07-07T13:13:51Z

@shawntabrizi maybe you can understand why the diff of the bot commit is kinda strange.

…rite-snapshot-put

…trate into kiz-rewrite-snapshot-put

kianenigma · 2021-07-08T11:41:24Z

Waiting for #9286 to get more insight into the weights.

…rite-snapshot-put

kianenigma · 2021-07-12T14:01:58Z

I ran the new create_snapshot_memory with this feature and without it. It will create a very large snapshot, which should give us an indication of any overhead in using encoded_size().

Without:

Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=   931500
              µs

Reads = 81006
Writes = 3

With:

Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=   897700
              µs

Reads = 81006
Writes = 3

which is pretty small.

…rite-snapshot-put

kianenigma · 2021-07-12T14:05:58Z

bot merge

ghost · 2021-07-12T14:06:02Z

Waiting for commit status.

Store election snapshot in a more memory-friendly way.

409306c

kianenigma requested review from bkchr and gui1117 July 5, 2021 13:42

coriolinus approved these changes Jul 5, 2021

View reviewed changes

Comment thread frame/election-provider-multi-phase/src/lib.rs Outdated

bkchr approved these changes Jul 5, 2021

View reviewed changes

fix

2953b52

re-order benchmarks

2e97d9d

gui1117 reviewed Jul 7, 2021

View reviewed changes

Comment thread frame/election-provider-multi-phase/src/lib.rs Outdated

Update frame/election-provider-multi-phase/src/lib.rs

8fd046f

Co-authored-by: Guillaume Thiolliere <gui.thiolliere@gmail.com>

github-actions Bot added the A7-needspolkadotpr label Jul 7, 2021

Parity Bot added 2 commits July 7, 2021 09:02

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

f734a1e

… kiz-rewrite-snapshot-put

kianenigma added 3 commits July 8, 2021 13:36

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

10ddfa9

…rite-snapshot-put

Merge branch 'kiz-rewrite-snapshot-put' of github.com:paritytech/subs…

34222f6

…trate into kiz-rewrite-snapshot-put

manually fix the weights

adb9927

kianenigma added 2 commits July 9, 2021 09:03

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

61b0806

…rite-snapshot-put

Master.into()

58dae39

kianenigma added 2 commits July 12, 2021 16:02

remove todo

1ba5123

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

34aae44

…rite-snapshot-put

github-actions Bot removed the A7-needspolkadotpr label Jul 12, 2021

ghost merged commit ef185e9 into master Jul 12, 2021

ghost deleted the kiz-rewrite-snapshot-put branch July 12, 2021 14:35

This pull request was closed.

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