re benchmark

[kianenigma]

No description provided.

[kianenigma]

/benchmark runtime polkadot pallet_election_provider_multi_phase

[kianenigma]

/benchmark runtime polkadot pallet_staking

[kianenigma]

/benchmark runtime kusama pallet_staking

[kianenigma]

/benchmark runtime kusama pallet_election_provider_multi_phase

[kianenigma]

/benchmark runtime westend pallet_staking

[kianenigma]

/benchmark runtime westend pallet_election_provider_multi_phase

[kianenigma]

following #2622

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Kusama Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=kusama-dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/kusama/src/weights/

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 ~= 20.76
µs

Reads = 7
Writes = 0
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 20.76
µs

Reads = 7
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 ~= 98.17
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 98.17
µs

Reads = 8
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 ~= 97.5
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 97.5
µs

Reads = 8
Writes = 4
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 ~= 18.25
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 18.25
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 ~= 7060
µs

Reads = 2
Writes = 6
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 7060
µs

Reads = 2
Writes = 6
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 3.875
+ t 0.167
+ a 12.39
+ d 7.152
µs

Reads = 6 + (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 55180 44.23 0.0%
4040 1600 3000 800 55330 87.84 0.1%
4080 1600 3000 800 55470 149.6 0.2%
4120 1600 3000 800 55570 71.01 0.1%
4160 1600 3000 800 55770 132.7 0.2%
4200 1600 3000 800 55890 91.96 0.1%
4240 1600 3000 800 55990 110 0.1%
4280 1600 3000 800 56190 94.35 0.1%
4320 1600 3000 800 56310 77.7 0.1%
4360 1600 3000 800 56530 80.44 0.1%
4400 1600 3000 800 56620 76.11 0.1%
4440 1600 3000 800 56760 53.29 0.0%
4480 1600 3000 800 56960 77.57 0.1%
4520 1600 3000 800 57010 77.04 0.1%
4560 1600 3000 800 57140 188.1 0.3%
4600 1600 3000 800 57380 115.7 0.2%
4640 1600 3000 800 57520 86.89 0.1%
4680 1600 3000 800 57640 72.58 0.1%
4720 1600 3000 800 57880 117.7 0.2%
4760 1600 3000 800 57900 91.38 0.1%
4800 1600 3000 800 58210 70.28 0.1%
4840 1600 3000 800 58260 94.21 0.1%
4880 1600 3000 800 58480 103.4 0.1%
4920 1600 3000 800 58640 73.82 0.1%
4960 1600 3000 800 58840 53.84 0.0%
5000 1600 3000 800 58900 68.25 0.1%
5040 1600 3000 800 59130 122.3 0.2%
5080 1600 3000 800 59150 96.96 0.1%
5120 1600 3000 800 59420 82.35 0.1%
5160 1600 3000 800 59510 76.82 0.1%
5200 1600 3000 800 59790 110.1 0.1%
5240 1600 3000 800 59880 128.8 0.2%
5280 1600 3000 800 60010 108.5 0.1%
5320 1600 3000 800 60010 58.29 0.0%
5360 1600 3000 800 60360 100.3 0.1%
5400 1600 3000 800 60450 78.19 0.1%
5440 1600 3000 800 60670 77.17 0.1%
5480 1600 3000 800 60680 71.43 0.1%
5520 1600 3000 800 60880 77.9 0.1%
5560 1600 3000 800 61090 69.51 0.1%
5600 1600 3000 800 61310 78.17 0.1%
5640 1600 3000 800 61410 84.39 0.1%
5680 1600 3000 800 61580 65.37 0.1%
5720 1600 3000 800 61720 139.1 0.2%
5760 1600 3000 800 61930 74.3 0.1%
5800 1600 3000 800 61980 81.21 0.1%
5840 1600 3000 800 62130 81.01 0.1%
5880 1600 3000 800 62290 67.11 0.1%
5920 1600 3000 800 62610 105.8 0.1%
5960 1600 3000 800 62680 146.4 0.2%
6000 1000 3000 800 62820 128.8 0.2%
6000 1012 3000 800 62850 64.01 0.1%
6000 1024 3000 800 62720 55.23 0.0%
6000 1036 3000 800 62750 95.25 0.1%
6000 1048 3000 800 62770 113.4 0.1%
6000 1060 3000 800 62900 138.3 0.2%
6000 1072 3000 800 62750 100.7 0.1%
6000 1084 3000 800 62910 80.87 0.1%
6000 1096 3000 800 62830 101.7 0.1%
6000 1108 3000 800 62810 52.42 0.0%
6000 1120 3000 800 62760 134 0.2%
6000 1132 3000 800 62900 84.83 0.1%
6000 1144 3000 800 62780 70.96 0.1%
6000 1156 3000 800 62810 76.77 0.1%
6000 1168 3000 800 62750 75.9 0.1%
6000 1180 3000 800 62810 75.75 0.1%
6000 1192 3000 800 62750 52.17 0.0%
6000 1204 3000 800 62790 111.9 0.1%
6000 1216 3000 800 62670 75.57 0.1%
6000 1228 3000 800 62820 91.06 0.1%
6000 1240 3000 800 62800 83.53 0.1%
6000 1252 3000 800 62870 70.22 0.1%
6000 1264 3000 800 62640 59.41 0.0%
6000 1276 3000 800 62890 49.04 0.0%
6000 1288 3000 800 62690 67.86 0.1%
6000 1300 3000 800 62780 84.61 0.1%
6000 1312 3000 800 62730 101.9 0.1%
6000 1324 3000 800 62990 60.97 0.0%
6000 1336 3000 800 62890 86.46 0.1%
6000 1348 3000 800 62920 80.55 0.1%
6000 1360 3000 800 62890 89.51 0.1%
6000 1372 3000 800 62900 89.92 0.1%
6000 1384 3000 800 62650 109.5 0.1%
6000 1396 3000 800 62890 52.06 0.0%
6000 1408 3000 800 62840 48.58 0.0%
6000 1420 3000 800 62840 128 0.2%
6000 1432 3000 800 62790 116 0.1%
6000 1444 3000 800 62890 68.2 0.1%
6000 1456 3000 800 62740 45.78 0.0%
6000 1468 3000 800 62900 109 0.1%
6000 1480 3000 800 62780 78.37 0.1%
6000 1492 3000 800 62850 81.52 0.1%
6000 1504 3000 800 62820 113.2 0.1%
6000 1516 3000 800 62940 46.45 0.0%
6000 1528 3000 800 62870 134 0.2%
6000 1540 3000 800 62740 140.4 0.2%
6000 1552 3000 800 62850 129.9 0.2%
6000 1564 3000 800 62940 93.02 0.1%
6000 1576 3000 800 62810 154.7 0.2%
6000 1588 3000 800 62800 143.6 0.2%
6000 1600 1000 800 37010 57.83 0.1%
6000 1600 1040 800 37430 103.1 0.2%
6000 1600 1080 800 38000 36.53 0.0%
6000 1600 1120 800 38410 58.21 0.1%
6000 1600 1160 800 38810 93.32 0.2%
6000 1600 1200 800 39290 90.78 0.2%
6000 1600 1240 800 39770 112.3 0.2%
6000 1600 1280 800 40150 77.91 0.1%
6000 1600 1320 800 40680 62.48 0.1%
6000 1600 1360 800 41250 59.17 0.1%
6000 1600 1400 800 42450 29.81 0.0%
6000 1600 1440 800 42970 124.3 0.2%
6000 1600 1480 800 43360 93.47 0.2%
6000 1600 1520 800 43990 88.82 0.2%
6000 1600 1560 800 44410 111.5 0.2%
6000 1600 1600 800 44970 95.18 0.2%
6000 1600 1640 800 45460 90.53 0.1%
6000 1600 1680 800 45980 43.37 0.0%
6000 1600 1720 800 46400 63.05 0.1%
6000 1600 1760 800 46890 84.6 0.1%
6000 1600 1800 800 47540 43.25 0.0%
6000 1600 1840 800 47940 79.67 0.1%
6000 1600 1880 800 48420 69.4 0.1%
6000 1600 1920 800 48890 64.64 0.1%
6000 1600 1960 800 49290 84.26 0.1%
6000 1600 2000 800 49780 86.05 0.1%
6000 1600 2040 800 50230 90.6 0.1%
6000 1600 2080 800 50750 81.4 0.1%
6000 1600 2120 800 51200 39.55 0.0%
6000 1600 2160 800 51610 53.16 0.1%
6000 1600 2200 800 52030 76.6 0.1%
6000 1600 2240 800 52470 80.36 0.1%
6000 1600 2280 800 52880 61.05 0.1%
6000 1600 2320 800 53300 100.1 0.1%
6000 1600 2360 800 53790 74.88 0.1%
6000 1600 2400 800 54230 68.38 0.1%
6000 1600 2440 800 54670 79.06 0.1%
6000 1600 2480 800 55200 36.98 0.0%
6000 1600 2520 800 55590 58.21 0.1%
6000 1600 2560 800 55890 61.01 0.1%
6000 1600 2600 800 56280 76.79 0.1%
6000 1600 2640 800 56940 43.23 0.0%
6000 1600 2680 800 57360 54.28 0.0%
6000 1600 2720 800 57790 107.1 0.1%
6000 1600 2760 800 58300 41.47 0.0%
6000 1600 2800 800 58760 38.79 0.0%
6000 1600 2840 800 59210 107.7 0.1%
6000 1600 2880 800 61530 57.45 0.0%
6000 1600 2920 800 61950 117.4 0.1%
6000 1600 2960 800 62420 48.47 0.0%
6000 1600 3000 400 60340 70.29 0.1%
6000 1600 3000 408 60450 76.6 0.1%
6000 1600 3000 416 60390 60.87 0.1%
6000 1600 3000 424 60540 61.97 0.1%
6000 1600 3000 432 60560 96.1 0.1%
6000 1600 3000 440 60580 73.76 0.1%
6000 1600 3000 448 60620 76.35 0.1%
6000 1600 3000 456 60830 76.48 0.1%
6000 1600 3000 464 60830 69.4 0.1%
6000 1600 3000 472 60910 69.06 0.1%
6000 1600 3000 480 61000 97.73 0.1%
6000 1600 3000 488 61220 49.13 0.0%
6000 1600 3000 496 61160 83.48 0.1%
6000 1600 3000 504 61460 45.6 0.0%
6000 1600 3000 512 61440 117.4 0.1%
6000 1600 3000 520 61620 48.11 0.0%
6000 1600 3000 528 61690 38.91 0.0%
6000 1600 3000 536 61710 103.6 0.1%
6000 1600 3000 544 61800 56.1 0.0%
6000 1600 3000 552 61800 56.71 0.0%
6000 1600 3000 560 61890 86.42 0.1%
6000 1600 3000 568 62140 45.38 0.0%
6000 1600 3000 576 62110 116.2 0.1%
6000 1600 3000 584 62270 44.55 0.0%
6000 1600 3000 592 62320 68.68 0.1%
6000 1600 3000 600 62370 70.15 0.1%
6000 1600 3000 608 62500 49.28 0.0%
6000 1600 3000 616 62590 48.48 0.0%
6000 1600 3000 624 62550 62.68 0.1%
6000 1600 3000 632 62680 73.93 0.1%
6000 1600 3000 640 62590 75.26 0.1%
6000 1600 3000 648 62740 42.27 0.0%
6000 1600 3000 656 62520 81.19 0.1%
6000 1600 3000 664 62720 74.56 0.1%
6000 1600 3000 672 62910 57.99 0.0%
6000 1600 3000 680 62860 110.2 0.1%
6000 1600 3000 688 62840 67.07 0.1%
6000 1600 3000 696 63030 62.94 0.0%
6000 1600 3000 704 62920 67.08 0.1%
6000 1600 3000 712 62890 102 0.1%
6000 1600 3000 720 62950 37.59 0.0%
6000 1600 3000 728 63070 86.78 0.1%
6000 1600 3000 736 63000 53.48 0.0%
6000 1600 3000 744 63050 50.73 0.0%
6000 1600 3000 752 62850 120.3 0.1%
6000 1600 3000 760 63060 70.24 0.1%
6000 1600 3000 768 62970 42.04 0.0%
6000 1600 3000 776 62980 110.8 0.1%
6000 1600 3000 784 63020 87.78 0.1%
6000 1600 3000 792 63090 49.94 0.0%
6000 1600 3000 800 62970 99.4 0.1%

Quality and confidence:
param error
v 0.02
t 0.067
a 0.02
d 0.101

Model:
Time ~= 0
+ v 3.847
+ t 0
+ a 13.02
+ d 4.584
µs

Reads = 6 + (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 3.85
+ t 0.114
+ a 9.462
+ d 5.69
µs

Reads = 3 + (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 44690 57.7 0.1%
4040 1600 3000 800 44830 42.38 0.0%
4080 1600 3000 800 44950 59.71 0.1%
4120 1600 3000 800 45160 23.59 0.0%
4160 1600 3000 800 45320 36.36 0.0%
4200 1600 3000 800 45490 48.23 0.1%
4240 1600 3000 800 45500 73.73 0.1%
4280 1600 3000 800 45750 42.2 0.0%
4320 1600 3000 800 45920 59.69 0.1%
4360 1600 3000 800 46070 72.65 0.1%
4400 1600 3000 800 46230 57.5 0.1%
4440 1600 3000 800 46360 42.62 0.0%
4480 1600 3000 800 46460 33.86 0.0%
4520 1600 3000 800 46670 49.04 0.1%
4560 1600 3000 800 46800 70.31 0.1%
4600 1600 3000 800 46870 78.64 0.1%
4640 1600 3000 800 47090 59.9 0.1%
4680 1600 3000 800 47300 60.27 0.1%
4720 1600 3000 800 47390 45.98 0.0%
4760 1600 3000 800 47560 63.09 0.1%
4800 1600 3000 800 47760 65.6 0.1%
4840 1600 3000 800 47790 95.14 0.1%
4880 1600 3000 800 48070 77.89 0.1%
4920 1600 3000 800 48170 52.69 0.1%
4960 1600 3000 800 48390 58.7 0.1%
5000 1600 3000 800 48460 55.79 0.1%
5040 1600 3000 800 48710 69.8 0.1%
5080 1600 3000 800 48800 50.45 0.1%
5120 1600 3000 800 48950 95.41 0.1%
5160 1600 3000 800 49110 57.5 0.1%
5200 1600 3000 800 49250 80.08 0.1%
5240 1600 3000 800 49490 47.96 0.0%
5280 1600 3000 800 49580 42.64 0.0%
5320 1600 3000 800 49750 42.51 0.0%
5360 1600 3000 800 49910 63.5 0.1%
5400 1600 3000 800 50110 35.42 0.0%
5440 1600 3000 800 50190 76.12 0.1%
5480 1600 3000 800 50340 65.9 0.1%
5520 1600 3000 800 50530 42.15 0.0%
5560 1600 3000 800 50660 58.5 0.1%
5600 1600 3000 800 50900 60.07 0.1%
5640 1600 3000 800 51030 49.88 0.0%
5680 1600 3000 800 51130 53.95 0.1%
5720 1600 3000 800 51270 61.73 0.1%
5760 1600 3000 800 51360 66.27 0.1%
5800 1600 3000 800 51600 71.97 0.1%
5840 1600 3000 800 51740 68.05 0.1%
5880 1600 3000 800 51970 59.71 0.1%
5920 1600 3000 800 52030 100.9 0.1%
5960 1600 3000 800 52210 80.91 0.1%
6000 1000 3000 800 52240 79.6 0.1%
6000 1012 3000 800 52340 44.59 0.0%
6000 1024 3000 800 52340 74.22 0.1%
6000 1036 3000 800 52280 78.79 0.1%
6000 1048 3000 800 52290 91.69 0.1%
6000 1060 3000 800 52370 54.2 0.1%
6000 1072 3000 800 52310 82.72 0.1%
6000 1084 3000 800 52380 73.71 0.1%
6000 1096 3000 800 52270 128.3 0.2%
6000 1108 3000 800 52290 53.01 0.1%
6000 1120 3000 800 52340 77.23 0.1%
6000 1132 3000 800 52360 95.52 0.1%
6000 1144 3000 800 52270 96.23 0.1%
6000 1156 3000 800 52310 54.7 0.1%
6000 1168 3000 800 52310 56.71 0.1%
6000 1180 3000 800 52330 70.2 0.1%
6000 1192 3000 800 52340 56.72 0.1%
6000 1204 3000 800 52390 54.12 0.1%
6000 1216 3000 800 52330 44.26 0.0%
6000 1228 3000 800 52340 43.92 0.0%
6000 1240 3000 800 52310 56.67 0.1%
6000 1252 3000 800 52290 55.45 0.1%
6000 1264 3000 800 52350 58.59 0.1%
6000 1276 3000 800 52400 88.72 0.1%
6000 1288 3000 800 52280 75.98 0.1%
6000 1300 3000 800 52320 75.69 0.1%
6000 1312 3000 800 52380 49.2 0.0%
6000 1324 3000 800 52270 117.3 0.2%
6000 1336 3000 800 52220 86.76 0.1%
6000 1348 3000 800 52320 59.13 0.1%
6000 1360 3000 800 52330 94.78 0.1%
6000 1372 3000 800 52400 44.96 0.0%
6000 1384 3000 800 52300 71.02 0.1%
6000 1396 3000 800 52210 44.4 0.0%
6000 1408 3000 800 52460 100.1 0.1%
6000 1420 3000 800 52360 66.47 0.1%
6000 1432 3000 800 52450 39.19 0.0%
6000 1444 3000 800 52410 68.74 0.1%
6000 1456 3000 800 52370 59.44 0.1%
6000 1468 3000 800 52230 74.16 0.1%
6000 1480 3000 800 52280 97.64 0.1%
6000 1492 3000 800 52270 104.5 0.1%
6000 1504 3000 800 52400 99.1 0.1%
6000 1516 3000 800 52410 54.65 0.1%
6000 1528 3000 800 52440 72.7 0.1%
6000 1540 3000 800 52350 63.9 0.1%
6000 1552 3000 800 52420 67.91 0.1%
6000 1564 3000 800 52370 55.84 0.1%
6000 1576 3000 800 52330 71.49 0.1%
6000 1588 3000 800 52360 47.42 0.0%
6000 1600 1000 800 33320 115.4 0.3%
6000 1600 1040 800 33810 46.7 0.1%
6000 1600 1080 800 34090 58.32 0.1%
6000 1600 1120 800 34520 84.86 0.2%
6000 1600 1160 800 34830 94.93 0.2%
6000 1600 1200 800 35290 100.1 0.2%
6000 1600 1240 800 35700 29.01 0.0%
6000 1600 1280 800 36000 50.63 0.1%
6000 1600 1320 800 36420 50.13 0.1%
6000 1600 1360 800 36850 35.96 0.0%
6000 1600 1400 800 37040 67.92 0.1%
6000 1600 1440 800 37620 50.47 0.1%
6000 1600 1480 800 37870 114.2 0.3%
6000 1600 1520 800 38340 89.2 0.2%
6000 1600 1560 800 38830 82.03 0.2%
6000 1600 1600 800 39230 66.41 0.1%
6000 1600 1640 800 39590 83.9 0.2%
6000 1600 1680 800 39950 78.63 0.1%
6000 1600 1720 800 40390 94.87 0.2%
6000 1600 1760 800 40790 118.9 0.2%
6000 1600 1800 800 41290 80.76 0.1%
6000 1600 1840 800 41550 80.21 0.1%
6000 1600 1880 800 41990 90.36 0.2%
6000 1600 1920 800 42390 108.1 0.2%
6000 1600 1960 800 42790 91.88 0.2%
6000 1600 2000 800 43150 101.5 0.2%
6000 1600 2040 800 43650 27.29 0.0%
6000 1600 2080 800 44000 46.29 0.1%
6000 1600 2120 800 44350 20.53 0.0%
6000 1600 2160 800 44520 68.17 0.1%
6000 1600 2200 800 44960 105.6 0.2%
6000 1600 2240 800 45390 95.11 0.2%
6000 1600 2280 800 45780 58 0.1%
6000 1600 2320 800 46030 80.04 0.1%
6000 1600 2360 800 46430 75.61 0.1%
6000 1600 2400 800 46760 70.49 0.1%
6000 1600 2440 800 47170 38.24 0.0%
6000 1600 2480 800 47430 89.25 0.1%
6000 1600 2520 800 47830 51.15 0.1%
6000 1600 2560 800 48150 63.64 0.1%
6000 1600 2600 800 48550 45.66 0.0%
6000 1600 2640 800 48730 110.2 0.2%
6000 1600 2680 800 49230 31.26 0.0%
6000 1600 2720 800 49640 69.86 0.1%
6000 1600 2760 800 49990 85.29 0.1%
6000 1600 2800 800 50440 35.91 0.0%
6000 1600 2840 800 50810 54.66 0.1%
6000 1600 2880 800 51150 69.44 0.1%
6000 1600 2920 800 51540 33.76 0.0%
6000 1600 2960 800 51980 93.62 0.1%
6000 1600 3000 400 50430 82.14 0.1%
6000 1600 3000 408 50350 124.5 0.2%
6000 1600 3000 416 50250 109.7 0.2%
6000 1600 3000 424 50490 44.06 0.0%
6000 1600 3000 432 50410 81.67 0.1%
6000 1600 3000 440 50510 68.2 0.1%
6000 1600 3000 448 50630 65.73 0.1%
6000 1600 3000 456 50660 96.94 0.1%
6000 1600 3000 464 50870 98.25 0.1%
6000 1600 3000 472 50880 88.96 0.1%
6000 1600 3000 480 50890 61.04 0.1%
6000 1600 3000 488 50900 63.01 0.1%
6000 1600 3000 496 51070 31.5 0.0%
6000 1600 3000 504 51110 58.1 0.1%
6000 1600 3000 512 51290 52.69 0.1%
6000 1600 3000 520 51370 75.42 0.1%
6000 1600 3000 528 51410 58.1 0.1%
6000 1600 3000 536 51430 78.41 0.1%
6000 1600 3000 544 51560 126.5 0.2%
6000 1600 3000 552 51660 51.32 0.0%
6000 1600 3000 560 51810 75.48 0.1%
6000 1600 3000 568 51870 102.1 0.1%
6000 1600 3000 576 51850 99.66 0.1%
6000 1600 3000 584 51950 75.44 0.1%
6000 1600 3000 592 51930 102.9 0.1%
6000 1600 3000 600 52050 112.5 0.2%
6000 1600 3000 608 52160 104.9 0.2%
6000 1600 3000 616 52210 66.46 0.1%
6000 1600 3000 624 52260 70.12 0.1%
6000 1600 3000 632 52250 78.09 0.1%
6000 1600 3000 640 52400 73.1 0.1%
6000 1600 3000 648 52400 45.76 0.0%
6000 1600 3000 656 52330 68.61 0.1%
6000 1600 3000 664 52460 40.34 0.0%
6000 1600 3000 672 52420 53.28 0.1%
6000 1600 3000 680 52550 30.88 0.0%
6000 1600 3000 688 52640 38.92 0.0%
6000 1600 3000 696 52550 41.89 0.0%
6000 1600 3000 704 52540 38.55 0.0%
6000 1600 3000 712 52490 42.78 0.0%
6000 1600 3000 720 52500 46.26 0.0%
6000 1600 3000 728 52480 102.7 0.1%
6000 1600 3000 736 52520 80.76 0.1%
6000 1600 3000 744 52450 73.62 0.1%
6000 1600 3000 752 52400 58.86 0.1%
6000 1600 3000 760 52390 83.18 0.1%
6000 1600 3000 768 52420 73.74 0.1%
6000 1600 3000 776 52380 55.27 0.1%
6000 1600 3000 784 52460 63.04 0.1%
6000 1600 3000 792 52490 77.25 0.1%
6000 1600 3000 800 52380 63.01 0.1%

Quality and confidence:
param error
v 0.01
t 0.035
a 0.01
d 0.053

Model:
Time ~= 0
+ v 3.978
+ t 0.514
+ a 9.553
+ d 4.396
µs

Reads = 3 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Westend Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=westend-dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/westend/src/weights/

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 ~= 21.7
µs

Reads = 7
Writes = 0
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 21.7
µs

Reads = 7
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 ~= 103.4
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 103.4
µs

Reads = 8
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 ~= 102.4
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 102.4
µs

Reads = 8
Writes = 4
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 ~= 19.13
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 19.13
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 ~= 6981
µs

Reads = 2
Writes = 6
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 6981
µs

Reads = 2
Writes = 6
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 3.822
+ t 0.204
+ a 12.98
+ d 7.133
µs

Reads = 6 + (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 56950 114 0.2%
4040 1600 3000 800 57010 63.01 0.1%
4080 1600 3000 800 57270 65.67 0.1%
4120 1600 3000 800 57340 109.1 0.1%
4160 1600 3000 800 57530 94.01 0.1%
4200 1600 3000 800 57550 51.8 0.0%
4240 1600 3000 800 57780 81.68 0.1%
4280 1600 3000 800 57930 57.69 0.0%
4320 1600 3000 800 58160 72.49 0.1%
4360 1600 3000 800 58210 49.15 0.0%
4400 1600 3000 800 58410 72.02 0.1%
4440 1600 3000 800 58470 75.04 0.1%
4480 1600 3000 800 58730 55.85 0.0%
4520 1600 3000 800 58910 70.39 0.1%
4560 1600 3000 800 59050 45.93 0.0%
4600 1600 3000 800 59210 108.5 0.1%
4640 1600 3000 800 59390 82.55 0.1%
4680 1600 3000 800 59500 70.31 0.1%
4720 1600 3000 800 59600 46.62 0.0%
4760 1600 3000 800 59800 102.4 0.1%
4800 1600 3000 800 59970 79.76 0.1%
4840 1600 3000 800 60020 111.7 0.1%
4880 1600 3000 800 60320 88.66 0.1%
4920 1600 3000 800 60450 75.74 0.1%
4960 1600 3000 800 60580 63.01 0.1%
5000 1600 3000 800 60670 45.84 0.0%
5040 1600 3000 800 60900 78.3 0.1%
5080 1600 3000 800 60960 96.26 0.1%
5120 1600 3000 800 61210 93 0.1%
5160 1600 3000 800 61230 51.96 0.0%
5200 1600 3000 800 61480 88.29 0.1%
5240 1600 3000 800 61660 79.15 0.1%
5280 1600 3000 800 61750 101.9 0.1%
5320 1600 3000 800 61930 82.65 0.1%
5360 1600 3000 800 62100 62.49 0.1%
5400 1600 3000 800 62230 141.5 0.2%
5440 1600 3000 800 62390 93.67 0.1%
5480 1600 3000 800 62400 124.6 0.1%
5520 1600 3000 800 62700 76.24 0.1%
5560 1600 3000 800 62810 94.65 0.1%
5600 1600 3000 800 63040 54.53 0.0%
5640 1600 3000 800 63070 123.1 0.1%
5680 1600 3000 800 63300 63 0.0%
5720 1600 3000 800 63350 51.31 0.0%
5760 1600 3000 800 63580 87.09 0.1%
5800 1600 3000 800 63720 117.6 0.1%
5840 1600 3000 800 63900 88.79 0.1%
5880 1600 3000 800 64020 108.2 0.1%
5920 1600 3000 800 64210 106.2 0.1%
5960 1600 3000 800 64310 100.8 0.1%
6000 1000 3000 800 64530 60.54 0.0%
6000 1012 3000 800 64470 100.2 0.1%
6000 1024 3000 800 64480 46.68 0.0%
6000 1036 3000 800 64500 114.1 0.1%
6000 1048 3000 800 64460 73.11 0.1%
6000 1060 3000 800 64500 115.8 0.1%
6000 1072 3000 800 64510 104.2 0.1%
6000 1084 3000 800 64590 65.35 0.1%
6000 1096 3000 800 64520 151.8 0.2%
6000 1108 3000 800 64660 73.06 0.1%
6000 1120 3000 800 64530 76.41 0.1%
6000 1132 3000 800 64590 140.9 0.2%
6000 1144 3000 800 64550 131.5 0.2%
6000 1156 3000 800 64510 117.4 0.1%
6000 1168 3000 800 64420 51.39 0.0%
6000 1180 3000 800 64570 147.9 0.2%
6000 1192 3000 800 64380 105.8 0.1%
6000 1204 3000 800 64660 99.36 0.1%
6000 1216 3000 800 64490 84.66 0.1%
6000 1228 3000 800 64570 82.93 0.1%
6000 1240 3000 800 64490 108.4 0.1%
6000 1252 3000 800 64530 89.36 0.1%
6000 1264 3000 800 64430 67.8 0.1%
6000 1276 3000 800 64630 84.35 0.1%
6000 1288 3000 800 64400 82.34 0.1%
6000 1300 3000 800 64500 98.49 0.1%
6000 1312 3000 800 64650 92.13 0.1%
6000 1324 3000 800 64610 112.6 0.1%
6000 1336 3000 800 64480 85.45 0.1%
6000 1348 3000 800 64520 100.2 0.1%
6000 1360 3000 800 64560 98.88 0.1%
6000 1372 3000 800 64610 56.23 0.0%
6000 1384 3000 800 64570 145.9 0.2%
6000 1396 3000 800 64850 98.63 0.1%
6000 1408 3000 800 64580 156.9 0.2%
6000 1420 3000 800 64620 93.64 0.1%
6000 1432 3000 800 64480 80.83 0.1%
6000 1444 3000 800 64650 103.1 0.1%
6000 1456 3000 800 64460 116.5 0.1%
6000 1468 3000 800 64670 69.67 0.1%
6000 1480 3000 800 64470 149.6 0.2%
6000 1492 3000 800 64560 59.76 0.0%
6000 1504 3000 800 64550 99.54 0.1%
6000 1516 3000 800 64500 72.74 0.1%
6000 1528 3000 800 64620 98.35 0.1%
6000 1540 3000 800 64530 109.8 0.1%
6000 1552 3000 800 64660 84.49 0.1%
6000 1564 3000 800 64720 109 0.1%
6000 1576 3000 800 64630 128.4 0.1%
6000 1588 3000 800 64480 60.73 0.0%
6000 1600 1000 800 37610 39.98 0.1%
6000 1600 1040 800 38080 70.92 0.1%
6000 1600 1080 800 38610 75.1 0.1%
6000 1600 1120 800 39040 65.5 0.1%
6000 1600 1160 800 39470 131.7 0.3%
6000 1600 1200 800 40070 106 0.2%
6000 1600 1240 800 40400 86.19 0.2%
6000 1600 1280 800 40760 106.3 0.2%
6000 1600 1320 800 41400 66.24 0.1%
6000 1600 1360 800 41950 92.06 0.2%
6000 1600 1400 800 43430 63.26 0.1%
6000 1600 1440 800 43890 110 0.2%
6000 1600 1480 800 44370 117.9 0.2%
6000 1600 1520 800 44880 83.26 0.1%
6000 1600 1560 800 45430 84.02 0.1%
6000 1600 1600 800 45880 70.09 0.1%
6000 1600 1640 800 46430 97.59 0.2%
6000 1600 1680 800 46930 119 0.2%
6000 1600 1720 800 47430 128.1 0.2%
6000 1600 1760 800 48040 75.18 0.1%
6000 1600 1800 800 48480 96.58 0.1%
6000 1600 1840 800 48940 74.75 0.1%
6000 1600 1880 800 49510 44.2 0.0%
6000 1600 1920 800 49990 63.83 0.1%
6000 1600 1960 800 50500 50.87 0.1%
6000 1600 2000 800 50960 63.58 0.1%
6000 1600 2040 800 51520 52.11 0.1%
6000 1600 2080 800 52010 58.76 0.1%
6000 1600 2120 800 52450 79.1 0.1%
6000 1600 2160 800 52940 103.1 0.1%
6000 1600 2200 800 53280 80.89 0.1%
6000 1600 2240 800 53790 63.45 0.1%
6000 1600 2280 800 54250 100.9 0.1%
6000 1600 2320 800 54720 102.9 0.1%
6000 1600 2360 800 55220 88.01 0.1%
6000 1600 2400 800 55670 78.89 0.1%
6000 1600 2440 800 56020 102.2 0.1%
6000 1600 2480 800 56590 60.98 0.1%
6000 1600 2520 800 56950 63.79 0.1%
6000 1600 2560 800 57480 86.63 0.1%
6000 1600 2600 800 57920 117.8 0.2%
6000 1600 2640 800 58480 33.85 0.0%
6000 1600 2680 800 58960 113.4 0.1%
6000 1600 2720 800 59290 95.34 0.1%
6000 1600 2760 800 59920 48.8 0.0%
6000 1600 2800 800 60390 64.64 0.1%
6000 1600 2840 800 60930 69.31 0.1%
6000 1600 2880 800 63140 99.16 0.1%
6000 1600 2920 800 63720 89.8 0.1%
6000 1600 2960 800 64100 101 0.1%
6000 1600 3000 400 62240 41.6 0.0%
6000 1600 3000 408 62120 63.55 0.1%
6000 1600 3000 416 62130 82.83 0.1%
6000 1600 3000 424 62230 66.12 0.1%
6000 1600 3000 432 62180 104.2 0.1%
6000 1600 3000 440 62310 85.35 0.1%
6000 1600 3000 448 62370 75.35 0.1%
6000 1600 3000 456 62540 90.18 0.1%
6000 1600 3000 464 62650 90.05 0.1%
6000 1600 3000 472 62620 90.47 0.1%
6000 1600 3000 480 62710 58.7 0.0%
6000 1600 3000 488 62920 55.26 0.0%
6000 1600 3000 496 62920 90.57 0.1%
6000 1600 3000 504 62900 51.82 0.0%
6000 1600 3000 512 63090 126.3 0.2%
6000 1600 3000 520 63110 41.17 0.0%
6000 1600 3000 528 63330 79.89 0.1%
6000 1600 3000 536 63370 67.45 0.1%
6000 1600 3000 544 63420 50.12 0.0%
6000 1600 3000 552 63540 65.44 0.1%
6000 1600 3000 560 63660 87.87 0.1%
6000 1600 3000 568 63760 74.87 0.1%
6000 1600 3000 576 63910 71.05 0.1%
6000 1600 3000 584 63920 109.8 0.1%
6000 1600 3000 592 64020 90.83 0.1%
6000 1600 3000 600 64160 87.44 0.1%
6000 1600 3000 608 64080 43.93 0.0%
6000 1600 3000 616 64170 130 0.2%
6000 1600 3000 624 64150 70.63 0.1%
6000 1600 3000 632 64190 48.77 0.0%
6000 1600 3000 640 64260 84.86 0.1%
6000 1600 3000 648 64440 113.4 0.1%
6000 1600 3000 656 64380 97.91 0.1%
6000 1600 3000 664 64510 129.8 0.2%
6000 1600 3000 672 64520 152.7 0.2%
6000 1600 3000 680 64670 88.86 0.1%
6000 1600 3000 688 64590 44.74 0.0%
6000 1600 3000 696 64680 94.49 0.1%
6000 1600 3000 704 64750 119.2 0.1%
6000 1600 3000 712 64590 91.39 0.1%
6000 1600 3000 720 64700 39.37 0.0%
6000 1600 3000 728 64710 67.39 0.1%
6000 1600 3000 736 64630 119 0.1%
6000 1600 3000 744 64690 86.62 0.1%
6000 1600 3000 752 64500 68.72 0.1%
6000 1600 3000 760 64720 120.6 0.1%
6000 1600 3000 768 64630 87.71 0.1%
6000 1600 3000 776 64700 81.41 0.1%
6000 1600 3000 784 64800 95.25 0.1%
6000 1600 3000 792 64840 67.09 0.1%
6000 1600 3000 800 64660 92.25 0.1%

Quality and confidence:
param error
v 0.02
t 0.066
a 0.02
d 0.1

Model:
Time ~= 0
+ v 3.81
+ t 0
+ a 13.58
+ d 4.713
µs

Reads = 6 + (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 3.847
+ t 0.257
+ a 10
+ d 5.829
µs

Reads = 3 + (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 46230 78.55 0.1%
4040 1600 3000 800 46400 35.32 0.0%
4080 1600 3000 800 46630 55.39 0.1%
4120 1600 3000 800 46590 75.67 0.1%
4160 1600 3000 800 46860 80.61 0.1%
4200 1600 3000 800 46970 84.76 0.1%
4240 1600 3000 800 47190 54.85 0.1%
4280 1600 3000 800 47340 53.27 0.1%
4320 1600 3000 800 47420 66.46 0.1%
4360 1600 3000 800 47560 57.73 0.1%
4400 1600 3000 800 47690 69.11 0.1%
4440 1600 3000 800 47880 55.71 0.1%
4480 1600 3000 800 48050 39.38 0.0%
4520 1600 3000 800 48180 53.85 0.1%
4560 1600 3000 800 48390 47.36 0.0%
4600 1600 3000 800 48560 30.26 0.0%
4640 1600 3000 800 48650 21.81 0.0%
4680 1600 3000 800 48770 53.89 0.1%
4720 1600 3000 800 48940 85.65 0.1%
4760 1600 3000 800 49150 41.89 0.0%
4800 1600 3000 800 49280 34.65 0.0%
4840 1600 3000 800 49440 41.31 0.0%
4880 1600 3000 800 49590 81.2 0.1%
4920 1600 3000 800 49720 74.91 0.1%
4960 1600 3000 800 49910 66.31 0.1%
5000 1600 3000 800 50110 40.76 0.0%
5040 1600 3000 800 50210 63.75 0.1%
5080 1600 3000 800 50450 49.27 0.0%
5120 1600 3000 800 50570 56.95 0.1%
5160 1600 3000 800 50650 45.14 0.0%
5200 1600 3000 800 50800 102.8 0.2%
5240 1600 3000 800 51060 54.11 0.1%
5280 1600 3000 800 51130 54.32 0.1%
5320 1600 3000 800 51260 59.73 0.1%
5360 1600 3000 800 51490 57.32 0.1%
5400 1600 3000 800 51490 56.95 0.1%
5440 1600 3000 800 51760 66.36 0.1%
5480 1600 3000 800 51850 95.95 0.1%
5520 1600 3000 800 52080 37.54 0.0%
5560 1600 3000 800 52210 58.65 0.1%
5600 1600 3000 800 52380 36.2 0.0%
5640 1600 3000 800 52510 68.63 0.1%
5680 1600 3000 800 52640 88.79 0.1%
5720 1600 3000 800 52840 93.31 0.1%
5760 1600 3000 800 52940 68.22 0.1%
5800 1600 3000 800 53050 107.7 0.2%
5840 1600 3000 800 53240 59.43 0.1%
5880 1600 3000 800 53500 46.42 0.0%
5920 1600 3000 800 53630 62.38 0.1%
5960 1600 3000 800 53800 62.09 0.1%
6000 1000 3000 800 53870 53.45 0.0%
6000 1012 3000 800 53680 130.5 0.2%
6000 1024 3000 800 53830 68.4 0.1%
6000 1036 3000 800 53790 108.6 0.2%
6000 1048 3000 800 53720 81.1 0.1%
6000 1060 3000 800 53880 34.6 0.0%
6000 1072 3000 800 53790 114.9 0.2%
6000 1084 3000 800 53920 70.84 0.1%
6000 1096 3000 800 53720 60.83 0.1%
6000 1108 3000 800 53810 109 0.2%
6000 1120 3000 800 53830 76.4 0.1%
6000 1132 3000 800 53750 81.04 0.1%
6000 1144 3000 800 53780 47.29 0.0%
6000 1156 3000 800 53800 70.26 0.1%
6000 1168 3000 800 53780 91.19 0.1%
6000 1180 3000 800 53730 85.84 0.1%
6000 1192 3000 800 53780 47.6 0.0%
6000 1204 3000 800 53890 88.25 0.1%
6000 1216 3000 800 53830 49.93 0.0%
6000 1228 3000 800 53870 107.7 0.1%
6000 1240 3000 800 53740 111.5 0.2%
6000 1252 3000 800 53900 78.08 0.1%
6000 1264 3000 800 53720 82.89 0.1%
6000 1276 3000 800 53890 75.1 0.1%
6000 1288 3000 800 53900 83.29 0.1%
6000 1300 3000 800 53840 85.92 0.1%
6000 1312 3000 800 53980 53.79 0.0%
6000 1324 3000 800 53950 109.1 0.2%
6000 1336 3000 800 53870 58.07 0.1%
6000 1348 3000 800 53940 86.59 0.1%
6000 1360 3000 800 53830 92.32 0.1%
6000 1372 3000 800 53800 72.86 0.1%
6000 1384 3000 800 53790 112.4 0.2%
6000 1396 3000 800 53970 55.55 0.1%
6000 1408 3000 800 53930 86.94 0.1%
6000 1420 3000 800 53930 47.98 0.0%
6000 1432 3000 800 53940 125.8 0.2%
6000 1444 3000 800 53920 66.15 0.1%
6000 1456 3000 800 53790 100 0.1%
6000 1468 3000 800 53940 103.8 0.1%
6000 1480 3000 800 53820 79.41 0.1%
6000 1492 3000 800 53820 98.2 0.1%
6000 1504 3000 800 53870 102.4 0.1%
6000 1516 3000 800 53990 68.39 0.1%
6000 1528 3000 800 53920 88.43 0.1%
6000 1540 3000 800 53840 62 0.1%
6000 1552 3000 800 53980 80.34 0.1%
6000 1564 3000 800 53970 86.61 0.1%
6000 1576 3000 800 53960 85.54 0.1%
6000 1588 3000 800 53880 68.2 0.1%
6000 1600 1000 800 33810 65.09 0.1%
6000 1600 1040 800 34250 73.58 0.2%
6000 1600 1080 800 34640 85.91 0.2%
6000 1600 1120 800 35020 86.36 0.2%
6000 1600 1160 800 35430 106.7 0.3%
6000 1600 1200 800 35840 45.38 0.1%
6000 1600 1240 800 36190 99.21 0.2%
6000 1600 1280 800 36510 58.7 0.1%
6000 1600 1320 800 36940 55.37 0.1%
6000 1600 1360 800 37430 68.84 0.1%
6000 1600 1400 800 37790 75.64 0.2%
6000 1600 1440 800 38230 113 0.2%
6000 1600 1480 800 38580 103.5 0.2%
6000 1600 1520 800 39150 116.7 0.2%
6000 1600 1560 800 39510 57.14 0.1%
6000 1600 1600 800 39960 113.4 0.2%
6000 1600 1640 800 40450 87.02 0.2%
6000 1600 1680 800 40860 91.67 0.2%
6000 1600 1720 800 41280 104.6 0.2%
6000 1600 1760 800 41640 64.61 0.1%
6000 1600 1800 800 42160 60.04 0.1%
6000 1600 1840 800 42450 83.85 0.1%
6000 1600 1880 800 42860 82.92 0.1%
6000 1600 1920 800 43310 90.18 0.2%
6000 1600 1960 800 43700 107.2 0.2%
6000 1600 2000 800 44150 87.86 0.1%
6000 1600 2040 800 44590 68.59 0.1%
6000 1600 2080 800 44960 105.2 0.2%
6000 1600 2120 800 45330 67.7 0.1%
6000 1600 2160 800 45720 76.94 0.1%
6000 1600 2200 800 46160 129.8 0.2%
6000 1600 2240 800 46550 31.92 0.0%
6000 1600 2280 800 46830 79.4 0.1%
6000 1600 2320 800 47140 97.63 0.2%
6000 1600 2360 800 47670 70 0.1%
6000 1600 2400 800 47870 116.9 0.2%
6000 1600 2440 800 48300 87.77 0.1%
6000 1600 2480 800 48720 91.97 0.1%
6000 1600 2520 800 49070 60.41 0.1%
6000 1600 2560 800 49340 115 0.2%
6000 1600 2600 800 49860 62.65 0.1%
6000 1600 2640 800 50140 96.77 0.1%
6000 1600 2680 800 50550 50.61 0.1%
6000 1600 2720 800 50950 56.45 0.1%
6000 1600 2760 800 51440 95.1 0.1%
6000 1600 2800 800 51870 122.1 0.2%
6000 1600 2840 800 52100 64.64 0.1%
6000 1600 2880 800 52610 128.1 0.2%
6000 1600 2920 800 53010 102.7 0.1%
6000 1600 2960 800 53470 78.95 0.1%
6000 1600 3000 400 52130 128.7 0.2%
6000 1600 3000 408 52020 79.84 0.1%
6000 1600 3000 416 51930 89.42 0.1%
6000 1600 3000 424 51960 97.39 0.1%
6000 1600 3000 432 51890 80.62 0.1%
6000 1600 3000 440 51940 93.24 0.1%
6000 1600 3000 448 51890 51.79 0.0%
6000 1600 3000 456 52190 104.1 0.1%
6000 1600 3000 464 52270 68.37 0.1%
6000 1600 3000 472 52120 79.38 0.1%
6000 1600 3000 480 52400 71.29 0.1%
6000 1600 3000 488 52480 70.64 0.1%
6000 1600 3000 496 52480 108.3 0.2%
6000 1600 3000 504 52720 92.53 0.1%
6000 1600 3000 512 52870 57.37 0.1%
6000 1600 3000 520 52890 102.5 0.1%
6000 1600 3000 528 52950 114.6 0.2%
6000 1600 3000 536 53110 67.02 0.1%
6000 1600 3000 544 53180 119.2 0.2%
6000 1600 3000 552 53260 57.42 0.1%
6000 1600 3000 560 53290 95.07 0.1%
6000 1600 3000 568 53330 101.5 0.1%
6000 1600 3000 576 53410 90.15 0.1%
6000 1600 3000 584 53490 84.9 0.1%
6000 1600 3000 592 53520 126.6 0.2%
6000 1600 3000 600 53610 124.6 0.2%
6000 1600 3000 608 53740 88.85 0.1%
6000 1600 3000 616 53730 126.7 0.2%
6000 1600 3000 624 53760 96.34 0.1%
6000 1600 3000 632 53850 51.22 0.0%
6000 1600 3000 640 53830 105 0.1%
6000 1600 3000 648 53840 82.11 0.1%
6000 1600 3000 656 53720 68.12 0.1%
6000 1600 3000 664 53690 46.69 0.0%
6000 1600 3000 672 53910 43.18 0.0%
6000 1600 3000 680 54010 92.15 0.1%
6000 1600 3000 688 54140 98.47 0.1%
6000 1600 3000 696 54150 51.89 0.0%
6000 1600 3000 704 54020 109.8 0.2%
6000 1600 3000 712 54120 115.4 0.2%
6000 1600 3000 720 54050 84.58 0.1%
6000 1600 3000 728 54090 118.1 0.2%
6000 1600 3000 736 54060 87.11 0.1%
6000 1600 3000 744 54080 77.09 0.1%
6000 1600 3000 752 54070 75.16 0.1%
6000 1600 3000 760 54020 87.28 0.1%
6000 1600 3000 768 53940 80.24 0.1%
6000 1600 3000 776 53970 108.4 0.2%
6000 1600 3000 784 54010 77.29 0.1%
6000 1600 3000 792 54160 75.13 0.1%
6000 1600 3000 800 53950 86.97 0.1%

Quality and confidence:
param error
v 0.011
t 0.037
a 0.011
d 0.055

Model:
Time ~= 0
+ v 3.973
+ t 0.618
+ a 10.11
+ d 4.482
µs

Reads = 3 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Westend Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=westend-dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/westend/src/weights/

Results

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

-- Extrinsic Time --

Model:
Time ~= 81.49
µs

Reads = 5
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 81.49
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 ~= 65.71
µs

Reads = 4
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 65.71
µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 59.92
µs

Reads = 5
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 59.92
µs

Reads = 5
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 59.33
+ s 0.032
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 58.72 0.082 0.1%
2 58.87 0.073 0.1%
4 59.39 0.131 0.2%
6 59.64 0.202 0.3%
8 59.53 0.064 0.1%
10 59.49 0.155 0.2%
12 59.61 0.11 0.1%
14 59.8 0.132 0.2%
16 59.8 0.104 0.1%
18 59.77 0.07 0.1%
20 60.2 0.141 0.2%
22 59.85 0.119 0.1%
24 60.09 0.164 0.2%
26 60.14 0.117 0.1%
28 60.21 0.125 0.2%
30 60.67 0.1 0.1%
32 60.7 0.165 0.2%
34 60.83 0.132 0.2%
36 60.58 0.18 0.2%
38 60.88 0.151 0.2%
40 60.38 0.16 0.2%
42 60.69 0.129 0.2%
44 60.75 0.204 0.3%
46 61.42 0.19 0.3%
48 60.86 0.107 0.1%
50 60.65 0.182 0.3%
52 60.4 0.139 0.2%
54 60.85 0.163 0.2%
56 61.87 0.515 0.8%
58 60.94 0.13 0.2%
60 60.89 0.128 0.2%
62 61.42 0.167 0.2%
64 61.48 0.168 0.2%
66 62 0.214 0.3%
68 61.68 0.152 0.2%
70 61.98 0.203 0.3%
72 61.95 0.106 0.1%
74 61.9 0.217 0.3%
76 61.89 0.137 0.2%
78 61.7 0.158 0.2%
80 61.78 0.132 0.2%
82 62.07 0.188 0.3%
84 62.03 0.137 0.2%
86 61.59 0.131 0.2%
88 62.38 0.131 0.2%
90 61.86 0.063 0.1%
92 62.22 0.136 0.2%
94 62.23 0.143 0.2%
96 61.77 0.146 0.2%
98 62.35 0.14 0.2%
100 62.29 0.163 0.2%

Quality and confidence:
param error
s 0

Model:
Time ~= 59.32
+ s 0.032
µs

Reads = 5 + (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 ~= 93.31
+ s 2.783
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 88.46 0.189 0.2%
2 98.63 0.24 0.2%
4 104.3 0.143 0.1%
6 110.1 0.173 0.1%
8 115.5 0.149 0.1%
10 120.9 0.126 0.1%
12 127.2 0.211 0.1%
14 132.1 0.147 0.1%
16 138.1 0.219 0.1%
18 143.6 0.272 0.1%
20 149.1 0.089 0.0%
22 154 0.275 0.1%
24 160.6 0.326 0.2%
26 166.6 0.329 0.1%
28 171.2 0.322 0.1%
30 177.2 0.343 0.1%
32 181.8 0.321 0.1%
34 188.1 0.199 0.1%
36 194.2 0.221 0.1%
38 198.8 0.271 0.1%
40 205.4 0.45 0.2%
42 209.9 0.499 0.2%
44 215.6 0.231 0.1%
46 221.3 0.181 0.0%
48 227.3 0.201 0.0%
50 232.2 0.297 0.1%
52 237.7 0.33 0.1%
54 242.7 0.233 0.0%
56 249.1 0.327 0.1%
58 254.4 0.651 0.2%
60 259.4 0.503 0.1%
62 265.4 0.365 0.1%
64 271.4 0.119 0.0%
66 277 0.727 0.2%
68 281.7 0.667 0.2%
70 286.8 0.695 0.2%
72 292.7 0.441 0.1%
74 299.7 1.385 0.4%
76 305.9 0.703 0.2%
78 309.6 0.493 0.1%
80 316.3 0.276 0.0%
82 319.8 0.458 0.1%
84 326.9 0.427 0.1%
86 331.9 0.699 0.2%
88 339.3 0.747 0.2%
90 343.4 0.711 0.2%
92 350.5 0.85 0.2%
94 355 0.907 0.2%
96 361 0.355 0.0%
98 366.4 1.067 0.2%
100 372.6 0.51 0.1%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 92.96
+ s 2.788
µs

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

-- Extrinsic Time --

Model:
Time ~= 19.66
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 19.66
µs

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

-- Extrinsic Time --

Model:
Time ~= 17.33
+ k 19.4
µs

Reads = 2 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
k mean µs sigma µs %
1 44.89 0.107 0.2%
3 85.07 0.146 0.1%
5 122.1 0.25 0.2%
7 158.7 0.341 0.2%
9 196.4 0.429 0.2%
11 234.6 0.445 0.1%
13 271.7 0.47 0.1%
15 309.1 0.776 0.2%
17 346.9 0.426 0.1%
19 387.9 0.753 0.1%
21 424 1.074 0.2%
23 463.8 0.86 0.1%
25 500.4 0.685 0.1%
27 541.6 1.318 0.2%
29 575.8 1.52 0.2%
31 614.7 1.466 0.2%
33 654.8 2.267 0.3%
35 692.8 1.788 0.2%
37 731.8 1.695 0.2%
39 769.1 1.528 0.1%
41 803 2.008 0.2%
43 843.2 1.737 0.2%
45 885.2 5.08 0.5%
47 923.1 1.43 0.1%
49 963.2 2.125 0.2%
51 1006 1.93 0.1%
53 1043 3.302 0.3%
55 1075 2.233 0.2%
57 1115 2.249 0.2%
59 1159 2.527 0.2%
61 1195 5.626 0.4%
63 1231 3.356 0.2%
65 1285 7.978 0.6%
67 1318 1.864 0.1%
69 1350 2.757 0.2%
71 1389 5.41 0.3%
73 1430 5.366 0.3%
75 1472 5.021 0.3%
77 1506 8.426 0.5%
79 1551 4.21 0.2%
81 1581 5.844 0.3%
83 1623 4.633 0.2%
85 1664 10.38 0.6%
87 1700 4.262 0.2%
89 1782 8.867 0.4%
91 1788 10.98 0.6%
93 1812 6.696 0.3%
95 1846 2.648 0.1%
97 1896 6.879 0.3%
99 1940 9.122 0.4%
101 1975 6.561 0.3%
103 2014 7.637 0.3%
105 2066 13.79 0.6%
107 2102 8.002 0.3%
109 2155 17.2 0.7%
111 2192 13.31 0.6%
113 2226 10.76 0.4%
115 2253 12.31 0.5%
117 2299 10.77 0.4%
119 2368 18.09 0.7%
121 2410 11.39 0.4%
123 2411 7.207 0.2%
125 2462 9.952 0.4%
127 2486 6.257 0.2%

Quality and confidence:
param error
k 0.013

Model:
Time ~= 12.19
+ k 19.52
µs

Reads = 2 + (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 ~= 30.25
+ n 6.042
µs

Reads = 4 + (1 * n)
Writes = 2 + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 35.65 0.172 0.4%
2 42.52 0.105 0.2%
3 47.98 0.137 0.2%
4 54.37 0.149 0.2%
5 60.66 0.113 0.1%
6 66.85 0.094 0.1%
7 72.49 0.172 0.2%
8 77.38 0.265 0.3%
9 84.61 0.077 0.0%
10 91.45 0.077 0.0%
11 97.78 0.242 0.2%
12 102.7 0.23 0.2%
13 108 0.47 0.4%
14 115.5 0.454 0.3%
15 120.3 0.341 0.2%
16 125.7 0.372 0.2%

Quality and confidence:
param error
n 0.011

Model:
Time ~= 30.23
+ n 6.033
µs

Reads = 4 + (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 ~= 19.03
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 19.03
µs

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

-- Extrinsic Time --

Model:
Time ~= 12.63
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 12.63
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 ~= 28.21
µs

Reads = 3
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 28.21
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 ~= 2.227
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.227
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 ~= 2.471
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.471
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 ~= 2.474
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.474
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 ~= 2.498
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.498
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 ~= 2.582
+ v 0.034
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
0 2.482 0.024 0.9%
20 3.394 0.018 0.5%
40 4.103 0.021 0.5%
60 4.785 0.014 0.2%
80 5.455 0.024 0.4%
100 6.12 0.01 0.1%
120 6.775 0.011 0.1%
140 7.521 0.027 0.3%
160 8.187 0.017 0.2%
180 8.856 0.031 0.3%
200 9.572 0.028 0.2%
220 10.21 0.048 0.4%
240 10.88 0.029 0.2%
260 11.59 0.029 0.2%
280 12.31 0.028 0.2%
300 12.92 0.011 0.0%
320 13.67 0.046 0.3%
340 14.64 0.022 0.1%
360 15.01 0.024 0.1%
380 15.63 0.019 0.1%
400 16.43 0.109 0.6%
420 17.05 0.056 0.3%
440 17.69 0.035 0.1%
460 18.43 0.03 0.1%
480 19.2 0.13 0.6%
500 19.81 0.013 0.0%
520 20.71 0.032 0.1%
540 21.35 0.023 0.1%
560 22.03 0.048 0.2%
580 22.73 0.05 0.2%
600 23.44 0.031 0.1%
620 24.14 0.063 0.2%
640 24.9 0.055 0.2%
660 25.57 0.027 0.1%
680 26.26 0.033 0.1%
700 26.91 0.025 0.0%
720 27.65 0.031 0.1%
740 28.3 0.023 0.0%
760 28.98 0.013 0.0%
780 29.82 0.042 0.1%
800 30.44 0.034 0.1%
820 31.12 0.024 0.0%
840 31.85 0.043 0.1%
860 32.53 0.038 0.1%
880 33.19 0.034 0.1%
900 34.03 0.044 0.1%
920 34.71 0.031 0.0%
940 35.34 0.042 0.1%
960 36.05 0.028 0.0%
980 36.71 0.034 0.0%
1000 37.37 0.026 0.0%

Quality and confidence:
param error
v 0

Model:
Time ~= 2.574
+ v 0.035
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 ~= 63.15
+ s 2.773
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 58.72 0.568 0.9%
2 67.89 0.109 0.1%
4 74.26 0.127 0.1%
6 79.37 0.155 0.1%
8 84.97 0.17 0.2%
10 90.47 0.138 0.1%
12 96.31 0.106 0.1%
14 102.3 0.199 0.1%
16 107.8 0.165 0.1%
18 113.5 0.196 0.1%
20 118.9 0.165 0.1%
22 124.4 0.23 0.1%
24 130.4 0.094 0.0%
26 137.3 1.402 1.0%
28 141.4 0.279 0.1%
30 146.6 0.243 0.1%
32 151.9 0.271 0.1%
34 157.4 0.229 0.1%
36 162.9 0.252 0.1%
38 168.1 0.191 0.1%
40 174.5 0.132 0.0%
42 180.3 0.233 0.1%
44 185.1 0.268 0.1%
46 190.5 0.241 0.1%
48 196.6 0.208 0.1%
50 201.7 0.405 0.2%
52 206.9 0.342 0.1%
54 212.6 0.336 0.1%
56 220.9 1.923 0.8%
58 223.3 0.281 0.1%
60 229.1 0.753 0.3%
62 234.8 0.365 0.1%
64 240.4 0.362 0.1%
66 246.3 0.316 0.1%
68 251.7 0.48 0.1%
70 257.2 0.214 0.0%
72 262.7 0.3 0.1%
74 267.8 0.567 0.2%
76 273.4 0.324 0.1%
78 278.9 0.309 0.1%
80 285.3 1.267 0.4%
82 291 1.049 0.3%
84 295.1 0.473 0.1%
86 300.8 0.424 0.1%
88 306.7 0.51 0.1%
90 311.8 0.442 0.1%
92 318 0.389 0.1%
94 323.7 0.467 0.1%
96 329.9 0.419 0.1%
98 336.4 0.222 0.0%
100 342 0.545 0.1%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 62.94
+ s 2.777
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 6689
+ s 34.77
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 439.1 0.588 0.1%
20 1735 12.51 0.7%
39 3010 12.25 0.4%
58 4256 5.241 0.1%
77 5483 14.39 0.2%
96 6687 8.906 0.1%
115 7842 8.592 0.1%
134 8999 14.22 0.1%
153 10110 12.27 0.1%
172 11230 12.23 0.1%
191 12290 13.31 0.1%
210 13330 21.07 0.1%
229 14340 9.548 0.0%
248 15360 23.15 0.1%
267 16310 17.55 0.1%
286 17270 19.34 0.1%
305 18190 22.8 0.1%
324 19090 13.34 0.0%
343 19950 19.36 0.0%
362 20810 16.94 0.0%
381 21620 22.35 0.1%
400 22420 10 0.0%
419 23200 12.95 0.0%
438 23960 27.69 0.1%
457 24670 29.56 0.1%
476 25370 16.03 0.0%
495 26030 11.76 0.0%
514 26670 29.71 0.1%
533 27290 11.08 0.0%
552 27870 22.25 0.0%
571 28470 17.37 0.0%
590 29010 27.41 0.0%
609 29530 12.7 0.0%
628 30030 21.53 0.0%
647 30500 17.99 0.0%
666 30960 27.35 0.0%
685 31370 17.8 0.0%
704 31790 24.5 0.0%
723 32150 12.49 0.0%
742 32730 282 0.8%
761 32850 33.23 0.1%
780 33110 16.48 0.0%
799 33400 29.04 0.0%
818 33630 20.24 0.0%
837 33890 18.48 0.0%
856 34080 23.36 0.0%
875 34240 14.57 0.0%
894 34420 18.28 0.0%
913 34500 21.26 0.0%
932 34640 34.96 0.1%
951 34710 30.3 0.0%
970 35180 324.7 0.9%
989 34760 12.32 0.0%

Quality and confidence:
param error
s 0.388

Model:
Time ~= 5907
+ s 34.79
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 ~= 109.9
+ n 53.38
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 161 0.502 0.3%
2 213.7 0.543 0.2%
3 274.7 7.367 2.6%
4 325.4 1.105 0.3%
5 377.3 0.677 0.1%
6 428.8 0.551 0.1%
7 480.1 0.973 0.2%
8 537.9 0.903 0.1%
9 587.7 1.823 0.3%
10 636.7 1.124 0.1%
11 694.4 1.69 0.2%
12 749.2 8.434 1.1%
13 803.6 0.954 0.1%
14 860.6 1.523 0.1%
15 917.9 10.11 1.1%
16 960.9 3.282 0.3%
17 1015 2.224 0.2%
18 1074 4.947 0.4%
19 1123 6.046 0.5%
20 1180 3.348 0.2%
21 1228 5.394 0.4%
22 1283 2.632 0.2%
23 1336 8.223 0.6%
24 1389 2.928 0.2%
25 1451 11.01 0.7%
26 1498 4.377 0.2%
27 1552 8.34 0.5%
28 1605 5.531 0.3%
29 1655 6.782 0.4%
30 1708 9.092 0.5%
31 1761 4.018 0.2%
32 1830 8.367 0.4%
33 1877 7.96 0.4%
34 1922 7.958 0.4%
35 1996 9.248 0.4%
36 2042 8.506 0.4%
37 2083 8.128 0.3%
38 2189 15.28 0.6%
39 2197 6.98 0.3%
40 2252 10.35 0.4%
41 2310 8.54 0.3%
42 2351 9.41 0.4%
43 2420 11.34 0.4%
44 2473 11.19 0.4%
45 2527 8.741 0.3%
46 2569 9.709 0.3%
47 2627 18.2 0.6%
48 2678 18.91 0.7%
49 2729 9.213 0.3%
50 2770 11.83 0.4%
51 2830 10.08 0.3%
52 2898 12.86 0.4%
53 2934 7.738 0.2%
54 2997 8.622 0.2%
55 3061 11.87 0.3%
56 3100 8.268 0.2%
57 3165 12.5 0.3%
58 3202 13.79 0.4%
59 3255 11.33 0.3%
60 3323 7.231 0.2%
61 3350 10.54 0.3%
62 3438 15.44 0.4%
63 3446 11.85 0.3%
64 3533 8.801 0.2%

Quality and confidence:
param error
n 0.027

Model:
Time ~= 110
+ n 53.47
µs

Reads = 11 + (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 ~= 141
+ n 66.54
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 204.5 0.606 0.2%
2 274 0.482 0.1%
3 342 0.903 0.2%
4 404 1.749 0.4%
5 472.7 1.198 0.2%
6 539 1.507 0.2%
7 603.6 0.97 0.1%
8 676.4 1.782 0.2%
9 742.6 5.209 0.7%
10 808.5 1.851 0.2%
11 869.4 2.968 0.3%
12 941 5.535 0.5%
13 1003 3.038 0.3%
14 1063 3.508 0.3%
15 1134 5.6 0.4%
16 1198 6.472 0.5%
17 1267 2.921 0.2%
18 1337 9.89 0.7%
19 1400 5.699 0.4%
20 1480 9.559 0.6%
21 1531 6.946 0.4%
22 1594 2.811 0.1%
23 1671 3.972 0.2%
24 1781 14.82 0.8%
25 1828 16.45 0.9%
26 1867 7.374 0.3%
27 1947 9.319 0.4%
28 1993 7.017 0.3%
29 2072 11.81 0.5%
30 2137 9.698 0.4%
31 2205 14.76 0.6%
32 2271 8.941 0.3%
33 2341 7.004 0.2%
34 2410 12.61 0.5%
35 2472 10.08 0.4%
36 2529 9.216 0.3%
37 2596 10.91 0.4%
38 2676 8.28 0.3%
39 2742 10.98 0.4%
40 2803 7.26 0.2%
41 2881 10.37 0.3%
42 2952 9.785 0.3%
43 3033 8.351 0.2%
44 3073 10.46 0.3%
45 3125 3.869 0.1%
46 3223 7.765 0.2%
47 3298 15.06 0.4%
48 3347 11.63 0.3%
49 3427 10.04 0.2%
50 3475 14.13 0.4%
51 3545 11.09 0.3%
52 3626 7.924 0.2%
53 3739 10.7 0.2%
54 3735 8.527 0.2%
55 3790 5.482 0.1%
56 3873 14.09 0.3%
57 3932 9.897 0.2%
58 3995 9.212 0.2%
59 4042 14.83 0.3%
60 4129 9.35 0.2%
61 4187 7.355 0.1%
62 4279 18.91 0.4%
63 4349 9.666 0.2%
64 4378 10.06 0.2%

Quality and confidence:
param error
n 0.036

Model:
Time ~= 139.9
+ n 66.69
µs

Reads = 12 + (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 ~= 40.65
+ l 0.082
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
l mean µs sigma µs %
1 40.81 0.126 0.3%
2 40.66 0.098 0.2%
3 40.59 0.105 0.2%
4 40.55 0.072 0.1%
5 41.11 0.177 0.4%
6 40.99 0.088 0.2%
7 41.02 0.088 0.2%
8 41.01 0.08 0.1%
9 41.53 0.042 0.1%
10 41.52 0.107 0.2%
11 41.52 0.042 0.1%
12 41.88 0.117 0.2%
13 41.91 0.118 0.2%
14 41.83 0.098 0.2%
15 41.9 0.098 0.2%
16 41.88 0.09 0.2%
17 42.48 0.072 0.1%
18 42.63 0.092 0.2%
19 42.59 0.093 0.2%
20 42.6 0.076 0.1%
21 42.66 0.1 0.2%
22 42.72 0.079 0.1%
23 42.78 0.123 0.2%
24 42.64 0.087 0.2%
25 42.83 0.075 0.1%
26 42.88 0.085 0.1%
27 42.79 0.083 0.1%
28 42.85 0.066 0.1%
29 42.77 0.076 0.1%
30 42.88 0.047 0.1%
31 42.85 0.077 0.1%
32 42.85 0.074 0.1%

Quality and confidence:
param error
l 0.001

Model:
Time ~= 40.65
+ l 0.083
µs

Reads = 4 + (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 34.4
µs

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

-- Extrinsic Time --

Data points distribution:
e mean µs sigma µs %
1 41.19 0.151 0.3%
2 68.37 0.12 0.1%
3 93.77 0.235 0.2%
4 121.5 0.328 0.2%
5 148.3 0.378 0.2%
6 173.7 1.21 0.6%
7 200.7 0.533 0.2%
8 225.6 0.504 0.2%
9 252.1 0.701 0.2%
10 282.1 0.409 0.1%
11 309.3 0.83 0.2%
12 336.6 1.31 0.3%
13 363.8 0.72 0.1%
14 394.2 0.961 0.2%
15 421.2 0.784 0.1%
16 450.4 0.508 0.1%
17 481.6 1.067 0.2%
18 510.3 1.248 0.2%
19 537.3 1.769 0.3%
20 570.7 1.133 0.1%
21 599.2 2.217 0.3%
22 627.8 1.237 0.1%
23 659.8 1.658 0.2%
24 686.6 1.471 0.2%
25 719 1.46 0.2%
26 747.1 2.259 0.3%
27 778.7 2.912 0.3%
28 819.1 3.55 0.4%
29 844 2.653 0.3%
30 872.4 0.641 0.0%
31 903.7 1.863 0.2%
32 944.9 3.876 0.4%
33 964.4 2.294 0.2%
34 1011 5.21 0.5%
35 1030 2.852 0.2%
36 1066 1.841 0.1%
37 1101 4.401 0.3%
38 1135 3.476 0.3%
39 1162 3.656 0.3%
40 1196 2.899 0.2%
41 1234 5.407 0.4%
42 1250 5.249 0.4%
43 1290 3.777 0.2%
44 1332 3.554 0.2%
45 1378 13.04 0.9%
46 1411 8.946 0.6%
47 1443 7.076 0.4%
48 1465 5.888 0.4%
49 1503 5.404 0.3%
50 1538 7.402 0.4%
51 1580 3.733 0.2%
52 1601 11.91 0.7%
53 1641 8.894 0.5%
54 1677 5.409 0.3%
55 1708 7.304 0.4%
56 1731 7.108 0.4%
57 1780 8.757 0.4%
58 1821 7.34 0.4%
59 1866 8.719 0.4%
60 1896 4.527 0.2%
61 1928 7.849 0.4%
62 1953 5.252 0.2%
63 2013 6.158 0.3%
64 2031 12.95 0.6%
65 2047 9.46 0.4%
66 2099 7.48 0.3%
67 2144 4.992 0.2%
68 2164 9.325 0.4%
69 2219 5.277 0.2%
70 2254 8.559 0.3%
71 2282 7.395 0.3%
72 2336 7.73 0.3%
73 2371 5.891 0.2%
74 2404 8.194 0.3%
75 2457 10.56 0.4%
76 2479 8.892 0.3%
77 2508 8.604 0.3%
78 2557 9.864 0.3%
79 2592 9.824 0.3%
80 2613 9.161 0.3%
81 2672 11.65 0.4%
82 2728 8.944 0.3%
83 2762 5.553 0.2%
84 2822 8.946 0.3%
85 2819 11.8 0.4%
86 2896 10.27 0.3%
87 2928 11.04 0.3%
88 2951 13.09 0.4%
89 3021 6.33 0.2%
90 3042 10.62 0.3%
91 3099 4.875 0.1%
92 3148 10.31 0.3%
93 3175 7.28 0.2%
94 3204 13.9 0.4%
95 3240 14.08 0.4%
96 3311 8.708 0.2%
97 3324 10.1 0.3%
98 3378 9.598 0.2%
99 3404 11.32 0.3%
100 3428 8.515 0.2%

Quality and confidence:
param error
e 0.066

Model:
Time ~= 0
+ e 34.57
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 ~= 66.28
+ s 2.773
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 68.07 0.158 0.2%
2 70.92 0.177 0.2%
3 73.79 0.089 0.1%
4 77.33 0.171 0.2%
5 80.14 0.144 0.1%
6 82.91 0.084 0.1%
7 85.49 0.251 0.2%
8 88.18 0.122 0.1%
9 90.96 0.141 0.1%
10 93.52 0.137 0.1%
11 96.28 0.145 0.1%
12 99.38 0.092 0.0%
13 102.6 0.183 0.1%
14 105.4 0.172 0.1%
15 108.2 0.127 0.1%
16 110.9 0.187 0.1%
17 113.4 0.121 0.1%
18 116.6 0.129 0.1%
19 119.3 0.201 0.1%
20 121.8 0.184 0.1%
21 124.8 0.284 0.2%
22 127.4 0.182 0.1%
23 130.2 0.163 0.1%
24 133.3 0.206 0.1%
25 136.4 0.211 0.1%
26 138.9 0.147 0.1%
27 141.5 0.16 0.1%
28 144.4 0.274 0.1%
29 146.9 0.294 0.2%
30 150.1 0.329 0.2%
31 153.2 0.883 0.5%
32 155.6 0.389 0.2%
33 157.5 0.215 0.1%
34 160.8 0.254 0.1%
35 163.5 0.325 0.1%
36 165.9 0.173 0.1%
37 168.6 0.222 0.1%
38 171.8 0.281 0.1%
39 174.4 0.238 0.1%
40 177.3 0.335 0.1%
41 180 0.306 0.1%
42 182.9 0.397 0.2%
43 185.4 0.276 0.1%
44 188.4 0.331 0.1%
45 191.2 0.156 0.0%
46 193.8 0.381 0.1%
47 197.5 1.289 0.6%
48 199.5 0.187 0.0%
49 202.1 0.22 0.1%
50 204.3 0.31 0.1%
51 207 0.221 0.1%
52 210.1 0.247 0.1%
53 213.1 0.395 0.1%
54 216 0.28 0.1%
55 219.8 0.946 0.4%
56 221.2 0.376 0.1%
57 224.4 0.382 0.1%
58 226.7 0.547 0.2%
59 229.9 0.334 0.1%
60 232.1 0.251 0.1%
61 235.1 0.362 0.1%
62 238 0.521 0.2%
63 241.1 0.465 0.1%
64 243.5 0.282 0.1%
65 246.7 0.625 0.2%
66 249.4 0.366 0.1%
67 252 0.414 0.1%
68 254.7 0.342 0.1%
69 257.4 0.481 0.1%
70 259.8 0.452 0.1%
71 262.6 0.362 0.1%
72 265.5 0.513 0.1%
73 267.9 0.235 0.0%
74 271.4 0.214 0.0%
75 274.6 0.432 0.1%
76 276.5 0.353 0.1%
77 279.3 0.465 0.1%
78 282.5 0.651 0.2%
79 285.1 0.361 0.1%
80 287.4 0.326 0.1%
81 292 2.002 0.6%
82 293.6 0.571 0.1%
83 296.2 0.246 0.0%
84 298.5 0.596 0.1%
85 301.8 0.629 0.2%
86 304 0.3 0.0%
87 307.1 0.394 0.1%
88 309.4 0.374 0.1%
89 313.1 1.117 0.3%
90 314.7 0.653 0.2%
91 318.3 0.429 0.1%
92 321.7 0.289 0.0%
93 325.4 1.044 0.3%
94 328.3 0.562 0.1%
95 329.8 0.24 0.0%
96 334 0.394 0.1%
97 336.8 0.525 0.1%
98 339.8 0.344 0.1%
99 342.8 0.405 0.1%
100 344.3 0.561 0.1%

Quality and confidence:
param error
s 0

Model:
Time ~= 66.19
+ s 2.776
µs

Reads = 4 + (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 568.1
+ n 83.64
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n mean µs sigma µs %
1 100 3832 15.59 0.4%
2 100 4429 14.94 0.3%
3 100 4902 16.12 0.3%
4 100 5433 8.754 0.1%
5 100 6020 7.959 0.1%
6 100 6571 10.05 0.1%
7 100 7076 9.221 0.1%
8 100 7668 12.94 0.1%
9 100 8388 12.77 0.1%
10 1 762.5 2.117 0.2%
10 2 825.4 14.81 1.7%
10 3 897.9 2.793 0.3%
10 4 976.3 2.854 0.2%
10 5 1073 13.03 1.2%
10 6 1155 16.05 1.3%
10 7 1262 2.316 0.1%
10 8 1354 6.155 0.4%
10 9 1435 3.486 0.2%
10 10 1525 2.709 0.1%
10 11 1608 10.72 0.6%
10 12 1691 11.57 0.6%
10 13 1776 10.13 0.5%
10 14 1860 16.95 0.9%
10 15 1928 5.143 0.2%
10 16 2012 4.286 0.2%
10 17 2093 4.269 0.2%
10 18 2150 13.44 0.6%
10 19 2251 2.813 0.1%
10 20 2350 13.8 0.5%
10 21 2437 2.721 0.1%
10 22 2501 13.89 0.5%
10 23 2590 11.92 0.4%
10 24 2667 11.14 0.4%
10 25 2757 13.95 0.5%
10 26 2840 10.35 0.3%
10 27 2915 9.445 0.3%
10 28 3008 13.88 0.4%
10 29 3078 12.28 0.3%
10 30 3160 10.74 0.3%
10 31 3255 12.09 0.3%
10 32 3342 11.24 0.3%
10 33 3436 17.24 0.5%
10 34 3535 9.481 0.2%
10 35 3604 3.326 0.0%
10 36 3673 15.89 0.4%
10 37 3771 4.81 0.1%
10 38 3859 10.53 0.2%
10 39 3943 10.6 0.2%
10 40 4049 11.65 0.2%
10 41 4124 16.33 0.3%
10 42 4207 6.863 0.1%
10 43 4275 10.8 0.2%
10 44 4368 12.02 0.2%
10 45 4437 14.86 0.3%
10 46 4521 9.793 0.2%
10 47 4626 10.41 0.2%
10 48 4701 11.98 0.2%
10 49 4758 14.61 0.3%
10 50 4832 7.983 0.1%
10 51 4994 12.86 0.2%
10 52 5061 20.07 0.3%
10 53 5077 10.64 0.2%
10 54 5181 15.64 0.3%
10 55 5251 9.058 0.1%
10 56 5351 10.16 0.1%
10 57 5457 14.19 0.2%
10 58 5523 6.23 0.1%
10 59 5593 6.627 0.1%
10 60 5723 8.828 0.1%
10 61 5778 6.679 0.1%
10 62 5867 7.551 0.1%
10 63 5943 16.51 0.2%
10 64 6060 12.48 0.2%
10 65 6140 11.98 0.1%
10 66 6224 12.33 0.1%
10 67 6338 6.998 0.1%
10 68 6382 11.63 0.1%
10 69 6495 8.88 0.1%
10 70 6562 6.518 0.0%
10 71 6651 11.07 0.1%
10 72 6714 11.15 0.1%
10 73 6792 8.25 0.1%
10 74 6863 10.05 0.1%
10 75 6942 10.64 0.1%
10 76 7048 12.29 0.1%
10 77 7092 5.814 0.0%
10 78 7212 6.119 0.0%
10 79 7315 13.58 0.1%
10 80 7402 15.29 0.2%
10 81 7450 4.65 0.0%
10 82 7543 8.18 0.1%
10 83 7628 12.72 0.1%
10 84 7711 10.83 0.1%
10 85 7758 9.755 0.1%
10 86 7882 15.69 0.1%
10 87 7971 8.359 0.1%
10 88 8026 10.62 0.1%
10 89 8115 11.13 0.1%
10 90 8171 9.605 0.1%
10 91 8246 12.4 0.1%
10 92 8343 11.98 0.1%
10 93 8434 14.56 0.1%
10 94 8530 9.38 0.1%
10 95 8571 9.617 0.1%
10 96 8671 14.89 0.1%
10 97 8809 52.24 0.5%
10 98 8890 41.85 0.4%
10 99 8917 14.68 0.1%
10 100 8964 11.74 0.1%

Quality and confidence:
param error
v 0.866
n 0.043

Model:
Time ~= 0
+ v 589
+ n 83.39
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "submit_solution_better", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 1.025
+ n 0.583
+ a 76.79
+ w 7.973
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n a w mean µs sigma µs %
200 1000 400 100 31670 62.62 0.1%
204 1000 400 100 31700 72.16 0.2%
208 1000 400 100 31630 63.57 0.2%
212 1000 400 100 31640 81.78 0.2%
216 1000 400 100 31750 81.33 0.2%
220 1000 400 100 31800 94.93 0.2%
224 1000 400 100 31730 56.64 0.1%
228 1000 400 100 31610 32.07 0.1%
232 1000 400 100 31730 41.69 0.1%
236 1000 400 100 31730 42.74 0.1%
240 1000 400 100 31590 61.93 0.1%
244 1000 400 100 31650 61.06 0.1%
248 1000 400 100 31750 38.57 0.1%
252 1000 400 100 31870 69.68 0.2%
256 1000 400 100 31800 35.35 0.1%
260 1000 400 100 31760 67.43 0.2%
264 1000 400 100 31810 74.09 0.2%
268 1000 400 100 31850 42.95 0.1%
272 1000 400 100 31770 60.55 0.1%
276 1000 400 100 31610 40.27 0.1%
280 1000 400 100 31740 81.41 0.2%
284 1000 400 100 31680 114.5 0.3%
288 1000 400 100 31870 63.15 0.1%
292 1000 400 100 31790 47.37 0.1%
296 1000 400 100 31830 57.67 0.1%
300 1000 400 100 31680 57.14 0.1%
304 1000 400 100 31820 33.14 0.1%
308 1000 400 100 31640 53.03 0.1%
312 1000 400 100 31890 66.09 0.2%
316 1000 400 100 31610 50.22 0.1%
320 1000 400 100 31750 36.86 0.1%
324 1000 400 100 31700 75.48 0.2%
328 1000 400 100 31680 61.43 0.1%
332 1000 400 100 31870 49.18 0.1%
336 1000 400 100 31920 80.01 0.2%
340 1000 400 100 31930 57.02 0.1%
344 1000 400 100 31880 61.34 0.1%
348 1000 400 100 31730 36.43 0.1%
352 1000 400 100 31900 74.5 0.2%
356 1000 400 100 32000 51.42 0.1%
360 1000 400 100 31840 65.49 0.2%
364 1000 400 100 31790 77.55 0.2%
368 1000 400 100 31740 40.23 0.1%
372 1000 400 100 31780 40.96 0.1%
376 1000 400 100 31970 58.9 0.1%
380 1000 400 100 31900 44.31 0.1%
384 1000 400 100 31940 48.75 0.1%
388 1000 400 100 31840 78.73 0.2%
392 1000 400 100 31780 79.74 0.2%
396 1000 400 100 31880 73.14 0.2%
400 500 400 100 31480 98.05 0.3%
400 510 400 100 31460 63.6 0.2%
400 520 400 100 31690 47.25 0.1%
400 530 400 100 31620 51.39 0.1%
400 540 400 100 31650 76.93 0.2%
400 550 400 100 31700 52.59 0.1%
400 560 400 100 31590 82.33 0.2%
400 570 400 100 31690 31.5 0.0%
400 580 400 100 31540 35.21 0.1%
400 590 400 100 31650 77.31 0.2%
400 600 400 100 31600 28.86 0.0%
400 610 400 100 31610 92.09 0.2%
400 620 400 100 31730 61.17 0.1%
400 630 400 100 31740 67.96 0.2%
400 640 400 100 31810 63.74 0.2%
400 650 400 100 31710 67.26 0.2%
400 660 400 100 31690 76.95 0.2%
400 670 400 100 31800 56.03 0.1%
400 680 400 100 31730 58.03 0.1%
400 690 400 100 31810 73.77 0.2%
400 700 400 100 31650 75.97 0.2%
400 710 400 100 31720 34.57 0.1%
400 720 400 100 31680 131.4 0.4%
400 730 400 100 31660 60.21 0.1%
400 740 400 100 31710 65.74 0.2%
400 750 400 100 31790 41.63 0.1%
400 760 400 100 31890 48.95 0.1%
400 770 400 100 31810 50.81 0.1%
400 780 400 100 31870 77.73 0.2%
400 790 400 100 31580 38.62 0.1%
400 800 400 100 31850 63.19 0.1%
400 810 400 100 31900 60.73 0.1%
400 820 400 100 31700 51.53 0.1%
400 830 400 100 31700 41.46 0.1%
400 840 400 100 31800 58.13 0.1%
400 850 400 100 31690 40.48 0.1%
400 860 400 100 31920 38.25 0.1%
400 870 400 100 31860 71.3 0.2%
400 880 400 100 31900 55.27 0.1%
400 890 400 100 31890 81.09 0.2%
400 900 400 100 31890 111.9 0.3%
400 910 400 100 31840 58.27 0.1%
400 920 400 100 31730 54.9 0.1%
400 930 400 100 31770 78.61 0.2%
400 940 400 100 31860 37.7 0.1%
400 950 400 100 31880 57.34 0.1%
400 960 400 100 31960 56.97 0.1%
400 970 400 100 31860 39.9 0.1%
400 980 400 100 31800 60.24 0.1%
400 990 400 100 31830 48.19 0.1%
400 1000 200 100 16420 19.57 0.1%
400 1000 204 100 16670 29.11 0.1%
400 1000 208 100 17010 49.09 0.2%
400 1000 212 100 17320 43.73 0.2%
400 1000 216 100 17670 39.89 0.2%
400 1000 220 100 18080 40.09 0.2%
400 1000 224 100 18390 30.6 0.1%
400 1000 228 100 18720 58.67 0.3%
400 1000 232 100 19040 18.49 0.0%
400 1000 236 100 19330 33.37 0.1%
400 1000 240 100 19640 25.61 0.1%
400 1000 244 100 19960 36 0.1%
400 1000 248 100 20240 35.13 0.1%
400 1000 252 100 20520 43.75 0.2%
400 1000 256 100 20860 47.72 0.2%
400 1000 260 100 21140 58.61 0.2%
400 1000 264 100 21440 43.17 0.2%
400 1000 268 100 21740 46.66 0.2%
400 1000 272 100 22080 28.87 0.1%
400 1000 276 100 22420 62.47 0.2%
400 1000 280 100 22700 37.53 0.1%
400 1000 284 100 22950 57.21 0.2%
400 1000 288 100 23320 34.82 0.1%
400 1000 292 100 23630 36.57 0.1%
400 1000 296 100 23900 58.51 0.2%
400 1000 300 100 24170 51.1 0.2%
400 1000 304 100 24460 30.34 0.1%
400 1000 308 100 24810 46.01 0.1%
400 1000 312 100 25050 30.16 0.1%
400 1000 316 100 25430 53.57 0.2%
400 1000 320 100 25630 49.32 0.1%
400 1000 324 100 26010 34.05 0.1%
400 1000 328 100 26270 49.68 0.1%
400 1000 332 100 26590 27.5 0.1%
400 1000 336 100 26960 40.53 0.1%
400 1000 340 100 27250 41.71 0.1%
400 1000 344 100 27540 27.69 0.1%
400 1000 348 100 27900 36.43 0.1%
400 1000 352 100 28200 22.9 0.0%
400 1000 356 100 28560 61.19 0.2%
400 1000 360 100 28730 31.44 0.1%
400 1000 364 100 29040 84.28 0.2%
400 1000 368 100 29380 52.58 0.1%
400 1000 372 100 29710 61.95 0.2%
400 1000 376 100 30060 54.74 0.1%
400 1000 380 100 30260 43.32 0.1%
400 1000 384 100 30630 62.57 0.2%
400 1000 388 100 30870 83.42 0.2%
400 1000 392 100 31280 45.8 0.1%
400 1000 396 100 31600 56.78 0.1%
400 1000 400 16 31360 72.57 0.2%
400 1000 400 17 31260 62.43 0.1%
400 1000 400 18 31250 69.63 0.2%
400 1000 400 19 31330 40.79 0.1%
400 1000 400 20 31290 72.16 0.2%
400 1000 400 21 31390 56.52 0.1%
400 1000 400 22 31360 70.26 0.2%
400 1000 400 23 31470 47.72 0.1%
400 1000 400 24 31390 64.97 0.2%
400 1000 400 25 31350 42.35 0.1%
400 1000 400 26 31260 42.67 0.1%
400 1000 400 27 31340 50.07 0.1%
400 1000 400 28 31250 49.96 0.1%
400 1000 400 29 31470 58.12 0.1%
400 1000 400 30 31300 75.29 0.2%
400 1000 400 31 31390 53.83 0.1%
400 1000 400 32 31370 52.41 0.1%
400 1000 400 33 31220 46.21 0.1%
400 1000 400 34 31470 35.48 0.1%
400 1000 400 35 31270 70.55 0.2%
400 1000 400 36 31330 61.41 0.1%
400 1000 400 37 31470 74.36 0.2%
400 1000 400 38 31450 64.45 0.2%
400 1000 400 39 31520 73.18 0.2%
400 1000 400 40 31470 43.31 0.1%
400 1000 400 41 31510 75.39 0.2%
400 1000 400 42 31620 64.93 0.2%
400 1000 400 43 31650 40.95 0.1%
400 1000 400 44 31680 57.96 0.1%
400 1000 400 45 31630 83.84 0.2%
400 1000 400 46 31520 30.52 0.0%
400 1000 400 47 31510 60.77 0.1%
400 1000 400 48 31480 55.59 0.1%
400 1000 400 49 31710 68.43 0.2%
400 1000 400 50 31560 71.52 0.2%
400 1000 400 51 31540 76.9 0.2%
400 1000 400 52 31390 42.34 0.1%
400 1000 400 53 31600 50.45 0.1%
400 1000 400 54 31430 41.56 0.1%
400 1000 400 55 31590 74.88 0.2%
400 1000 400 56 31580 106.4 0.3%
400 1000 400 57 31590 46.06 0.1%
400 1000 400 58 31530 82.26 0.2%
400 1000 400 59 31390 36.61 0.1%
400 1000 400 60 31540 70.08 0.2%
400 1000 400 61 31670 59.73 0.1%
400 1000 400 62 31700 65.77 0.2%
400 1000 400 63 31570 46.23 0.1%
400 1000 400 64 31490 63.08 0.2%
400 1000 400 65 31640 47.05 0.1%
400 1000 400 66 31590 61.47 0.1%
400 1000 400 67 31670 61.09 0.1%
400 1000 400 68 31620 43.1 0.1%
400 1000 400 69 31730 45.84 0.1%
400 1000 400 70 31520 35.57 0.1%
400 1000 400 71 31720 62.97 0.1%
400 1000 400 72 31570 57.11 0.1%
400 1000 400 73 31720 47.82 0.1%
400 1000 400 74 31770 54.43 0.1%
400 1000 400 75 31850 78.24 0.2%
400 1000 400 76 31830 82.62 0.2%
400 1000 400 77 31880 68.42 0.2%
400 1000 400 78 31610 48.68 0.1%
400 1000 400 79 31840 71.47 0.2%
400 1000 400 80 31810 79.36 0.2%
400 1000 400 81 31790 40.57 0.1%
400 1000 400 82 31830 79.44 0.2%
400 1000 400 83 31990 59.37 0.1%
400 1000 400 84 31900 49.71 0.1%
400 1000 400 85 32020 73.7 0.2%
400 1000 400 86 31980 59.28 0.1%
400 1000 400 87 31970 88.53 0.2%
400 1000 400 88 31800 62.19 0.1%
400 1000 400 89 31760 34.34 0.1%
400 1000 400 90 31930 46.87 0.1%
400 1000 400 91 31860 98.38 0.3%
400 1000 400 92 31890 91.65 0.2%
400 1000 400 93 31860 73.02 0.2%
400 1000 400 94 31950 50.58 0.1%
400 1000 400 95 31800 75.87 0.2%
400 1000 400 96 31850 70.27 0.2%
400 1000 400 97 31880 64.79 0.2%
400 1000 400 98 32060 35.62 0.1%
400 1000 400 99 31870 53.84 0.1%
400 1000 400 100 31900 71.86 0.2%

Quality and confidence:
param error
v 0.049
n 0.019
a 0.049
w 0.103

Model:
Time ~= 0
+ v 1.193
+ n 0.613
+ a 77.07
+ w 7.277
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 29.33
+ n 68.47
+ s 29.24
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n s mean µs sigma µs %
200 400 20 33050 39.55 0.1%
204 400 20 32680 80.22 0.2%
208 400 20 32820 55.91 0.1%
212 400 20 32730 43.22 0.1%
216 400 20 32910 27.79 0.0%
220 400 20 33330 55.14 0.1%
224 400 20 33220 62.68 0.1%
228 400 20 33390 78.21 0.2%
232 400 20 33570 58.88 0.1%
236 400 20 33720 57.83 0.1%
240 400 20 33890 47.81 0.1%
244 400 20 33790 78.78 0.2%
248 400 20 34050 78.88 0.2%
252 400 20 34070 64.25 0.1%
256 400 20 34180 52.2 0.1%
260 400 20 34070 68.19 0.2%
264 400 20 34220 61.89 0.1%
268 400 20 34800 74.94 0.2%
272 400 20 34630 62.43 0.1%
276 400 20 34590 52.06 0.1%
280 400 20 35220 105.6 0.3%
284 400 20 35110 81.51 0.2%
288 400 20 35290 61.95 0.1%
292 400 20 35230 81.55 0.2%
296 400 20 35360 104.7 0.2%
300 400 20 35210 118.5 0.3%
304 400 20 35460 29.18 0.0%
308 400 20 35810 50.67 0.1%
312 400 20 35970 113.3 0.3%
316 400 20 36340 115.1 0.3%
320 400 20 36220 75.19 0.2%
324 400 20 36450 70.02 0.1%
328 400 20 36070 75.64 0.2%
332 400 20 36460 78.65 0.2%
336 400 20 36710 55.91 0.1%
340 400 20 36910 92.56 0.2%
344 400 20 36930 57.05 0.1%
348 400 20 37150 90.17 0.2%
352 400 20 37260 114.9 0.3%
356 400 20 36720 59.87 0.1%
360 400 20 37320 135.4 0.3%
364 400 20 37450 77.5 0.2%
368 400 20 37700 61.99 0.1%
372 400 20 37600 130.2 0.3%
376 400 20 37710 117.4 0.3%
380 400 20 37750 92.5 0.2%
384 400 20 38030 74.61 0.1%
388 400 20 37680 67.86 0.1%
392 400 20 38010 69.75 0.1%
396 400 20 38450 125 0.3%
400 200 20 24580 79.11 0.3%
400 204 20 24820 58.36 0.2%
400 208 20 25400 82.85 0.3%
400 212 20 25560 63.99 0.2%
400 216 20 25920 68.37 0.2%
400 220 20 26110 35.57 0.1%
400 224 20 26420 60.39 0.2%
400 228 20 26480 20.96 0.0%
400 232 20 27000 117.2 0.4%
400 236 20 27390 34.84 0.1%
400 240 20 27590 62.73 0.2%
400 244 20 27800 85.57 0.3%
400 248 20 28060 42.39 0.1%
400 252 20 28300 84.63 0.2%
400 256 20 28460 66.73 0.2%
400 260 20 28490 61.65 0.2%
400 264 20 29170 58.51 0.2%
400 268 20 29430 92.17 0.3%
400 272 20 29640 46.66 0.1%
400 276 20 29900 73.71 0.2%
400 280 20 30080 80.9 0.2%
400 284 20 30650 93.15 0.3%
400 288 20 30770 100.7 0.3%
400 292 20 31200 62.69 0.2%
400 296 20 31080 86.81 0.2%
400 300 20 31720 52.35 0.1%
400 304 20 31930 75.77 0.2%
400 308 20 32230 79.41 0.2%
400 312 20 32090 71.68 0.2%
400 316 20 32300 57.2 0.1%
400 320 20 33170 66.55 0.2%
400 324 20 32900 56.38 0.1%
400 328 20 33250 65.82 0.1%
400 332 20 33960 127.9 0.3%
400 336 20 34170 98.29 0.2%
400 340 20 34590 130.2 0.3%
400 344 20 34180 34.49 0.1%
400 348 20 35120 62.52 0.1%
400 352 20 34840 78.34 0.2%
400 356 20 35390 53.19 0.1%
400 360 20 35790 109.6 0.3%
400 364 20 36040 85.93 0.2%
400 368 20 36130 58.76 0.1%
400 372 20 36500 115.8 0.3%
400 376 20 36760 66.85 0.1%
400 380 20 37010 88.88 0.2%
400 384 20 37500 87.47 0.2%
400 388 20 37210 63.38 0.1%
400 392 20 38020 74.36 0.1%
400 396 20 37990 169.2 0.4%
400 400 1 38010 147 0.3%
400 400 2 38030 97.96 0.2%
400 400 3 37830 146.6 0.3%
400 400 4 38040 78.61 0.2%
400 400 5 38190 173.5 0.4%
400 400 6 37960 128.7 0.3%
400 400 7 38090 72.65 0.1%
400 400 8 37940 128.1 0.3%
400 400 9 38070 63.84 0.1%
400 400 10 38280 67.75 0.1%
400 400 11 38270 64.06 0.1%
400 400 12 38150 108.8 0.2%
400 400 13 38460 82.07 0.2%
400 400 14 38170 191.6 0.5%
400 400 15 38290 123.7 0.3%
400 400 16 38310 90.82 0.2%
400 400 17 38480 141.9 0.3%
400 400 18 38420 72.68 0.1%
400 400 19 38410 111 0.2%
400 400 20 38500 82.63 0.2%

Quality and confidence:
param error
v 0.108
n 0.108
s 1.48

Model:
Time ~= 0
+ v 29.04
+ n 68.55
+ s 25.44
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * 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 ~= 0
+ v 10.87
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
200 2047 4.515 0.2%
204 2094 11.72 0.5%
208 2196 16.22 0.7%
212 2193 18.55 0.8%
216 2217 9.805 0.4%
220 2303 14.14 0.6%
224 2313 21.03 0.9%
228 2381 18.44 0.7%
232 2388 13.99 0.5%
236 2501 12.41 0.4%
240 2472 11.58 0.4%
244 2543 9.999 0.3%
248 2626 11.5 0.4%
252 2635 11.24 0.4%
256 2661 21.22 0.7%
260 2702 27.27 1.0%
264 2814 18.72 0.6%
268 2764 20.92 0.7%
272 2799 13.24 0.4%
276 2887 22.81 0.7%
280 2945 9.782 0.3%
284 3009 20.68 0.6%
288 2997 17.89 0.5%
292 3036 19.63 0.6%
296 3146 17.48 0.5%
300 3107 25.89 0.8%
304 3225 19.22 0.5%
308 3272 18.53 0.5%
312 3293 14.37 0.4%
316 3264 22.98 0.7%
320 3359 23.41 0.6%
324 3401 19.13 0.5%
328 3486 14.7 0.4%
332 3484 16.11 0.4%
336 3541 30.28 0.8%
340 3577 15.7 0.4%
344 3606 14.34 0.3%
348 3674 23.69 0.6%
352 3730 33.15 0.8%
356 3765 18 0.4%
360 3809 19.53 0.5%
364 3852 19.41 0.5%
368 3916 23.41 0.5%
372 3908 23.59 0.6%
376 3905 36.66 0.9%
380 4029 20.76 0.5%
384 4050 29.43 0.7%
388 4129 18.48 0.4%
392 4118 35.94 0.8%
396 4232 17.29 0.4%
400 4268 22.34 0.5%

Quality and confidence:
param error
v 0.026

Model:
Time ~= 0
+ v 10.85
µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Polkadot Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=polkadot-dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/polkadot/src/weights/

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 ~= 20.66
µs

Reads = 7
Writes = 0
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 20.66
µs

Reads = 7
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 ~= 96.26
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 96.26
µs

Reads = 8
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 ~= 96.27
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 96.27
µs

Reads = 8
Writes = 4
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 ~= 18.79
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 18.79
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 ~= 7329
µs

Reads = 2
Writes = 6
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 7329
µs

Reads = 2
Writes = 6
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 3.927
+ t 0.286
+ a 12.6
+ d 7.153
µs

Reads = 6 + (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 55890 125.3 0.2%
4040 1600 3000 800 55980 104.5 0.1%
4080 1600 3000 800 56230 83.75 0.1%
4120 1600 3000 800 56350 68 0.1%
4160 1600 3000 800 56560 141.5 0.2%
4200 1600 3000 800 56620 89.08 0.1%
4240 1600 3000 800 56770 105.8 0.1%
4280 1600 3000 800 56970 77.17 0.1%
4320 1600 3000 800 57100 72.58 0.1%
4360 1600 3000 800 57230 128.1 0.2%
4400 1600 3000 800 57340 104 0.1%
4440 1600 3000 800 57660 118 0.2%
4480 1600 3000 800 57700 120.8 0.2%
4520 1600 3000 800 57780 60.15 0.1%
4560 1600 3000 800 58010 62.82 0.1%
4600 1600 3000 800 58190 99.14 0.1%
4640 1600 3000 800 58380 105.6 0.1%
4680 1600 3000 800 58400 137.6 0.2%
4720 1600 3000 800 58640 123.9 0.2%
4760 1600 3000 800 58760 76.38 0.1%
4800 1600 3000 800 58970 144.9 0.2%
4840 1600 3000 800 59080 55.28 0.0%
4880 1600 3000 800 59270 148.9 0.2%
4920 1600 3000 800 59430 106.9 0.1%
4960 1600 3000 800 59590 84.52 0.1%
5000 1600 3000 800 59700 81.6 0.1%
5040 1600 3000 800 59840 118.6 0.1%
5080 1600 3000 800 60060 74.29 0.1%
5120 1600 3000 800 60210 85.39 0.1%
5160 1600 3000 800 60320 108.2 0.1%
5200 1600 3000 800 60540 79.64 0.1%
5240 1600 3000 800 60600 130.9 0.2%
5280 1600 3000 800 60930 110.5 0.1%
5320 1600 3000 800 61010 74.73 0.1%
5360 1600 3000 800 61150 61.31 0.1%
5400 1600 3000 800 61250 114.1 0.1%
5440 1600 3000 800 61480 64.77 0.1%
5480 1600 3000 800 61520 123 0.2%
5520 1600 3000 800 61730 106.4 0.1%
5560 1600 3000 800 61940 116.9 0.1%
5600 1600 3000 800 62130 105.8 0.1%
5640 1600 3000 800 62080 95.79 0.1%
5680 1600 3000 800 62510 112.3 0.1%
5720 1600 3000 800 62610 140.9 0.2%
5760 1600 3000 800 62820 121.4 0.1%
5800 1600 3000 800 62900 102.1 0.1%
5840 1600 3000 800 62970 80.41 0.1%
5880 1600 3000 800 63130 56.26 0.0%
5920 1600 3000 800 63370 109.1 0.1%
5960 1600 3000 800 63520 62.79 0.0%
6000 1000 3000 800 63570 88.76 0.1%
6000 1012 3000 800 63640 110.2 0.1%
6000 1024 3000 800 63580 147 0.2%
6000 1036 3000 800 63580 135.2 0.2%
6000 1048 3000 800 63490 158.4 0.2%
6000 1060 3000 800 63680 120.3 0.1%
6000 1072 3000 800 63600 125.6 0.1%
6000 1084 3000 800 63620 87.88 0.1%
6000 1096 3000 800 63390 105.9 0.1%
6000 1108 3000 800 63720 71.53 0.1%
6000 1120 3000 800 63610 72.56 0.1%
6000 1132 3000 800 63700 142 0.2%
6000 1144 3000 800 63570 141.2 0.2%
6000 1156 3000 800 63590 97.08 0.1%
6000 1168 3000 800 63610 116.4 0.1%
6000 1180 3000 800 63500 76.49 0.1%
6000 1192 3000 800 63540 145 0.2%
6000 1204 3000 800 63690 78.39 0.1%
6000 1216 3000 800 63610 94.76 0.1%
6000 1228 3000 800 63740 110.2 0.1%
6000 1240 3000 800 63600 80.04 0.1%
6000 1252 3000 800 63660 64.62 0.1%
6000 1264 3000 800 63620 111.5 0.1%
6000 1276 3000 800 63750 113.3 0.1%
6000 1288 3000 800 63580 71.91 0.1%
6000 1300 3000 800 63560 60.35 0.0%
6000 1312 3000 800 63720 129.2 0.2%
6000 1324 3000 800 63770 109.9 0.1%
6000 1336 3000 800 63510 118.2 0.1%
6000 1348 3000 800 63570 87.89 0.1%
6000 1360 3000 800 63690 152 0.2%
6000 1372 3000 800 63700 122.3 0.1%
6000 1384 3000 800 63540 98.67 0.1%
6000 1396 3000 800 63700 111.8 0.1%
6000 1408 3000 800 63770 128.8 0.2%
6000 1420 3000 800 63710 93.36 0.1%
6000 1432 3000 800 63620 87.12 0.1%
6000 1444 3000 800 63760 102 0.1%
6000 1456 3000 800 63640 162 0.2%
6000 1468 3000 800 63760 157.6 0.2%
6000 1480 3000 800 63580 139.3 0.2%
6000 1492 3000 800 63780 86.12 0.1%
6000 1504 3000 800 63620 63.44 0.0%
6000 1516 3000 800 63740 91.05 0.1%
6000 1528 3000 800 63640 140.4 0.2%
6000 1540 3000 800 63660 128.6 0.2%
6000 1552 3000 800 63650 147.8 0.2%
6000 1564 3000 800 63800 106.3 0.1%
6000 1576 3000 800 63760 132.1 0.2%
6000 1588 3000 800 63700 90.5 0.1%
6000 1600 1000 800 37510 61.1 0.1%
6000 1600 1040 800 38160 40.31 0.1%
6000 1600 1080 800 38500 60.3 0.1%
6000 1600 1120 800 38970 45.76 0.1%
6000 1600 1160 800 39540 55 0.1%
6000 1600 1200 800 39860 71.75 0.1%
6000 1600 1240 800 40370 55.34 0.1%
6000 1600 1280 800 40800 86.84 0.2%
6000 1600 1320 800 41310 55.11 0.1%
6000 1600 1360 800 41730 104.5 0.2%
6000 1600 1400 800 43000 41.28 0.0%
6000 1600 1440 800 43600 92.82 0.2%
6000 1600 1480 800 44090 78.3 0.1%
6000 1600 1520 800 44570 79.1 0.1%
6000 1600 1560 800 45150 52.64 0.1%
6000 1600 1600 800 45640 51.16 0.1%
6000 1600 1640 800 46110 73.85 0.1%
6000 1600 1680 800 46700 44.12 0.0%
6000 1600 1720 800 47070 118.8 0.2%
6000 1600 1760 800 47530 102.1 0.2%
6000 1600 1800 800 48160 89.83 0.1%
6000 1600 1840 800 48660 79.14 0.1%
6000 1600 1880 800 49130 69.08 0.1%
6000 1600 1920 800 49590 82.51 0.1%
6000 1600 1960 800 50030 62.38 0.1%
6000 1600 2000 800 50550 124.6 0.2%
6000 1600 2040 800 51000 61.46 0.1%
6000 1600 2080 800 51560 45.87 0.0%
6000 1600 2120 800 51990 64.47 0.1%
6000 1600 2160 800 52490 62.55 0.1%
6000 1600 2200 800 52900 77.51 0.1%
6000 1600 2240 800 53250 49.25 0.0%
6000 1600 2280 800 53740 69.36 0.1%
6000 1600 2320 800 54070 124.6 0.2%
6000 1600 2360 800 54660 61.27 0.1%
6000 1600 2400 800 55080 72.92 0.1%
6000 1600 2440 800 55570 100.4 0.1%
6000 1600 2480 800 55950 79.05 0.1%
6000 1600 2520 800 56390 36.8 0.0%
6000 1600 2560 800 56830 69.73 0.1%
6000 1600 2600 800 57160 122.4 0.2%
6000 1600 2640 800 57740 71.98 0.1%
6000 1600 2680 800 58200 97.89 0.1%
6000 1600 2720 800 58620 108 0.1%
6000 1600 2760 800 59180 57.77 0.0%
6000 1600 2800 800 59710 51.1 0.0%
6000 1600 2840 800 60270 60.68 0.1%
6000 1600 2880 800 62350 84.27 0.1%
6000 1600 2920 800 62930 66.97 0.1%
6000 1600 2960 800 63370 60.42 0.0%
6000 1600 3000 400 61410 77.85 0.1%
6000 1600 3000 408 61460 103.3 0.1%
6000 1600 3000 416 61300 74.21 0.1%
6000 1600 3000 424 61460 81.64 0.1%
6000 1600 3000 432 61400 69.15 0.1%
6000 1600 3000 440 61490 89.15 0.1%
6000 1600 3000 448 61480 63.51 0.1%
6000 1600 3000 456 61760 89.72 0.1%
6000 1600 3000 464 61820 121.5 0.1%
6000 1600 3000 472 61890 35.12 0.0%
6000 1600 3000 480 61930 75.54 0.1%
6000 1600 3000 488 62140 25.72 0.0%
6000 1600 3000 496 62130 53.95 0.0%
6000 1600 3000 504 62290 79.78 0.1%
6000 1600 3000 512 62420 75.3 0.1%
6000 1600 3000 520 62550 52.34 0.0%
6000 1600 3000 528 62480 76.64 0.1%
6000 1600 3000 536 62640 43.89 0.0%
6000 1600 3000 544 62660 31.08 0.0%
6000 1600 3000 552 62820 77.34 0.1%
6000 1600 3000 560 62750 68 0.1%
6000 1600 3000 568 62950 70.09 0.1%
6000 1600 3000 576 63030 104.1 0.1%
6000 1600 3000 584 63180 60.11 0.0%
6000 1600 3000 592 63270 70.63 0.1%
6000 1600 3000 600 63230 84.43 0.1%
6000 1600 3000 608 63350 66.92 0.1%
6000 1600 3000 616 63390 137.2 0.2%
6000 1600 3000 624 63490 57.47 0.0%
6000 1600 3000 632 63590 34.19 0.0%
6000 1600 3000 640 63560 69.26 0.1%
6000 1600 3000 648 63640 80.92 0.1%
6000 1600 3000 656 63600 71.06 0.1%
6000 1600 3000 664 63720 88.86 0.1%
6000 1600 3000 672 63750 112.5 0.1%
6000 1600 3000 680 63830 66.28 0.1%
6000 1600 3000 688 63890 78.13 0.1%
6000 1600 3000 696 63800 97.1 0.1%
6000 1600 3000 704 63910 54.81 0.0%
6000 1600 3000 712 63920 79.5 0.1%
6000 1600 3000 720 63900 35.9 0.0%
6000 1600 3000 728 63970 72.05 0.1%
6000 1600 3000 736 63900 83.86 0.1%
6000 1600 3000 744 64020 91.44 0.1%
6000 1600 3000 752 63820 52.8 0.0%
6000 1600 3000 760 63920 73.13 0.1%
6000 1600 3000 768 63840 123.9 0.1%
6000 1600 3000 776 63860 97.01 0.1%
6000 1600 3000 784 64020 30.74 0.0%
6000 1600 3000 792 63990 101.2 0.1%
6000 1600 3000 800 63810 106.7 0.1%

Quality and confidence:
param error
v 0.02
t 0.067
a 0.02
d 0.1

Model:
Time ~= 0
+ v 3.93
+ t 0.154
+ a 13.18
+ d 4.485
µs

Reads = 6 + (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 3.91
+ t 0.137
+ a 9.621
+ d 5.798
µs

Reads = 3 + (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 45550 43.08 0.0%
4040 1600 3000 800 45680 50.38 0.1%
4080 1600 3000 800 45850 68.91 0.1%
4120 1600 3000 800 46050 77.01 0.1%
4160 1600 3000 800 46110 52.35 0.1%
4200 1600 3000 800 46290 54.23 0.1%
4240 1600 3000 800 46450 57.45 0.1%
4280 1600 3000 800 46600 76.25 0.1%
4320 1600 3000 800 46750 64.42 0.1%
4360 1600 3000 800 46880 52.68 0.1%
4400 1600 3000 800 47080 55.93 0.1%
4440 1600 3000 800 47280 68.17 0.1%
4480 1600 3000 800 47400 75.54 0.1%
4520 1600 3000 800 47510 66.67 0.1%
4560 1600 3000 800 47680 89.49 0.1%
4600 1600 3000 800 47840 45.75 0.0%
4640 1600 3000 800 48010 49.97 0.1%
4680 1600 3000 800 48250 41.33 0.0%
4720 1600 3000 800 48410 63.06 0.1%
4760 1600 3000 800 48520 35.61 0.0%
4800 1600 3000 800 48630 59.2 0.1%
4840 1600 3000 800 48780 108.3 0.2%
4880 1600 3000 800 48960 121 0.2%
4920 1600 3000 800 49080 90.02 0.1%
4960 1600 3000 800 49250 68.22 0.1%
5000 1600 3000 800 49540 36.69 0.0%
5040 1600 3000 800 49610 75.74 0.1%
5080 1600 3000 800 49720 68.45 0.1%
5120 1600 3000 800 49900 87.33 0.1%
5160 1600 3000 800 50020 75.9 0.1%
5200 1600 3000 800 50170 40.76 0.0%
5240 1600 3000 800 50310 65.35 0.1%
5280 1600 3000 800 50480 104.8 0.2%
5320 1600 3000 800 50690 80.35 0.1%
5360 1600 3000 800 50820 60.27 0.1%
5400 1600 3000 800 50950 60 0.1%
5440 1600 3000 800 51150 80.77 0.1%
5480 1600 3000 800 51300 80.14 0.1%
5520 1600 3000 800 51360 114.6 0.2%
5560 1600 3000 800 51600 93.56 0.1%
5600 1600 3000 800 51820 79.35 0.1%
5640 1600 3000 800 51860 64.05 0.1%
5680 1600 3000 800 52100 39.06 0.0%
5720 1600 3000 800 52290 37.67 0.0%
5760 1600 3000 800 52460 83.21 0.1%
5800 1600 3000 800 52580 55.96 0.1%
5840 1600 3000 800 52740 74.28 0.1%
5880 1600 3000 800 52890 68.44 0.1%
5920 1600 3000 800 53000 88.31 0.1%
5960 1600 3000 800 53120 93.75 0.1%
6000 1000 3000 800 53380 84.3 0.1%
6000 1012 3000 800 53250 53.62 0.1%
6000 1024 3000 800 53310 49.01 0.0%
6000 1036 3000 800 53430 70.08 0.1%
6000 1048 3000 800 53240 83.38 0.1%
6000 1060 3000 800 53300 86.72 0.1%
6000 1072 3000 800 53400 54.66 0.1%
6000 1084 3000 800 53360 53.29 0.0%
6000 1096 3000 800 53220 78.89 0.1%
6000 1108 3000 800 53270 105.2 0.1%
6000 1120 3000 800 53410 111.6 0.2%
6000 1132 3000 800 53340 59.9 0.1%
6000 1144 3000 800 53300 69 0.1%
6000 1156 3000 800 53320 49.29 0.0%
6000 1168 3000 800 53300 80.62 0.1%
6000 1180 3000 800 53230 69.37 0.1%
6000 1192 3000 800 53300 78.35 0.1%
6000 1204 3000 800 53270 36.68 0.0%
6000 1216 3000 800 53280 68.8 0.1%
6000 1228 3000 800 53310 79.87 0.1%
6000 1240 3000 800 53160 80.35 0.1%
6000 1252 3000 800 53350 104.4 0.1%
6000 1264 3000 800 53320 79.15 0.1%
6000 1276 3000 800 53450 74.61 0.1%
6000 1288 3000 800 53260 85.25 0.1%
6000 1300 3000 800 53220 67.91 0.1%
6000 1312 3000 800 53380 62.92 0.1%
6000 1324 3000 800 53270 95.97 0.1%
6000 1336 3000 800 53290 71.92 0.1%
6000 1348 3000 800 53300 67.6 0.1%
6000 1360 3000 800 53370 91.25 0.1%
6000 1372 3000 800 53320 70.66 0.1%
6000 1384 3000 800 53230 95.72 0.1%
6000 1396 3000 800 53340 65.76 0.1%
6000 1408 3000 800 53360 72.1 0.1%
6000 1420 3000 800 53350 92.63 0.1%
6000 1432 3000 800 53280 102.2 0.1%
6000 1444 3000 800 53370 115.2 0.2%
6000 1456 3000 800 53340 66.56 0.1%
6000 1468 3000 800 53380 70.46 0.1%
6000 1480 3000 800 53260 82.14 0.1%
6000 1492 3000 800 53460 133 0.2%
6000 1504 3000 800 53420 112.3 0.2%
6000 1516 3000 800 53300 106.9 0.2%
6000 1528 3000 800 53420 102.6 0.1%
6000 1540 3000 800 53350 99.07 0.1%
6000 1552 3000 800 53500 75.6 0.1%
6000 1564 3000 800 53380 77.57 0.1%
6000 1576 3000 800 53360 38.98 0.0%
6000 1588 3000 800 53370 51.2 0.0%
6000 1600 1000 800 33910 94.41 0.2%
6000 1600 1040 800 34400 80.05 0.2%
6000 1600 1080 800 34820 65.4 0.1%
6000 1600 1120 800 35270 38.03 0.1%
6000 1600 1160 800 35530 100.4 0.2%
6000 1600 1200 800 36000 45.41 0.1%
6000 1600 1240 800 36350 81.08 0.2%
6000 1600 1280 800 36660 74.95 0.2%
6000 1600 1320 800 37010 73.61 0.1%
6000 1600 1360 800 37690 134.2 0.3%
6000 1600 1400 800 38010 123.4 0.3%
6000 1600 1440 800 38340 91.06 0.2%
6000 1600 1480 800 38640 120.5 0.3%
6000 1600 1520 800 38860 66.18 0.1%
6000 1600 1560 800 39410 60.77 0.1%
6000 1600 1600 800 40010 105.4 0.2%
6000 1600 1640 800 40390 71.94 0.1%
6000 1600 1680 800 40830 77.97 0.1%
6000 1600 1720 800 41510 78.33 0.1%
6000 1600 1760 800 41640 62.25 0.1%
6000 1600 1800 800 42140 63.79 0.1%
6000 1600 1840 800 42430 106 0.2%
6000 1600 1880 800 42890 78.06 0.1%
6000 1600 1920 800 43160 81.47 0.1%
6000 1600 1960 800 43640 118.4 0.2%
6000 1600 2000 800 43950 51.68 0.1%
6000 1600 2040 800 44220 38.61 0.0%
6000 1600 2080 800 44800 92.91 0.2%
6000 1600 2120 800 45070 57.33 0.1%
6000 1600 2160 800 45490 78.22 0.1%
6000 1600 2200 800 45890 71.06 0.1%
6000 1600 2240 800 46120 87.85 0.1%
6000 1600 2280 800 46630 54.9 0.1%
6000 1600 2320 800 46920 73.47 0.1%
6000 1600 2360 800 47210 128.9 0.2%
6000 1600 2400 800 47530 92.29 0.1%
6000 1600 2440 800 47990 59.31 0.1%
6000 1600 2480 800 48330 74.26 0.1%
6000 1600 2520 800 48770 50.45 0.1%
6000 1600 2560 800 49040 93.5 0.1%
6000 1600 2600 800 49480 83.8 0.1%
6000 1600 2640 800 49780 86.98 0.1%
6000 1600 2680 800 50150 94.96 0.1%
6000 1600 2720 800 50480 119 0.2%
6000 1600 2760 800 50930 77.83 0.1%
6000 1600 2800 800 51240 96.53 0.1%
6000 1600 2840 800 51730 50.33 0.0%
6000 1600 2880 800 52120 117.6 0.2%
6000 1600 2920 800 52610 115.7 0.2%
6000 1600 2960 800 53030 107.6 0.2%
6000 1600 3000 400 51440 117.1 0.2%
6000 1600 3000 408 51380 84.27 0.1%
6000 1600 3000 416 51350 78.99 0.1%
6000 1600 3000 424 51480 60.87 0.1%
6000 1600 3000 432 51410 108.3 0.2%
6000 1600 3000 440 51550 86.31 0.1%
6000 1600 3000 448 51550 82.08 0.1%
6000 1600 3000 456 51730 79.09 0.1%
6000 1600 3000 464 51730 137.5 0.2%
6000 1600 3000 472 51790 84.14 0.1%
6000 1600 3000 480 51870 69.86 0.1%
6000 1600 3000 488 51970 80.05 0.1%
6000 1600 3000 496 52030 37.17 0.0%
6000 1600 3000 504 52100 41.6 0.0%
6000 1600 3000 512 52310 66.95 0.1%
6000 1600 3000 520 52260 65.39 0.1%
6000 1600 3000 528 52420 42.41 0.0%
6000 1600 3000 536 52430 122.6 0.2%
6000 1600 3000 544 52520 88.69 0.1%
6000 1600 3000 552 52650 65.28 0.1%
6000 1600 3000 560 52800 54.05 0.1%
6000 1600 3000 568 52770 38.71 0.0%
6000 1600 3000 576 52890 106.2 0.2%
6000 1600 3000 584 52900 80.72 0.1%
6000 1600 3000 592 53020 29.29 0.0%
6000 1600 3000 600 53110 91.38 0.1%
6000 1600 3000 608 53190 87.17 0.1%
6000 1600 3000 616 53210 105.2 0.1%
6000 1600 3000 624 53240 103.7 0.1%
6000 1600 3000 632 53250 58.36 0.1%
6000 1600 3000 640 53250 111.7 0.2%
6000 1600 3000 648 53300 76.94 0.1%
6000 1600 3000 656 53260 85.85 0.1%
6000 1600 3000 664 53400 123.8 0.2%
6000 1600 3000 672 53440 76.79 0.1%
6000 1600 3000 680 53520 75.76 0.1%
6000 1600 3000 688 53510 80.2 0.1%
6000 1600 3000 696 53500 96.67 0.1%
6000 1600 3000 704 53570 72.13 0.1%
6000 1600 3000 712 53480 105.2 0.1%
6000 1600 3000 720 53520 65.43 0.1%
6000 1600 3000 728 53480 95.58 0.1%
6000 1600 3000 736 53350 124.5 0.2%
6000 1600 3000 744 53430 109 0.2%
6000 1600 3000 752 53290 72.12 0.1%
6000 1600 3000 760 53510 74.23 0.1%
6000 1600 3000 768 53370 81.58 0.1%
6000 1600 3000 776 53400 81.26 0.1%
6000 1600 3000 784 53720 130.8 0.2%
6000 1600 3000 792 53540 34.48 0.0%
6000 1600 3000 800 53390 89.64 0.1%

Quality and confidence:
param error
v 0.011
t 0.036
a 0.011
d 0.055

Model:
Time ~= 0
+ v 4.042
+ t 0.497
+ a 9.711
+ d 4.378
µs

Reads = 3 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Polkadot Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=polkadot-dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/polkadot/src/weights/

Results

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

-- Extrinsic Time --

Model:
Time ~= 77.71
µs

Reads = 5
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 77.71
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 ~= 62.57
µs

Reads = 4
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 62.57
µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 57.14
µs

Reads = 5
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 57.14
µs

Reads = 5
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 57.36
+ s 0.033
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 56.79 0.121 0.2%
2 57.2 0.093 0.1%
4 57.21 0.149 0.2%
6 57.49 0.144 0.2%
8 57.39 0.091 0.1%
10 57.5 0.123 0.2%
12 57.63 0.107 0.1%
14 57.71 0.142 0.2%
16 57.86 0.065 0.1%
18 58.1 0.154 0.2%
20 57.89 0.123 0.2%
22 58.18 0.138 0.2%
24 58.28 0.138 0.2%
26 58.17 0.134 0.2%
28 58.14 0.162 0.2%
30 58.04 0.07 0.1%
32 58.68 0.123 0.2%
34 58.83 0.117 0.1%
36 58.82 0.106 0.1%
38 58.82 0.165 0.2%
40 59.35 0.108 0.1%
42 58.67 0.1 0.1%
44 59.09 0.098 0.1%
46 59.27 0.105 0.1%
48 59.59 0.114 0.1%
50 59.09 0.157 0.2%
52 59.22 0.115 0.1%
54 59.18 0.131 0.2%
56 59.58 0.125 0.2%
58 59.28 0.119 0.2%
60 59.38 0.127 0.2%
62 59.51 0.193 0.3%
64 59.94 0.149 0.2%
66 59.71 0.1 0.1%
68 60.05 0.182 0.3%
70 59.77 0.167 0.2%
72 59.95 0.075 0.1%
74 59.99 0.128 0.2%
76 60.29 0.11 0.1%
78 60.06 0.202 0.3%
80 59.97 0.139 0.2%
82 59.99 0.107 0.1%
84 59.71 0.09 0.1%
86 59.96 0.113 0.1%
88 60.23 0.115 0.1%
90 60.33 0.117 0.1%
92 60.24 0.083 0.1%
94 60.05 0.094 0.1%
96 60.44 0.118 0.1%
98 60.38 0.12 0.1%
100 60.38 0.197 0.3%

Quality and confidence:
param error
s 0

Model:
Time ~= 57.37
+ s 0.034
µs

Reads = 5 + (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 ~= 90.78
+ s 2.691
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 85.93 0.161 0.1%
2 95.67 0.113 0.1%
4 101.8 0.302 0.2%
6 106.8 0.189 0.1%
8 112.1 0.15 0.1%
10 117.9 0.195 0.1%
12 123.4 0.143 0.1%
14 128.8 0.151 0.1%
16 133.7 0.154 0.1%
18 139.4 0.316 0.2%
20 144.8 0.331 0.2%
22 150.1 0.221 0.1%
24 155.5 0.409 0.2%
26 161 0.233 0.1%
28 166.9 0.38 0.2%
30 171.4 0.25 0.1%
32 177 0.169 0.0%
34 182.5 0.215 0.1%
36 187.9 0.549 0.2%
38 193.1 0.426 0.2%
40 198.9 0.235 0.1%
42 204 0.586 0.2%
44 209.2 0.438 0.2%
46 214.8 0.282 0.1%
48 220.1 0.431 0.1%
50 225.2 0.388 0.1%
52 230 0.581 0.2%
54 235.6 0.269 0.1%
56 241.6 0.416 0.1%
58 246 0.51 0.2%
60 251.5 0.666 0.2%
62 258 0.384 0.1%
64 263.3 0.435 0.1%
66 267.8 0.4 0.1%
68 273.2 0.336 0.1%
70 280.5 1.858 0.6%
72 284.1 0.468 0.1%
74 290.4 0.559 0.1%
76 295.8 0.456 0.1%
78 299.2 0.353 0.1%
80 305.5 0.478 0.1%
82 311.3 0.349 0.1%
84 316.1 0.468 0.1%
86 320.8 0.679 0.2%
88 326.8 0.535 0.1%
90 331.9 0.743 0.2%
92 338.5 0.376 0.1%
94 344.7 0.97 0.2%
96 349.6 0.317 0.0%
98 356.4 0.594 0.1%
100 361.2 0.633 0.1%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 90.47
+ s 2.696
µs

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

-- Extrinsic Time --

Model:
Time ~= 18.9
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 18.9
µs

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

-- Extrinsic Time --

Model:
Time ~= 17.82
+ k 18.79
µs

Reads = 2 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
k mean µs sigma µs %
1 42.76 0.132 0.3%
3 81.47 0.116 0.1%
5 117.7 0.19 0.1%
7 153.8 0.156 0.1%
9 190.9 0.274 0.1%
11 227.6 0.457 0.2%
13 264.5 0.535 0.2%
15 299.7 0.605 0.2%
17 336.3 0.806 0.2%
19 375.2 0.546 0.1%
21 414.2 0.393 0.0%
23 450.1 0.695 0.1%
25 485.5 0.743 0.1%
27 521.8 0.952 0.1%
29 559.3 0.771 0.1%
31 599.1 1.113 0.1%
33 636.1 1.553 0.2%
35 671 1.578 0.2%
37 710 1.843 0.2%
39 745 1.663 0.2%
41 781 1.925 0.2%
43 817.8 1.524 0.1%
45 857 2.281 0.2%
47 895.9 1.546 0.1%
49 934.1 3.539 0.3%
51 972.3 1.098 0.1%
53 1009 2.567 0.2%
55 1045 1.806 0.1%
57 1112 4.773 0.4%
59 1120 2.134 0.1%
61 1159 2.118 0.1%
63 1200 6.611 0.5%
65 1244 4.1 0.3%
67 1280 9.447 0.7%
69 1315 0.875 0.0%
71 1350 2.852 0.2%
73 1384 2.943 0.2%
75 1424 3.615 0.2%
77 1458 2.61 0.1%
79 1510 11.87 0.7%
81 1538 8.531 0.5%
83 1571 3.462 0.2%
85 1615 11.37 0.7%
87 1651 8.747 0.5%
89 1689 10.08 0.5%
91 1720 5.582 0.3%
93 1764 4.852 0.2%
95 1806 9.797 0.5%
97 1833 10.74 0.5%
99 1875 7.856 0.4%
101 1918 5.463 0.2%
103 1964 13.5 0.6%
105 2008 12.11 0.6%
107 2032 7.687 0.3%
109 2078 13.81 0.6%
111 2118 10.49 0.4%
113 2170 19.01 0.8%
115 2194 13.96 0.6%
117 2232 7.975 0.3%
119 2275 3.662 0.1%
121 2312 12.02 0.5%
123 2340 11.58 0.4%
125 2368 9.548 0.4%
127 2417 12.55 0.5%

Quality and confidence:
param error
k 0.011

Model:
Time ~= 13.88
+ k 18.89
µs

Reads = 2 + (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 ~= 29.09
+ n 5.638
µs

Reads = 4 + (1 * n)
Writes = 2 + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 33.59 0.127 0.3%
2 40.44 0.039 0.0%
3 45.72 0.075 0.1%
4 51.48 0.086 0.1%
5 57.73 0.16 0.2%
6 63.16 0.152 0.2%
7 69.01 0.124 0.1%
8 73.24 0.138 0.1%
9 80.5 0.201 0.2%
10 85.45 0.106 0.1%
11 91.75 0.139 0.1%
12 96.61 0.212 0.2%
13 103 0.321 0.3%
14 107.7 0.345 0.3%
15 113.1 0.162 0.1%
16 117.9 0.222 0.1%

Quality and confidence:
param error
n 0.01

Model:
Time ~= 29.05
+ n 5.63
µs

Reads = 4 + (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 ~= 18.31
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 18.31
µs

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

-- Extrinsic Time --

Model:
Time ~= 12.31
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 12.31
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 ~= 26.91
µs

Reads = 3
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 26.91
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 ~= 2.171
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.171
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 ~= 2.363
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.363
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 ~= 2.376
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.376
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 ~= 2.389
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.389
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 ~= 2.516
+ v 0.036
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
0 2.462 0.022 0.8%
20 3.345 0.015 0.4%
40 4.059 0.013 0.3%
60 4.812 0.012 0.2%
80 5.517 0.021 0.3%
100 6.169 0.009 0.1%
120 6.914 0.025 0.3%
140 7.664 0.014 0.1%
160 8.359 0.015 0.1%
180 9.074 0.012 0.1%
200 9.811 0.01 0.1%
220 10.49 0.01 0.0%
240 11.22 0.028 0.2%
260 12.1 0.083 0.6%
280 12.7 0.029 0.2%
300 13.43 0.016 0.1%
320 14.16 0.015 0.1%
340 14.85 0.016 0.1%
360 15.59 0.012 0.0%
380 16.27 0.02 0.1%
400 17.01 0.019 0.1%
420 17.71 0.015 0.0%
440 18.45 0.024 0.1%
460 19.11 0.022 0.1%
480 19.84 0.02 0.1%
500 20.54 0.021 0.1%
520 21.4 0.019 0.0%
540 22.11 0.025 0.1%
560 22.81 0.026 0.1%
580 23.52 0.023 0.0%
600 24.27 0.019 0.0%
620 24.97 0.024 0.0%
640 25.91 0.038 0.1%
660 27.03 0.231 0.8%
680 27.41 0.042 0.1%
700 28.09 0.036 0.1%
720 28.8 0.016 0.0%
740 29.49 0.021 0.0%
760 30.17 0.021 0.0%
780 30.96 0.031 0.1%
800 31.7 0.026 0.0%
820 32.5 0.187 0.5%
840 33.14 0.027 0.0%
860 33.85 0.03 0.0%
880 34.57 0.032 0.0%
900 35.37 0.021 0.0%
920 36.08 0.021 0.0%
940 36.81 0.037 0.1%
960 37.5 0.022 0.0%
980 38.25 0.03 0.0%
1000 38.9 0.02 0.0%

Quality and confidence:
param error
v 0

Model:
Time ~= 2.507
+ v 0.036
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 ~= 62.17
+ s 2.675
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 58.07 0.366 0.6%
2 66.41 0.077 0.1%
4 72.59 0.079 0.1%
6 77.83 0.161 0.2%
8 83.19 0.099 0.1%
10 88.47 0.119 0.1%
12 94.23 0.076 0.0%
14 99.66 0.078 0.0%
16 104.9 0.138 0.1%
18 110.4 0.118 0.1%
20 115.8 0.129 0.1%
22 121.3 0.143 0.1%
24 127.1 0.141 0.1%
26 132.3 0.151 0.1%
28 137.3 0.075 0.0%
30 142.7 0.117 0.0%
32 151.4 0.171 0.1%
34 156.8 0.258 0.1%
36 158.7 0.137 0.0%
38 163.8 0.191 0.1%
40 169.3 0.247 0.1%
42 174.9 0.243 0.1%
44 180.3 0.212 0.1%
46 185.6 0.165 0.0%
48 190.9 0.202 0.1%
50 195.5 0.236 0.1%
52 200.7 0.148 0.0%
54 206.2 0.261 0.1%
56 211.6 0.153 0.0%
58 217 0.212 0.0%
60 222.1 0.294 0.1%
62 228.1 0.435 0.1%
64 233.4 0.244 0.1%
66 238.5 0.274 0.1%
68 245.8 2.407 0.9%
70 249.2 0.483 0.1%
72 254.5 0.487 0.1%
74 260 0.482 0.1%
76 264.7 0.427 0.1%
78 270.6 0.424 0.1%
80 275.7 0.231 0.0%
82 281.7 0.304 0.1%
84 286.4 0.62 0.2%
86 291.9 0.3 0.1%
88 296.7 0.266 0.0%
90 302.1 0.444 0.1%
92 308.9 0.34 0.1%
94 313.7 0.563 0.1%
96 319.3 0.18 0.0%
98 323.2 0.888 0.2%
100 331 0.528 0.1%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 62.14
+ s 2.677
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 6795
+ s 34.62
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 454.2 0.336 0.0%
20 1751 10.01 0.5%
39 3028 11.46 0.3%
58 4272 10.2 0.2%
77 5508 10.99 0.1%
96 6687 11.43 0.1%
115 7867 9.833 0.1%
134 9011 16.4 0.1%
153 10120 20.15 0.1%
172 11240 15.86 0.1%
191 12310 10.49 0.0%
210 13410 101.4 0.7%
229 14620 78.52 0.5%
248 15370 12.07 0.0%
267 16340 11.14 0.0%
286 17290 11.83 0.0%
305 18220 11.91 0.0%
324 19100 17.19 0.0%
343 20270 276.5 1.3%
362 20830 15.48 0.0%
381 21680 19.57 0.0%
400 22450 16.42 0.0%
419 23230 16.85 0.0%
438 23970 15.25 0.0%
457 24690 27.15 0.1%
476 25380 30.58 0.1%
495 26060 20.35 0.0%
514 26670 17.45 0.0%
533 27300 6.54 0.0%
552 27900 22.95 0.0%
571 28470 23.31 0.0%
590 29050 35.64 0.1%
609 29550 20.38 0.0%
628 30060 20.39 0.0%
647 30530 34.31 0.1%
666 30970 17.19 0.0%
685 31390 16.17 0.0%
704 31800 34.35 0.1%
723 32180 15.78 0.0%
742 32500 16.19 0.0%
761 32830 17.56 0.0%
780 33110 24.3 0.0%
799 33400 23.84 0.0%
818 33670 24.1 0.0%
837 33890 20.7 0.0%
856 34080 24.35 0.0%
875 34270 20.48 0.0%
894 34410 28.39 0.0%
913 34510 21.86 0.0%
932 35170 214 0.6%
951 34710 16.23 0.0%
970 34770 14.37 0.0%
989 34770 14.95 0.0%

Quality and confidence:
param error
s 0.389

Model:
Time ~= 5956
+ s 34.74
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 ~= 116.7
+ n 52.2
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 158.3 0.451 0.2%
3 265 0.773 0.2%
5 370.8 0.625 0.1%
7 476.5 0.704 0.1%
9 578.7 0.869 0.1%
11 684.3 1.085 0.1%
13 798.2 8.872 1.1%
15 894.6 2.014 0.2%
17 1001 1.647 0.1%
19 1109 1.457 0.1%
21 1212 8.843 0.7%
23 1320 4.396 0.3%
25 1420 11.5 0.8%
27 1521 7.92 0.5%
29 1627 6.097 0.3%
31 1741 13.55 0.7%
33 1872 18.89 1.0%
35 1972 12.55 0.6%
37 2064 13.78 0.6%
39 2156 9.868 0.4%
41 2249 2.295 0.1%
43 2378 12.73 0.5%
45 2481 12.18 0.4%
47 2583 8.921 0.3%
49 2689 10.86 0.4%
51 2787 13.41 0.4%
53 2894 15.51 0.5%
55 2989 14.78 0.4%
57 3108 14.19 0.4%
59 3212 6.785 0.2%
61 3302 11.73 0.3%
63 3415 5.91 0.1%
65 3503 9.598 0.2%
67 3613 11.24 0.3%
69 3717 6.449 0.1%
71 3832 8.394 0.2%
73 3932 8.023 0.2%
75 4031 7.493 0.1%
77 4163 14.01 0.3%
79 4249 10.03 0.2%
81 4373 9.514 0.2%
83 4468 5.99 0.1%
85 4565 11.41 0.2%
87 4680 13.98 0.2%
89 4780 7.323 0.1%
91 4872 9.61 0.1%
93 4996 7.697 0.1%
95 5097 6.339 0.1%
97 5185 9.374 0.1%
99 5290 15.55 0.2%
101 5390 8.851 0.1%
103 5510 14.5 0.2%
105 5599 6.692 0.1%
107 5698 7.31 0.1%
109 5821 9.372 0.1%
111 5913 13.43 0.2%
113 5984 11.33 0.1%
115 6119 6.636 0.1%
117 6185 8.488 0.1%
119 6300 13.56 0.2%
121 6407 13.75 0.2%
123 6643 25.93 0.3%
125 6620 9.886 0.1%
127 6744 9.52 0.1%

Quality and confidence:
param error
n 0.023

Model:
Time ~= 119.8
+ n 52.23
µs

Reads = 11 + (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 ~= 144.3
+ n 66.47
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 202 0.449 0.2%
3 340.3 1.09 0.3%
5 471.5 1.445 0.3%
7 603.9 0.978 0.1%
9 741.8 1.537 0.2%
11 870.7 2.166 0.2%
13 1009 9.407 0.9%
15 1127 1.673 0.1%
17 1263 3.363 0.2%
19 1407 2.167 0.1%
21 1547 5.535 0.3%
23 1680 8.126 0.4%
25 1798 7.882 0.4%
27 1955 13.93 0.7%
29 2074 9.997 0.4%
31 2215 5.287 0.2%
33 2339 8.573 0.3%
35 2493 9.875 0.3%
37 2604 9.627 0.3%
39 2720 8.859 0.3%
41 2876 7.795 0.2%
43 3039 4.529 0.1%
45 3152 10.71 0.3%
47 3289 6.061 0.1%
49 3421 9.902 0.2%
51 3552 8.695 0.2%
53 3658 15.71 0.4%
55 3821 6.06 0.1%
57 3939 13.25 0.3%
59 4042 8.628 0.2%
61 4187 7.139 0.1%
63 4327 7.799 0.1%
65 4484 6.656 0.1%
67 4553 5.968 0.1%
69 4716 8.879 0.1%
71 4848 14.87 0.3%
73 4989 16.95 0.3%
75 5116 20.95 0.4%
77 5258 12.75 0.2%
79 5380 15.21 0.2%
81 5504 12.87 0.2%
83 5643 9.485 0.1%
85 5771 7.838 0.1%
87 5957 6.822 0.1%
89 6060 5.487 0.0%
91 6220 12.34 0.1%
93 6349 18.46 0.2%
95 6486 11.05 0.1%
97 6617 8.545 0.1%
99 6726 7.859 0.1%
101 6880 14.94 0.2%
103 6996 20.72 0.2%
105 7133 5.742 0.0%
107 7228 8.4 0.1%
109 7421 9.105 0.1%
111 7571 48.61 0.6%
113 7682 20.48 0.2%
115 7801 14.86 0.1%
117 7919 16.22 0.2%
119 8039 21.27 0.2%
121 8166 8.285 0.1%
123 8343 19.57 0.2%
125 8446 15.77 0.1%
127 8507 19.9 0.2%

Quality and confidence:
param error
n 0.025

Model:
Time ~= 145.4
+ n 66.47
µs

Reads = 12 + (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 ~= 39.57
+ l 0.08
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
l mean µs sigma µs %
1 39.97 0.101 0.2%
2 39.55 0.084 0.2%
3 39.34 0.077 0.1%
4 39.59 0.095 0.2%
5 39.84 0.076 0.1%
6 39.87 0.084 0.2%
7 39.97 0.077 0.1%
8 39.99 0.073 0.1%
9 40.36 0.052 0.1%
10 40.48 0.119 0.2%
11 40.44 0.093 0.2%
12 40.94 0.118 0.2%
13 40.77 0.073 0.1%
14 40.68 0.091 0.2%
15 40.74 0.089 0.2%
16 40.97 0.113 0.2%
17 41.34 0.094 0.2%
18 41.28 0.103 0.2%
19 41.62 0.116 0.2%
20 41.49 0.096 0.2%
21 41.61 0.066 0.1%
22 41.5 0.079 0.1%
23 41.68 0.083 0.1%
24 41.66 0.076 0.1%
25 41.52 0.048 0.1%
26 41.65 0.107 0.2%
27 41.51 0.064 0.1%
28 41.72 0.096 0.2%
29 41.83 0.069 0.1%
30 41.72 0.07 0.1%
31 41.63 0.06 0.1%
32 41.85 0.097 0.2%

Quality and confidence:
param error
l 0.001

Model:
Time ~= 39.58
+ l 0.08
µs

Reads = 4 + (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 32.11
µs

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

-- Extrinsic Time --

Data points distribution:
e mean µs sigma µs %
1 38.28 0.163 0.4%
2 63.57 0.104 0.1%
3 87.21 0.114 0.1%
4 113.4 0.148 0.1%
5 137.6 0.147 0.1%
6 161.6 0.286 0.1%
7 187.2 0.396 0.2%
8 211.5 0.299 0.1%
9 234 0.444 0.1%
10 261.6 0.583 0.2%
11 282.7 1.019 0.3%
12 310.7 1.309 0.4%
13 334.8 1.61 0.4%
14 362.2 1.054 0.2%
15 387.1 0.955 0.2%
16 413.7 0.935 0.2%
17 441.5 1.299 0.2%
18 467.2 1.02 0.2%
19 498.2 1.383 0.2%
20 521.6 0.872 0.1%
21 547.4 1.358 0.2%
22 575.1 2.701 0.4%
23 602.9 1.185 0.1%
24 637.7 3.005 0.4%
25 659.5 1.72 0.2%
26 685 2.454 0.3%
27 723.7 1.568 0.2%
28 745.5 2.536 0.3%
29 771.5 1.171 0.1%
30 805.1 1.756 0.2%
31 839.1 3.84 0.4%
32 855.8 0.863 0.1%
33 884.6 2.015 0.2%
34 926.3 6.555 0.7%
35 944.9 2.992 0.3%
36 986.1 1.85 0.1%
37 1015 2.403 0.2%
38 1042 2.558 0.2%
39 1074 1.831 0.1%
40 1102 1.893 0.1%
41 1125 5.251 0.4%
42 1157 3.675 0.3%
43 1197 11.59 0.9%
44 1231 1.963 0.1%
45 1258 5.775 0.4%
46 1288 4.818 0.3%
47 1324 3.062 0.2%
48 1373 15.56 1.1%
49 1403 14.92 1.0%
50 1420 4.231 0.2%
51 1461 8.402 0.5%
52 1498 9.364 0.6%
53 1524 7.017 0.4%
54 1546 3.787 0.2%
55 1584 14.73 0.9%
56 1628 9.355 0.5%
57 1638 9.259 0.5%
58 1719 9.56 0.5%
59 1752 6.679 0.3%
60 1798 5.306 0.2%
61 1820 6.165 0.3%
62 1839 11.65 0.6%
63 1849 10.2 0.5%
64 1887 3.375 0.1%
65 1915 6.841 0.3%
66 1944 10.59 0.5%
67 1990 6.188 0.3%
68 2011 11.72 0.5%
69 2053 5.331 0.2%
70 2083 8.09 0.3%
71 2133 12.9 0.6%
72 2156 10.02 0.4%
73 2209 11.06 0.5%
74 2226 10.59 0.4%
75 2275 6.796 0.2%
76 2305 7.019 0.3%
77 2347 8.835 0.3%
78 2369 11.8 0.4%
79 2403 10.15 0.4%
80 2441 12 0.4%
81 2470 7.85 0.3%
82 2532 9.828 0.3%
83 2565 11.05 0.4%
84 2612 12.04 0.4%
85 2644 10.73 0.4%
86 2687 11.8 0.4%
87 2725 15.31 0.5%
88 2744 9.855 0.3%
89 2795 9.765 0.3%
90 2840 10.89 0.3%
91 2878 8.177 0.2%
92 2912 7.307 0.2%
93 2935 8.225 0.2%
94 2962 12.73 0.4%
95 2983 3.887 0.1%
96 3046 8.478 0.2%
97 3117 4.497 0.1%
98 3121 12.71 0.4%
99 3173 6.903 0.2%
100 3217 7.25 0.2%

Quality and confidence:
param error
e 0.063

Model:
Time ~= 0
+ e 32.18
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 ~= 64.98
+ s 2.667
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 66.68 0.103 0.1%
2 69.47 0.099 0.1%
3 72.24 0.164 0.2%
4 75.58 0.125 0.1%
5 78.23 0.064 0.0%
6 80.72 0.123 0.1%
7 83.53 0.124 0.1%
8 86.05 0.121 0.1%
9 88.68 0.174 0.1%
10 91.42 0.108 0.1%
11 94.05 0.134 0.1%
12 97.15 0.139 0.1%
13 99.93 0.157 0.1%
14 102.3 0.117 0.1%
15 105.1 0.092 0.0%
16 107.7 0.091 0.0%
17 110.4 0.146 0.1%
18 112.8 0.141 0.1%
19 115.8 0.109 0.0%
20 118.4 0.158 0.1%
21 121 0.143 0.1%
22 123.8 0.257 0.2%
23 126.6 0.169 0.1%
24 129.4 0.176 0.1%
25 132.4 0.139 0.1%
26 134.7 0.148 0.1%
27 137 0.127 0.0%
28 139.8 0.117 0.0%
29 142.7 0.169 0.1%
30 145.5 0.168 0.1%
31 148 0.237 0.1%
32 150.4 0.222 0.1%
33 153.1 0.21 0.1%
34 155.8 0.317 0.2%
35 158.4 0.117 0.0%
36 161 0.186 0.1%
37 163.5 0.147 0.0%
38 166.3 0.123 0.0%
39 169.1 0.109 0.0%
40 171.7 0.201 0.1%
41 174.5 0.13 0.0%
42 177.4 0.141 0.0%
43 180.1 0.221 0.1%
44 183 0.302 0.1%
45 185.4 0.246 0.1%
46 189.5 1.684 0.8%
47 190.7 0.225 0.1%
48 193.7 0.176 0.0%
49 195.5 0.141 0.0%
50 197.9 0.392 0.1%
51 200.7 0.265 0.1%
52 203 0.252 0.1%
53 206.1 0.272 0.1%
54 208.7 0.593 0.2%
55 211.9 0.167 0.0%
56 214.3 0.241 0.1%
57 216.6 0.245 0.1%
58 219 0.321 0.1%
59 222.5 0.288 0.1%
60 224.2 0.431 0.1%
61 227.1 0.303 0.1%
62 230.3 0.375 0.1%
63 232.9 0.276 0.1%
64 235.4 0.359 0.1%
65 238.5 0.353 0.1%
66 240.7 0.272 0.1%
67 243.4 0.305 0.1%
68 245.6 0.339 0.1%
69 249 0.3 0.1%
70 251.3 0.309 0.1%
71 254.1 0.269 0.1%
72 256.7 0.306 0.1%
73 259.7 0.32 0.1%
74 262.3 0.228 0.0%
75 265.2 0.309 0.1%
76 267.6 0.236 0.0%
77 270.2 0.323 0.1%
78 272.7 0.312 0.1%
79 275.5 0.323 0.1%
80 278.3 0.5 0.1%
81 280.4 0.321 0.1%
82 283.8 0.51 0.1%
83 286.5 0.282 0.0%
84 288.1 0.333 0.1%
85 290.8 0.382 0.1%
86 294.2 0.321 0.1%
87 296.6 0.24 0.0%
88 299.5 0.365 0.1%
89 301.9 0.179 0.0%
90 304.6 0.375 0.1%
91 308 0.676 0.2%
92 311.9 0.399 0.1%
93 314.6 0.408 0.1%
94 316.4 0.837 0.2%
95 317.5 0.413 0.1%
96 321.2 0.419 0.1%
97 323.8 0.378 0.1%
98 327.1 0.669 0.2%
99 331.4 4.576 1.3%
100 333.3 1.53 0.4%

Quality and confidence:
param error
s 0

Model:
Time ~= 64.89
+ s 2.67
µs

Reads = 4 + (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 577.7
+ n 82.69
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n mean µs sigma µs %
1 100 3651 12.98 0.3%
2 100 4247 11.88 0.2%
3 100 4760 21.05 0.4%
4 100 5270 15.04 0.2%
5 100 5860 10.31 0.1%
6 100 6420 11.37 0.1%
7 100 6982 7.101 0.1%
8 100 7523 13.86 0.1%
9 100 8278 11.72 0.1%
10 1 706.1 0.646 0.0%
10 2 789.7 2.194 0.2%
10 3 872.7 2.123 0.2%
10 4 965.3 11.56 1.1%
10 5 1046 9.241 0.8%
10 6 1116 2.379 0.2%
10 7 1208 12.63 1.0%
10 8 1293 10.32 0.7%
10 9 1365 2.139 0.1%
10 10 1461 2.068 0.1%
10 11 1533 11.34 0.7%
10 12 1625 15.57 0.9%
10 13 1691 2.948 0.1%
10 14 1783 12.16 0.6%
10 15 1861 14.87 0.7%
10 16 1951 13.72 0.7%
10 17 2035 14.12 0.6%
10 18 2100 9.654 0.4%
10 19 2227 12.59 0.5%
10 20 2288 7.783 0.3%
10 21 2387 11.34 0.4%
10 22 2457 14.83 0.6%
10 23 2541 13.08 0.5%
10 24 2647 8.81 0.3%
10 25 2697 13.14 0.4%
10 26 2779 14.79 0.5%
10 27 2863 15.27 0.5%
10 28 2938 12.56 0.4%
10 29 3024 10.7 0.3%
10 30 3116 12.13 0.3%
10 31 3190 11.55 0.3%
10 32 3280 15.4 0.4%
10 33 3369 11.4 0.3%
10 34 3448 17.02 0.4%
10 35 3516 15.78 0.4%
10 36 3627 15.53 0.4%
10 37 3709 9.752 0.2%
10 38 3808 12.05 0.3%
10 39 3907 10.88 0.2%
10 40 3974 6.599 0.1%
10 41 4056 7.792 0.1%
10 42 4119 10.24 0.2%
10 43 4203 6.95 0.1%
10 44 4286 8.822 0.2%
10 45 4356 2.631 0.0%
10 46 4466 12.12 0.2%
10 47 4543 8.421 0.1%
10 48 4593 7.165 0.1%
10 49 4729 29.55 0.6%
10 50 4806 19.14 0.3%
10 51 4842 12.66 0.2%
10 52 4939 14.42 0.2%
10 53 5000 3.875 0.0%
10 54 5081 10.22 0.2%
10 55 5182 8.023 0.1%
10 56 5270 11.06 0.2%
10 57 5347 10.81 0.2%
10 58 5449 11.9 0.2%
10 59 5530 9.22 0.1%
10 60 5601 7.958 0.1%
10 61 5647 5.472 0.0%
10 62 5759 6.399 0.1%
10 63 5841 11.85 0.2%
10 64 5960 12.07 0.2%
10 65 6015 8.809 0.1%
10 66 6120 7.935 0.1%
10 67 6192 9.52 0.1%
10 68 6278 9.858 0.1%
10 69 6368 17.8 0.2%
10 70 6424 4.345 0.0%
10 71 6521 9.69 0.1%
10 72 6682 17.19 0.2%
10 73 6647 8.582 0.1%
10 74 6717 17.13 0.2%
10 75 6810 12.83 0.1%
10 76 6938 9.166 0.1%
10 77 6969 11.11 0.1%
10 78 7111 8.422 0.1%
10 79 7221 11.89 0.1%
10 80 7292 6.562 0.0%
10 81 7352 9.909 0.1%
10 82 7415 11.97 0.1%
10 83 7518 10.89 0.1%
10 84 7620 14.41 0.1%
10 85 7692 12.42 0.1%
10 86 7740 6.551 0.0%
10 87 7796 9.409 0.1%
10 88 7924 14.84 0.1%
10 89 8005 14.94 0.1%
10 90 8074 14.47 0.1%
10 91 8137 8.148 0.1%
10 92 8227 17.39 0.2%
10 93 8333 15.37 0.1%
10 94 8382 23.24 0.2%
10 95 8490 13.38 0.1%
10 96 8521 14.45 0.1%
10 97 8655 15.83 0.1%
10 98 8712 15.03 0.1%
10 99 8778 9.948 0.1%
10 100 8877 8.89 0.1%

Quality and confidence:
param error
v 0.805
n 0.04

Model:
Time ~= 0
+ v 593.7
+ n 82.5
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "submit_solution_better", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 1
+ n 0.6
+ a 75.46
+ w 6.947
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n a w mean µs sigma µs %
200 1000 400 100 31070 46.09 0.1%
204 1000 400 100 31140 48.38 0.1%
208 1000 400 100 31320 34.98 0.1%
212 1000 400 100 31260 52.84 0.1%
216 1000 400 100 31150 37.71 0.1%
220 1000 400 100 31130 59.06 0.1%
224 1000 400 100 31140 28.46 0.0%
228 1000 400 100 31180 29.68 0.0%
232 1000 400 100 31200 60.04 0.1%
236 1000 400 100 31250 50.14 0.1%
240 1000 400 100 31240 54.98 0.1%
244 1000 400 100 31070 49.78 0.1%
248 1000 400 100 31040 49.82 0.1%
252 1000 400 100 31100 31.13 0.1%
256 1000 400 100 31230 64.08 0.2%
260 1000 400 100 31300 52.35 0.1%
264 1000 400 100 31210 63.85 0.2%
268 1000 400 100 31210 59.26 0.1%
272 1000 400 100 31070 46.87 0.1%
276 1000 400 100 31370 49.71 0.1%
280 1000 400 100 31380 38.19 0.1%
284 1000 400 100 31050 56.19 0.1%
288 1000 400 100 31300 22.52 0.0%
292 1000 400 100 31260 81.53 0.2%
296 1000 400 100 31390 65.65 0.2%
300 1000 400 100 31260 40.43 0.1%
304 1000 400 100 31110 35.21 0.1%
308 1000 400 100 31250 45.37 0.1%
312 1000 400 100 31310 55.36 0.1%
316 1000 400 100 31370 72.29 0.2%
320 1000 400 100 31160 40.36 0.1%
324 1000 400 100 31370 42.6 0.1%
328 1000 400 100 31230 49.29 0.1%
332 1000 400 100 31170 50.03 0.1%
336 1000 400 100 31130 66.3 0.2%
340 1000 400 100 31260 66.08 0.2%
344 1000 400 100 31200 52.69 0.1%
348 1000 400 100 31280 52.13 0.1%
352 1000 400 100 31300 61.86 0.1%
356 1000 400 100 31250 38.21 0.1%
360 1000 400 100 31430 45.09 0.1%
364 1000 400 100 31450 70.23 0.2%
368 1000 400 100 31280 64.73 0.2%
372 1000 400 100 31360 55.21 0.1%
376 1000 400 100 31240 85.08 0.2%
380 1000 400 100 31440 58.01 0.1%
384 1000 400 100 31190 49.03 0.1%
388 1000 400 100 31340 45.36 0.1%
392 1000 400 100 31370 54.49 0.1%
396 1000 400 100 31270 43.94 0.1%
400 500 400 100 30930 35.75 0.1%
400 510 400 100 31140 55.83 0.1%
400 520 400 100 31100 42.52 0.1%
400 530 400 100 30960 51.58 0.1%
400 540 400 100 31140 51.69 0.1%
400 550 400 100 31110 67.34 0.2%
400 560 400 100 31190 43.89 0.1%
400 570 400 100 31000 37.31 0.1%
400 580 400 100 31210 83.67 0.2%
400 590 400 100 31220 85.71 0.2%
400 600 400 100 31310 32.9 0.1%
400 610 400 100 31270 31.65 0.1%
400 620 400 100 31230 57.05 0.1%
400 630 400 100 31040 59.45 0.1%
400 640 400 100 31170 53.39 0.1%
400 650 400 100 31120 41.31 0.1%
400 660 400 100 31180 81.66 0.2%
400 670 400 100 31140 45.27 0.1%
400 680 400 100 31180 34.64 0.1%
400 690 400 100 31170 29.67 0.0%
400 700 400 100 31230 36.16 0.1%
400 710 400 100 31220 26.96 0.0%
400 720 400 100 31290 72.61 0.2%
400 730 400 100 31220 47.77 0.1%
400 740 400 100 31240 32.06 0.1%
400 750 400 100 31360 44.06 0.1%
400 760 400 100 31310 42.88 0.1%
400 770 400 100 31410 57.8 0.1%
400 780 400 100 31350 70.52 0.2%
400 790 400 100 31290 52.63 0.1%
400 800 400 100 31270 71.87 0.2%
400 810 400 100 31150 45.95 0.1%
400 820 400 100 31370 49.78 0.1%
400 830 400 100 31420 43.36 0.1%
400 840 400 100 31260 53.1 0.1%
400 850 400 100 31150 67.29 0.2%
400 860 400 100 31390 41.02 0.1%
400 870 400 100 31190 55.21 0.1%
400 880 400 100 31170 56.92 0.1%
400 890 400 100 31450 42.91 0.1%
400 900 400 100 31420 51.55 0.1%
400 910 400 100 31250 67.32 0.2%
400 920 400 100 31410 42.15 0.1%
400 930 400 100 31390 35.95 0.1%
400 940 400 100 31340 61.54 0.1%
400 950 400 100 31470 77.02 0.2%
400 960 400 100 31260 41.75 0.1%
400 970 400 100 31380 76.41 0.2%
400 980 400 100 31320 45.68 0.1%
400 990 400 100 31410 42.57 0.1%
400 1000 200 100 16100 15.82 0.0%
400 1000 204 100 16480 21.73 0.1%
400 1000 208 100 16740 37.24 0.2%
400 1000 212 100 17070 43.72 0.2%
400 1000 216 100 17350 27.1 0.1%
400 1000 220 100 17760 37.68 0.2%
400 1000 224 100 18100 21.63 0.1%
400 1000 228 100 18420 28.52 0.1%
400 1000 232 100 18690 22.21 0.1%
400 1000 236 100 19020 25.04 0.1%
400 1000 240 100 19290 37.43 0.1%
400 1000 244 100 19660 51.31 0.2%
400 1000 248 100 19940 40.33 0.2%
400 1000 252 100 20230 26.55 0.1%
400 1000 256 100 20520 20.95 0.1%
400 1000 260 100 20810 20.98 0.1%
400 1000 264 100 21120 31.9 0.1%
400 1000 268 100 21430 32.27 0.1%
400 1000 272 100 21710 35.68 0.1%
400 1000 276 100 22090 29.1 0.1%
400 1000 280 100 22330 33.44 0.1%
400 1000 284 100 22640 24.41 0.1%
400 1000 288 100 22940 47.32 0.2%
400 1000 292 100 23270 17.46 0.0%
400 1000 296 100 23500 38.44 0.1%
400 1000 300 100 23810 46.85 0.1%
400 1000 304 100 24110 35.71 0.1%
400 1000 308 100 24440 33.5 0.1%
400 1000 312 100 24750 50.23 0.2%
400 1000 316 100 25000 44.92 0.1%
400 1000 320 100 25290 38.88 0.1%
400 1000 324 100 25580 29.91 0.1%
400 1000 328 100 25910 51.52 0.1%
400 1000 332 100 26230 40.08 0.1%
400 1000 336 100 26520 49.73 0.1%
400 1000 340 100 26840 40.14 0.1%
400 1000 344 100 27120 49.99 0.1%
400 1000 348 100 27370 46.79 0.1%
400 1000 352 100 27680 42.89 0.1%
400 1000 356 100 27970 55.38 0.1%
400 1000 360 100 28290 33.88 0.1%
400 1000 364 100 28520 56.9 0.1%
400 1000 368 100 28910 38.43 0.1%
400 1000 372 100 29140 45.1 0.1%
400 1000 376 100 29480 48.31 0.1%
400 1000 380 100 29790 66.79 0.2%
400 1000 384 100 30140 33.63 0.1%
400 1000 388 100 30460 34.16 0.1%
400 1000 392 100 30800 46.74 0.1%
400 1000 396 100 31060 67.81 0.2%
400 1000 400 16 30710 52.17 0.1%
400 1000 400 17 30750 43.63 0.1%
400 1000 400 18 30860 62.22 0.2%
400 1000 400 19 30860 38.53 0.1%
400 1000 400 20 30740 66.85 0.2%
400 1000 400 21 30870 14.26 0.0%
400 1000 400 22 30830 39.1 0.1%
400 1000 400 23 30950 70.6 0.2%
400 1000 400 24 31060 62.05 0.1%
400 1000 400 25 30730 35.74 0.1%
400 1000 400 26 30860 70.21 0.2%
400 1000 400 27 30940 28.52 0.0%
400 1000 400 28 30890 91.81 0.2%
400 1000 400 29 30870 49.66 0.1%
400 1000 400 30 30760 29.85 0.0%
400 1000 400 31 30900 58.49 0.1%
400 1000 400 32 30990 71.66 0.2%
400 1000 400 33 30990 71.32 0.2%
400 1000 400 34 30900 72.02 0.2%
400 1000 400 35 30890 42.87 0.1%
400 1000 400 36 31070 48.2 0.1%
400 1000 400 37 30990 36.51 0.1%
400 1000 400 38 31090 44.62 0.1%
400 1000 400 39 31080 52.84 0.1%
400 1000 400 40 30890 34.2 0.1%
400 1000 400 41 31070 50.15 0.1%
400 1000 400 42 31010 63.21 0.2%
400 1000 400 43 31110 35.39 0.1%
400 1000 400 44 31160 57.62 0.1%
400 1000 400 45 31000 53.29 0.1%
400 1000 400 46 31020 51.99 0.1%
400 1000 400 47 31200 41.3 0.1%
400 1000 400 48 31080 51.47 0.1%
400 1000 400 49 31160 52.91 0.1%
400 1000 400 50 30840 58.59 0.1%
400 1000 400 51 31120 127.9 0.4%
400 1000 400 52 31060 30.47 0.0%
400 1000 400 53 31060 36.58 0.1%
400 1000 400 54 31120 70.02 0.2%
400 1000 400 55 31140 67.55 0.2%
400 1000 400 56 30930 48.17 0.1%
400 1000 400 57 31140 40.83 0.1%
400 1000 400 58 30980 88.24 0.2%
400 1000 400 59 31050 61.51 0.1%
400 1000 400 60 30970 52.31 0.1%
400 1000 400 61 31060 64.47 0.2%
400 1000 400 62 31130 41.4 0.1%
400 1000 400 63 31090 77.75 0.2%
400 1000 400 64 31290 43.63 0.1%
400 1000 400 65 31200 53.35 0.1%
400 1000 400 66 31170 61.04 0.1%
400 1000 400 67 31210 55.5 0.1%
400 1000 400 68 31150 26.58 0.0%
400 1000 400 69 31230 38.58 0.1%
400 1000 400 70 31240 50.62 0.1%
400 1000 400 71 31250 24.63 0.0%
400 1000 400 72 31330 54.41 0.1%
400 1000 400 73 31190 60.11 0.1%
400 1000 400 74 31240 71.74 0.2%
400 1000 400 75 31330 78.74 0.2%
400 1000 400 76 31210 47.99 0.1%
400 1000 400 77 31250 63.58 0.2%
400 1000 400 78 31350 33.92 0.1%
400 1000 400 79 31170 58.6 0.1%
400 1000 400 80 31230 65.98 0.2%
400 1000 400 81 31220 71.81 0.2%
400 1000 400 82 31210 24.63 0.0%
400 1000 400 83 31300 45.78 0.1%
400 1000 400 84 31430 47.41 0.1%
400 1000 400 85 31450 35.03 0.1%
400 1000 400 86 31300 76.19 0.2%
400 1000 400 87 31290 37.44 0.1%
400 1000 400 88 31270 21.61 0.0%
400 1000 400 89 31330 67.62 0.2%
400 1000 400 90 31360 22.13 0.0%
400 1000 400 91 31310 43.5 0.1%
400 1000 400 92 31350 30.58 0.0%
400 1000 400 93 31420 68.47 0.2%
400 1000 400 94 31330 36.94 0.1%
400 1000 400 95 31330 68.33 0.2%
400 1000 400 96 31360 83.92 0.2%
400 1000 400 97 31340 95.89 0.3%
400 1000 400 98 31430 53.56 0.1%
400 1000 400 99 31400 56.63 0.1%
400 1000 400 100 31370 41.65 0.1%

Quality and confidence:
param error
v 0.046
n 0.018
a 0.046
w 0.096

Model:
Time ~= 0
+ v 1.236
+ n 0.549
+ a 75.69
+ w 6.459
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 27.01
+ n 66.28
+ s 31.22
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n s mean µs sigma µs %
200 400 20 31810 88.37 0.2%
204 400 20 31860 29.93 0.0%
208 400 20 31910 47.93 0.1%
212 400 20 32130 99.11 0.3%
216 400 20 31960 54.87 0.1%
220 400 20 31900 48.31 0.1%
224 400 20 32230 54.21 0.1%
228 400 20 32560 62.16 0.1%
232 400 20 32660 89.3 0.2%
236 400 20 32740 57.67 0.1%
240 400 20 32630 72.17 0.2%
244 400 20 32980 81.75 0.2%
248 400 20 32640 90.07 0.2%
252 400 20 33090 76.02 0.2%
256 400 20 33060 67.68 0.2%
260 400 20 33100 85.15 0.2%
264 400 20 33320 100.2 0.3%
268 400 20 33630 77.89 0.2%
272 400 20 33760 79.09 0.2%
276 400 20 33810 112.5 0.3%
280 400 20 33870 46.58 0.1%
284 400 20 33980 63.44 0.1%
288 400 20 34150 71.68 0.2%
292 400 20 33860 75.87 0.2%
296 400 20 34150 64.31 0.1%
300 400 20 34300 82.89 0.2%
304 400 20 34290 36.24 0.1%
308 400 20 34710 51.5 0.1%
312 400 20 34740 64.78 0.1%
316 400 20 34900 65.34 0.1%
320 400 20 34620 81.72 0.2%
324 400 20 35080 82.93 0.2%
328 400 20 34780 38.18 0.1%
332 400 20 35430 68.8 0.1%
336 400 20 35530 65.39 0.1%
340 400 20 35480 54.66 0.1%
344 400 20 35610 55.21 0.1%
348 400 20 35360 66.52 0.1%
352 400 20 35750 57.54 0.1%
356 400 20 36010 73.79 0.2%
360 400 20 35820 122 0.3%
364 400 20 35800 69.79 0.1%
368 400 20 36130 96.99 0.2%
372 400 20 36130 130.5 0.3%
376 400 20 36350 63.5 0.1%
380 400 20 36460 64.66 0.1%
384 400 20 36790 140.1 0.3%
388 400 20 36880 130.7 0.3%
392 400 20 36820 75.72 0.2%
396 400 20 37260 116.3 0.3%
400 200 20 23660 55.37 0.2%
400 204 20 24140 69.72 0.2%
400 208 20 24100 72.65 0.3%
400 212 20 24410 85.89 0.3%
400 216 20 25060 74.04 0.2%
400 220 20 25230 36.77 0.1%
400 224 20 25040 53.19 0.2%
400 228 20 25700 51.92 0.2%
400 232 20 26050 75.67 0.2%
400 236 20 26140 71.6 0.2%
400 240 20 26510 72.54 0.2%
400 244 20 26830 50.13 0.1%
400 248 20 27080 45.91 0.1%
400 252 20 27220 61.27 0.2%
400 256 20 27510 66.72 0.2%
400 260 20 27510 75.18 0.2%
400 264 20 28220 172.4 0.6%
400 268 20 28430 83.44 0.2%
400 272 20 28540 53.93 0.1%
400 276 20 28970 42.37 0.1%
400 280 20 29110 44.73 0.1%
400 284 20 29430 56.81 0.1%
400 288 20 29780 71.71 0.2%
400 292 20 30030 69.48 0.2%
400 296 20 30450 90.43 0.2%
400 300 20 30240 52.45 0.1%
400 304 20 30980 76.62 0.2%
400 308 20 30780 106.7 0.3%
400 312 20 31280 44.45 0.1%
400 316 20 31360 71.46 0.2%
400 320 20 31580 48.29 0.1%
400 324 20 32190 36.28 0.1%
400 328 20 32400 68.77 0.2%
400 332 20 32500 58 0.1%
400 336 20 32790 49.31 0.1%
400 340 20 33170 80.55 0.2%
400 344 20 33320 91.7 0.2%
400 348 20 33680 44.58 0.1%
400 352 20 33810 98.1 0.2%
400 356 20 33880 65.11 0.1%
400 360 20 34490 109.2 0.3%
400 364 20 34420 65.49 0.1%
400 368 20 34620 70.28 0.2%
400 372 20 35270 67.14 0.1%
400 376 20 35590 44.42 0.1%
400 380 20 35860 42.01 0.1%
400 384 20 35930 70.64 0.1%
400 388 20 36320 97.16 0.2%
400 392 20 36130 51.56 0.1%
400 396 20 37020 92.72 0.2%
400 400 1 36390 101.8 0.2%
400 400 2 36700 41.04 0.1%
400 400 3 36670 59.54 0.1%
400 400 4 36830 53.21 0.1%
400 400 5 36350 36.57 0.1%
400 400 6 36440 71.34 0.1%
400 400 7 36870 99.48 0.2%
400 400 8 36510 97.54 0.2%
400 400 9 36810 38.03 0.1%
400 400 10 36750 88.53 0.2%
400 400 11 36930 71.47 0.1%
400 400 12 37240 92.02 0.2%
400 400 13 36980 91.92 0.2%
400 400 14 36940 85.82 0.2%
400 400 15 37100 179.9 0.4%
400 400 16 36930 86.71 0.2%
400 400 17 37040 103.3 0.2%
400 400 18 37090 143.6 0.3%
400 400 19 36880 52.28 0.1%
400 400 20 37110 74.39 0.2%

Quality and confidence:
param error
v 0.102
n 0.102
s 1.389

Model:
Time ~= 0
+ v 27.08
+ n 66.3
+ s 26.67
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * 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 ~= 0
+ v 9.937
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
200 1918 14.06 0.7%
204 1953 14.13 0.7%
208 1998 10.23 0.5%
212 2032 7.139 0.3%
216 2075 12.04 0.5%
220 2073 11.52 0.5%
224 2184 11.43 0.5%
228 2236 11.6 0.5%
232 2245 11.98 0.5%
236 2281 21.43 0.9%
240 2330 12.28 0.5%
244 2386 9.928 0.4%
248 2465 12.37 0.5%
252 2457 14.09 0.5%
256 2437 8.476 0.3%
260 2559 14.39 0.5%
264 2580 16.52 0.6%
268 2633 23.08 0.8%
272 2650 16.28 0.6%
276 2762 19.12 0.6%
280 2683 16.29 0.6%
284 2713 12.81 0.4%
288 2820 12.63 0.4%
292 2881 13.78 0.4%
296 2913 17 0.5%
300 2921 11.07 0.3%
304 2941 17.51 0.5%
308 3020 22.09 0.7%
312 3048 26.85 0.8%
316 3125 25.36 0.8%
320 3112 19.78 0.6%
324 3157 20.6 0.6%
328 3205 26.83 0.8%
332 3232 14.94 0.4%
336 3272 16.82 0.5%
340 3306 20.66 0.6%
344 3377 17.39 0.5%
348 3370 22.51 0.6%
352 3395 20.21 0.5%
356 3500 14.46 0.4%
360 3539 25.89 0.7%
364 3608 28.09 0.7%
368 3594 8.444 0.2%
372 3618 18.81 0.5%
376 3711 19.17 0.5%
380 3727 22.26 0.5%
384 3794 16.69 0.4%
388 3801 11.18 0.2%
392 3859 18.13 0.4%
396 3794 8.84 0.2%
400 3851 24.1 0.6%

Quality and confidence:
param error
v 0.027

Model:
Time ~= 0
+ v 9.912
µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)

[kianenigma]

This poor guy is still running

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Kusama Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=kusama-dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/kusama/src/weights/

Results

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

-- Extrinsic Time --

Model:
Time ~= 74.68
µs

Reads = 5
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 74.68
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 ~= 60.19
µs

Reads = 4
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 60.19
µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 54.6
µs

Reads = 5
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 54.6
µs

Reads = 5
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 55.89
+ s 0.031
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 55.11 0.137 0.2%
2 55.45 0.19 0.3%
4 55.47 0.092 0.1%
6 55.9 0.102 0.1%
8 55.75 0.12 0.2%
10 56.22 0.063 0.1%
12 56.01 0.083 0.1%
14 56.23 0.177 0.3%
16 56.26 0.106 0.1%
18 56.56 0.069 0.1%
20 56.69 0.085 0.1%
22 56.86 0.166 0.2%
24 56.7 0.117 0.2%
26 56.86 0.152 0.2%
28 56.88 0.085 0.1%
30 57.02 0.166 0.2%
32 57.09 0.126 0.2%
34 57.05 0.066 0.1%
36 56.96 0.217 0.3%
38 57.35 0.121 0.2%
40 57.39 0.089 0.1%
42 57.2 0.066 0.1%
44 56.97 0.111 0.1%
46 57.87 0.178 0.3%
48 57.9 0.108 0.1%
50 57.5 0.105 0.1%
52 57.62 0.107 0.1%
54 57.5 0.199 0.3%
56 57.67 0.155 0.2%
58 57.51 0.161 0.2%
60 57.67 0.079 0.1%
62 57.63 0.114 0.1%
64 58.05 0.119 0.2%
66 57.96 0.109 0.1%
68 58.25 0.134 0.2%
70 58.2 0.084 0.1%
72 58.24 0.239 0.4%
74 58.42 0.222 0.3%
76 58.49 0.212 0.3%
78 58.58 0.131 0.2%
80 58.61 0.145 0.2%
82 58.67 0.125 0.2%
84 58.39 0.083 0.1%
86 58.51 0.094 0.1%
88 58.82 0.137 0.2%
90 58.31 0.113 0.1%
92 58.39 0.068 0.1%
94 58.46 0.13 0.2%
96 58.68 0.135 0.2%
98 58.44 0.079 0.1%
100 58.12 0.165 0.2%

Quality and confidence:
param error
s 0

Model:
Time ~= 55.86
+ s 0.031
µs

Reads = 5 + (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 ~= 87.96
+ s 2.594
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 83.19 0.245 0.2%
2 92.87 0.156 0.1%
4 98.55 0.098 0.0%
6 103.1 0.328 0.3%
8 108.5 0.109 0.1%
10 114.1 0.149 0.1%
12 119.2 0.134 0.1%
14 125.4 0.703 0.5%
16 129.6 0.126 0.0%
18 134.8 0.349 0.2%
20 140.3 0.19 0.1%
22 145.1 0.229 0.1%
24 150.7 0.222 0.1%
26 155.8 0.235 0.1%
28 160.8 0.155 0.0%
30 166.3 0.139 0.0%
32 170.7 0.187 0.1%
34 176.1 0.208 0.1%
36 181.1 0.383 0.2%
38 186.8 0.68 0.3%
40 191.5 0.201 0.1%
42 196.8 0.278 0.1%
44 202.2 0.287 0.1%
46 207.2 0.269 0.1%
48 212.4 0.757 0.3%
50 217.1 0.188 0.0%
52 221.8 0.334 0.1%
54 227 0.302 0.1%
56 232.5 0.231 0.0%
58 237.9 0.353 0.1%
60 243 0.465 0.1%
62 248.1 0.284 0.1%
64 254.4 0.63 0.2%
66 258.9 0.335 0.1%
68 264.4 0.38 0.1%
70 268.9 0.357 0.1%
72 274.4 0.502 0.1%
74 279.4 0.409 0.1%
76 284.4 0.473 0.1%
78 290.1 0.774 0.2%
80 294.5 0.767 0.2%
82 300.2 0.485 0.1%
84 305.7 0.454 0.1%
86 310.1 0.343 0.1%
88 316.1 0.358 0.1%
90 320.6 0.582 0.1%
92 329.3 2.313 0.7%
94 332.8 0.423 0.1%
96 337.7 0.489 0.1%
98 344.3 0.893 0.2%
100 349.3 0.338 0.0%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 87.49
+ s 2.602
µs

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

-- Extrinsic Time --

Model:
Time ~= 18.05
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 18.05
µs

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

-- Extrinsic Time --

Model:
Time ~= 19.71
+ k 18.05
µs

Reads = 2 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
k mean µs sigma µs %
1 41.96 0.147 0.3%
3 79.27 0.222 0.2%
5 114.3 0.31 0.2%
7 148.9 0.188 0.1%
9 184.5 0.292 0.1%
11 219.6 0.478 0.2%
13 255.3 0.393 0.1%
15 290.3 0.412 0.1%
17 325 0.502 0.1%
19 362.4 0.807 0.2%
21 409.5 8.151 1.9%
23 443.4 1.302 0.2%
25 468.7 1.64 0.3%
27 505.3 0.887 0.1%
29 540.8 1.284 0.2%
31 576.9 0.801 0.1%
33 612.3 2.163 0.3%
35 647.1 1.372 0.2%
37 682 5.957 0.8%
39 720.7 2.781 0.3%
41 757.5 4.116 0.5%
43 791.5 8.266 1.0%
45 825.8 0.787 0.0%
47 862.1 2.907 0.3%
49 900.7 1.737 0.1%
51 936.4 1.146 0.1%
53 973.7 1.908 0.1%
55 1006 2.141 0.2%
57 1049 5.438 0.5%
59 1080 2.338 0.2%
61 1125 7.435 0.6%
63 1150 2.035 0.1%
65 1190 2.089 0.1%
67 1228 8.892 0.7%
69 1266 3.256 0.2%
71 1294 2.574 0.1%
73 1336 10.47 0.7%
75 1373 8.479 0.6%
77 1418 10.62 0.7%
79 1433 2.428 0.1%
81 1474 4.502 0.3%
83 1538 10.06 0.6%
85 1547 7.097 0.4%
87 1595 9.114 0.5%
89 1632 11.34 0.6%
91 1653 5.882 0.3%
93 1689 7.06 0.4%
95 1740 8.797 0.5%
97 1769 13.25 0.7%
99 1804 8.117 0.4%
101 1847 7.062 0.3%
103 1882 7.26 0.3%
105 1919 9.972 0.5%
107 1959 7.711 0.3%
109 1993 5.389 0.2%
111 2023 10.19 0.5%
113 2070 7.101 0.3%
115 2111 12.41 0.5%
117 2140 7.347 0.3%
119 2187 10.46 0.4%
121 2215 9.257 0.4%
123 2250 5.86 0.2%
125 2283 9.609 0.4%
127 2338 14.07 0.6%

Quality and confidence:
param error
k 0.01

Model:
Time ~= 16.48
+ k 18.12
µs

Reads = 2 + (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 ~= 27.81
+ n 5.509
µs

Reads = 4 + (1 * n)
Writes = 2 + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 32.27 0.125 0.3%
2 39.13 0.111 0.2%
3 44.09 0.112 0.2%
4 49.8 0.12 0.2%
5 55.73 0.107 0.1%
6 61.14 0.125 0.2%
7 66.11 0.251 0.3%
8 70.91 0.285 0.4%
9 77.78 0.074 0.0%
10 83.63 0.277 0.3%
11 90.35 0.195 0.2%
12 94.17 0.248 0.2%
13 99.28 0.279 0.2%
14 104.6 0.444 0.4%
15 109.7 0.15 0.1%
16 115 0.246 0.2%

Quality and confidence:
param error
n 0.013

Model:
Time ~= 27.8
+ n 5.506
µs

Reads = 4 + (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 ~= 17.34
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 17.34
µs

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

-- Extrinsic Time --

Model:
Time ~= 12.13
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 12.13
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 ~= 26.29
µs

Reads = 3
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 26.29
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 ~= 1.995
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 1.995
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 ~= 2.311
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.311
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 ~= 2.271
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.271
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 ~= 2.366
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 2.366
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 ~= 2.4
+ v 0.034
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
0 2.314 0.015 0.6%
20 3.235 0.017 0.5%
40 3.911 0.018 0.4%
60 4.62 0.014 0.3%
80 5.27 0.016 0.3%
100 5.95 0.014 0.2%
120 6.57 0.01 0.1%
140 7.32 0.023 0.3%
160 7.998 0.013 0.1%
180 8.671 0.026 0.2%
200 9.368 0.018 0.1%
220 10.03 0.026 0.2%
240 10.68 0.021 0.1%
260 11.42 0.037 0.3%
280 12.09 0.022 0.1%
300 12.72 0.021 0.1%
320 13.51 0.021 0.1%
340 14.16 0.025 0.1%
360 14.81 0.015 0.1%
380 15.52 0.024 0.1%
400 16.19 0.021 0.1%
420 16.88 0.018 0.1%
440 17.54 0.025 0.1%
460 18.27 0.03 0.1%
480 18.97 0.024 0.1%
500 19.63 0.015 0.0%
520 20.36 0.027 0.1%
540 21.09 0.024 0.1%
560 21.74 0.019 0.0%
580 22.44 0.014 0.0%
600 23.15 0.022 0.0%
620 23.84 0.02 0.0%
640 24.68 0.028 0.1%
660 25.35 0.022 0.0%
680 26 0.021 0.0%
700 26.71 0.017 0.0%
720 27.42 0.039 0.1%
740 28.04 0.022 0.0%
760 28.77 0.026 0.0%
780 29.52 0.05 0.1%
800 30.2 0.029 0.0%
820 30.89 0.04 0.1%
840 31.53 0.037 0.1%
860 32.24 0.046 0.1%
880 32.9 0.037 0.1%
900 33.72 0.031 0.0%
920 34.39 0.03 0.0%
940 35.12 0.034 0.0%
960 35.77 0.055 0.1%
980 36.41 0.018 0.0%
1000 37.38 0.334 0.8%

Quality and confidence:
param error
v 0

Model:
Time ~= 2.391
+ v 0.035
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 ~= 59.21
+ s 2.581
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 54.81 0.124 0.2%
2 63.6 0.112 0.1%
4 69.32 0.06 0.0%
6 74.51 0.127 0.1%
8 79.65 0.098 0.1%
10 84.69 0.218 0.2%
12 90.03 0.085 0.0%
14 95.58 0.185 0.1%
16 100.7 0.212 0.2%
18 106 0.129 0.1%
20 111 0.3 0.2%
22 116.5 0.097 0.0%
24 121.5 0.136 0.1%
26 127.1 0.21 0.1%
28 132 0.14 0.1%
30 137.1 0.323 0.2%
32 142 0.238 0.1%
34 147 0.15 0.1%
36 152 0.255 0.1%
38 157.7 0.166 0.1%
40 162.5 0.142 0.0%
42 168.1 0.253 0.1%
44 173.1 0.139 0.0%
46 177.8 0.303 0.1%
48 183.5 0.395 0.2%
50 188 0.283 0.1%
52 193 0.237 0.1%
54 198.4 0.437 0.2%
56 203.7 0.154 0.0%
58 209.2 0.396 0.1%
60 213.4 0.269 0.1%
62 219.6 0.451 0.2%
64 224.1 0.307 0.1%
66 228.8 0.288 0.1%
68 234.3 0.548 0.2%
70 239.6 0.333 0.1%
72 245.1 0.43 0.1%
74 250.1 0.354 0.1%
76 255.3 0.497 0.1%
78 260.6 0.616 0.2%
80 265 0.416 0.1%
82 270.5 0.545 0.2%
84 275.4 0.32 0.1%
86 280.3 0.915 0.3%
88 285.7 0.315 0.1%
90 291.8 0.26 0.0%
92 296.5 0.535 0.1%
94 302 0.274 0.0%
96 307.3 0.788 0.2%
98 312.7 0.376 0.1%
100 318.6 0.948 0.2%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 58.95
+ s 2.585
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 6718
+ s 34.77
µs

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

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 440.1 0.663 0.1%
20 1731 7.157 0.4%
39 3006 13.23 0.4%
58 4259 3.634 0.0%
77 5480 7.426 0.1%
96 6677 11.79 0.1%
115 7846 10.86 0.1%
134 8993 10.42 0.1%
153 10120 8.727 0.0%
172 11220 12.79 0.1%
191 12280 11.42 0.0%
210 13320 11.38 0.0%
229 14350 15.74 0.1%
248 15350 17.87 0.1%
267 16320 10.7 0.0%
286 17290 25.31 0.1%
305 18200 30.11 0.1%
324 19080 10.11 0.0%
343 19960 21.8 0.1%
362 20820 22.86 0.1%
381 21640 20.81 0.0%
400 22430 9.354 0.0%
419 23200 30.45 0.1%
438 23950 14.77 0.0%
457 24700 28 0.1%
476 25610 114.9 0.4%
495 26060 24.5 0.0%
514 26680 23.37 0.0%
533 27330 26.68 0.0%
552 27920 24.23 0.0%
571 28470 17.32 0.0%
590 29030 30.08 0.1%
609 29560 28.74 0.0%
628 30070 15.99 0.0%
647 30520 25.82 0.0%
666 30970 17.68 0.0%
685 31400 19.48 0.0%
704 31790 23.84 0.0%
723 32180 19.68 0.0%
742 32690 159.5 0.4%
761 32820 30.57 0.0%
780 33140 27.84 0.0%
799 33400 17.07 0.0%
818 33630 25.98 0.0%
837 33870 17.95 0.0%
856 34090 47.55 0.1%
875 34290 24.86 0.0%
894 34450 17.88 0.0%
913 34530 20.66 0.0%
932 34630 13.23 0.0%
951 34710 18.1 0.0%
970 34790 21.48 0.0%
989 34790 17.93 0.0%

Quality and confidence:
param error
s 0.391

Model:
Time ~= 5925
+ s 34.77
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 ~= 111.8
+ n 49.95
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 153.7 0.392 0.2%
3 256 0.923 0.3%
5 355.8 0.719 0.2%
7 456.8 1.257 0.2%
9 555.6 1.295 0.2%
11 653.1 0.758 0.1%
13 754.4 0.965 0.1%
15 864.5 6.315 0.7%
17 958.1 1.474 0.1%
19 1060 1.489 0.1%
21 1157 4.945 0.4%
23 1261 8.214 0.6%
25 1360 6.858 0.5%
27 1468 9.83 0.6%
29 1555 3.955 0.2%
31 1660 9.084 0.5%
33 1765 5.627 0.3%
35 1863 2.698 0.1%
37 1967 9.533 0.4%
39 2057 8.596 0.4%
41 2156 10.78 0.4%
43 2266 11.36 0.5%
45 2370 8.324 0.3%
47 2467 14.9 0.6%
49 2561 8.974 0.3%
51 2656 9.105 0.3%
53 2763 10.07 0.3%
55 2867 12.2 0.4%
57 2969 9.981 0.3%
59 3073 6.603 0.2%
61 3166 8.596 0.2%
63 3303 23.8 0.7%
65 3366 10.82 0.3%
67 3448 13.53 0.3%
69 3576 6.129 0.1%
71 3689 10.56 0.2%
73 3783 11.99 0.3%
75 3884 12.99 0.3%
77 3950 9.645 0.2%
79 4061 3.089 0.0%
81 4167 12.11 0.2%
83 4255 3.45 0.0%
85 4366 8.756 0.2%
87 4480 7.646 0.1%
89 4566 10.14 0.2%
91 4675 8.488 0.1%
93 4747 10.18 0.2%
95 4868 7.967 0.1%
97 4952 10.68 0.2%
99 5065 22.94 0.4%
101 5178 17.88 0.3%
103 5247 11.13 0.2%
105 5356 6.832 0.1%
107 5448 8.814 0.1%
109 5560 9.34 0.1%
111 5673 10.18 0.1%
113 5729 9.31 0.1%
115 5868 14.94 0.2%
117 5929 12.02 0.2%
119 6051 11.99 0.1%
121 6159 9.605 0.1%
123 6230 10.34 0.1%
125 6341 14.94 0.2%
127 6455 3.431 0.0%

Quality and confidence:
param error
n 0.017

Model:
Time ~= 114.4
+ n 49.95
µs

Reads = 11 + (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 ~= 141
+ n 63.65
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 195.9 0.583 0.2%
3 326.9 0.515 0.1%
5 453.8 1.268 0.2%
7 576.4 0.79 0.1%
9 713.5 0.986 0.1%
11 840.5 1.974 0.2%
13 965.8 3.103 0.3%
15 1091 8.369 0.7%
17 1222 1.678 0.1%
19 1363 16.38 1.2%
21 1479 2.393 0.1%
23 1615 9.821 0.6%
25 1744 14.71 0.8%
27 1856 7.494 0.4%
29 1994 7.067 0.3%
31 2134 11.72 0.5%
33 2241 9.873 0.4%
35 2368 11.75 0.4%
37 2502 15.85 0.6%
39 2613 16.44 0.6%
41 2742 11.64 0.4%
43 2905 19.41 0.6%
45 3008 10.63 0.3%
47 3131 14.09 0.4%
49 3288 12.14 0.3%
51 3402 5.756 0.1%
53 3520 11.57 0.3%
55 3655 9.587 0.2%
57 3755 7.885 0.2%
59 3917 18.09 0.4%
61 4027 7.067 0.1%
63 4158 8.892 0.2%
65 4316 26.73 0.6%
67 4408 7.656 0.1%
69 4512 9.552 0.2%
71 4644 16.56 0.3%
73 4760 10.83 0.2%
75 4925 12.07 0.2%
77 5019 14.75 0.2%
79 5160 9.696 0.1%
81 5267 9.687 0.1%
83 5425 8.734 0.1%
85 5523 4.329 0.0%
87 5700 9.474 0.1%
89 5830 11.4 0.1%
91 5957 12.18 0.2%
93 6042 8.664 0.1%
95 6216 14.73 0.2%
97 6329 9.225 0.1%
99 6470 11.33 0.1%
101 6570 9.516 0.1%
103 6711 12.87 0.1%
105 6828 13.9 0.2%
107 6970 15.76 0.2%
109 7087 18.63 0.2%
111 7234 16.48 0.2%
113 7341 17.53 0.2%
115 7469 12.75 0.1%
117 7616 11 0.1%
119 7698 12.82 0.1%
121 7837 12.78 0.1%
123 7911 14.13 0.1%
125 8064 13.75 0.1%
127 8239 21.92 0.2%

Quality and confidence:
param error
n 0.022

Model:
Time ~= 143.4
+ n 63.65
µs

Reads = 12 + (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 ~= 38.3
+ l 0.084
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
l mean µs sigma µs %
1 38.42 0.15 0.3%
2 38.31 0.064 0.1%
3 38.22 0.096 0.2%
4 38.28 0.086 0.2%
5 38.61 0.059 0.1%
6 38.71 0.05 0.1%
7 38.78 0.097 0.2%
8 38.89 0.087 0.2%
9 39.31 0.058 0.1%
10 39.1 0.083 0.2%
11 39.28 0.081 0.2%
12 39.27 0.079 0.2%
13 39.55 0.126 0.3%
14 39.58 0.049 0.1%
15 39.64 0.117 0.2%
16 39.58 0.125 0.3%
17 40.11 0.071 0.1%
18 40.45 0.388 0.9%
19 40.37 0.081 0.2%
20 40.22 0.135 0.3%
21 40.29 0.1 0.2%
22 40.26 0.098 0.2%
23 40.42 0.078 0.1%
24 40.34 0.044 0.1%
25 41.2 0.377 0.9%
26 40.75 0.247 0.6%
27 40.31 0.102 0.2%
28 40.48 0.141 0.3%
29 40.6 0.108 0.2%
30 40.41 0.048 0.1%
31 40.53 0.108 0.2%
32 40.55 0.116 0.2%

Quality and confidence:
param error
l 0.001

Model:
Time ~= 38.31
+ l 0.085
µs

Reads = 4 + (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 31.02
µs

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

-- Extrinsic Time --

Data points distribution:
e mean µs sigma µs %
1 37.28 0.169 0.4%
2 61.52 0.177 0.2%
3 84.99 0.343 0.4%
4 110.1 0.146 0.1%
5 132.8 0.223 0.1%
6 154.7 0.148 0.0%
7 179.5 0.286 0.1%
8 203.5 0.645 0.3%
9 228.9 0.294 0.1%
10 252.9 0.475 0.1%
11 276.1 0.529 0.1%
12 301.9 0.605 0.2%
13 326.2 1.044 0.3%
14 352.6 0.784 0.2%
15 379.6 1.035 0.2%
16 402.3 0.88 0.2%
17 425.5 1.176 0.2%
18 453.7 2.233 0.4%
19 480 1.068 0.2%
20 503.6 1.522 0.3%
21 537.1 0.907 0.1%
22 563.7 1.104 0.1%
23 593.6 0.628 0.1%
24 613.7 1.024 0.1%
25 642 1.029 0.1%
26 662 1.707 0.2%
27 693.5 1.308 0.1%
28 726.1 1.426 0.1%
29 750 3.607 0.4%
30 780.6 7.236 0.9%
31 804.6 3.306 0.4%
32 837.1 2.22 0.2%
33 862.5 2.371 0.2%
34 893.4 2.303 0.2%
35 925.6 3.559 0.3%
36 946.7 2.658 0.2%
37 981.5 2.306 0.2%
38 1006 3.771 0.3%
39 1036 8.284 0.7%
40 1066 1.904 0.1%
41 1088 3.43 0.3%
42 1121 2.819 0.2%
43 1157 2.666 0.2%
44 1186 1.809 0.1%
45 1220 2.533 0.2%
46 1255 8.181 0.6%
47 1289 6.685 0.5%
48 1313 3.481 0.2%
49 1329 7.253 0.5%
50 1366 2.758 0.2%
51 1383 2.699 0.1%
52 1423 3.079 0.2%
53 1460 3.492 0.2%
54 1494 5.351 0.3%
55 1515 9.454 0.6%
56 1566 6.353 0.4%
57 1606 4.339 0.2%
58 1644 10.98 0.6%
59 1675 11.93 0.7%
60 1707 6.974 0.4%
61 1714 5.895 0.3%
62 1761 9.182 0.5%
63 1785 8.199 0.4%
64 1815 8.244 0.4%
65 1854 5.368 0.2%
66 1901 11.96 0.6%
67 1937 7.447 0.3%
68 1937 10.64 0.5%
69 1975 10.99 0.5%
70 2003 11.33 0.5%
71 2059 7 0.3%
72 2107 15.31 0.7%
73 2139 10.59 0.4%
74 2161 9.082 0.4%
75 2182 8.913 0.4%
76 2246 12.97 0.5%
77 2278 11.28 0.4%
78 2270 9.389 0.4%
79 2335 10.42 0.4%
80 2364 5.496 0.2%
81 2403 9.363 0.3%
82 2438 12.13 0.4%
83 2466 12.53 0.5%
84 2534 16.78 0.6%
85 2550 10.72 0.4%
86 2602 8.836 0.3%
87 2625 11.58 0.4%
88 2675 12.43 0.4%
89 2710 13.95 0.5%
90 2751 11.3 0.4%
91 2793 11.81 0.4%
92 2828 19.48 0.6%
93 2846 11.24 0.3%
94 2862 3.48 0.1%
95 2972 4.984 0.1%
96 2954 4.358 0.1%
97 3002 10.63 0.3%
98 3009 7.9 0.2%
99 3101 5.982 0.1%
100 3131 17.35 0.5%

Quality and confidence:
param error
e 0.066

Model:
Time ~= 0
+ e 31.18
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 ~= 62.5
+ s 2.585
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 64.13 0.109 0.1%
2 66.58 0.049 0.0%
3 69.26 0.116 0.1%
4 72.55 0.093 0.1%
5 75.45 0.093 0.1%
6 77.7 0.107 0.1%
7 80.31 0.124 0.1%
8 82.96 0.09 0.1%
9 85.51 0.101 0.1%
10 88.05 0.136 0.1%
11 90.84 0.174 0.1%
12 93.59 0.166 0.1%
13 96.34 0.165 0.1%
14 98.79 0.081 0.0%
15 101.4 0.143 0.1%
16 104 0.113 0.1%
17 106.5 0.202 0.1%
18 109.5 0.19 0.1%
19 111.6 0.123 0.1%
20 114.4 0.198 0.1%
21 116.8 0.101 0.0%
22 119.2 0.156 0.1%
23 122.2 0.124 0.1%
24 125.2 0.108 0.0%
25 127.9 0.243 0.1%
26 130.2 0.242 0.1%
27 132.5 0.209 0.1%
28 135.2 0.211 0.1%
29 137.7 0.144 0.1%
30 141.1 0.809 0.5%
31 142.7 0.281 0.1%
32 145.4 0.157 0.1%
33 149.2 1.327 0.8%
34 150.6 0.276 0.1%
35 153 0.211 0.1%
36 155.4 0.359 0.2%
37 158.1 0.211 0.1%
38 161 0.346 0.2%
39 163.3 0.09 0.0%
40 166.2 0.234 0.1%
41 168.4 0.206 0.1%
42 171.6 0.33 0.1%
43 174 0.41 0.2%
44 176.8 0.292 0.1%
45 179.7 1.231 0.6%
46 181.7 0.327 0.1%
47 183.8 0.337 0.1%
48 186.9 0.311 0.1%
49 189.5 0.384 0.2%
50 191.3 0.187 0.0%
51 193.8 0.299 0.1%
52 196.3 0.395 0.2%
53 199.4 0.335 0.1%
54 201.8 0.378 0.1%
55 205 0.282 0.1%
56 207.3 0.389 0.1%
57 209.9 0.249 0.1%
58 212.2 0.456 0.2%
59 216.3 1.37 0.6%
60 216.9 0.391 0.1%
61 220.3 0.35 0.1%
62 222.6 0.219 0.0%
63 225.7 0.383 0.1%
64 227.9 0.243 0.1%
65 230.9 0.199 0.0%
66 232.6 0.628 0.2%
67 235.5 0.44 0.1%
68 238.3 0.381 0.1%
69 240.7 0.263 0.1%
70 243 0.68 0.2%
71 246 0.275 0.1%
72 249.8 2.835 1.1%
73 251.1 0.252 0.1%
74 253.9 0.496 0.1%
75 256 0.332 0.1%
76 258.5 0.231 0.0%
77 261.4 0.427 0.1%
78 263.8 0.419 0.1%
79 267.3 0.679 0.2%
80 269 0.464 0.1%
81 271.7 0.46 0.1%
82 274.5 0.385 0.1%
83 276.1 0.524 0.1%
84 278.7 0.311 0.1%
85 282 0.355 0.1%
86 283.8 0.288 0.1%
87 286.6 0.577 0.2%
88 288.6 0.486 0.1%
89 291.7 0.423 0.1%
90 294.3 0.429 0.1%
91 297.8 2.162 0.7%
92 301.5 0.603 0.1%
93 302.9 0.654 0.2%
94 305.6 0.228 0.0%
95 307.4 0.422 0.1%
96 311.3 0.563 0.1%
97 314.4 0.37 0.1%
98 317.3 0.348 0.1%
99 321 1.101 0.3%
100 321.5 0.632 0.1%

Quality and confidence:
param error
s 0

Model:
Time ~= 62.5
+ s 2.587
µs

Reads = 4 + (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 554
+ n 80.03
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n mean µs sigma µs %
1 100 3571 5.9 0.1%
2 100 4184 14 0.3%
3 100 4682 37.21 0.7%
4 100 5110 7.658 0.1%
5 100 5718 10.76 0.1%
6 100 6207 12.41 0.2%
7 100 6760 8.261 0.1%
8 100 7278 10.44 0.1%
9 100 8040 16.25 0.2%
10 1 687.4 0.618 0.0%
10 2 774.8 5.075 0.6%
10 3 850.6 3.924 0.4%
10 4 930.9 2.957 0.3%
10 5 1016 2.759 0.2%
10 6 1090 10.84 0.9%
10 7 1195 1.454 0.1%
10 8 1250 7.741 0.6%
10 9 1333 11.37 0.8%
10 10 1427 12.99 0.9%
10 11 1504 11.34 0.7%
10 12 1575 10.84 0.6%
10 13 1642 3.18 0.1%
10 14 1724 3.183 0.1%
10 15 1808 10.04 0.5%
10 16 1891 11.59 0.6%
10 17 1961 8.183 0.4%
10 18 2045 12.27 0.5%
10 19 2125 13.95 0.6%
10 20 2231 17.95 0.8%
10 21 2289 1.789 0.0%
10 22 2392 12.15 0.5%
10 23 2463 10.51 0.4%
10 24 2540 11.91 0.4%
10 25 2628 13.29 0.5%
10 26 2715 14.99 0.5%
10 27 2796 12.28 0.4%
10 28 2858 14.44 0.5%
10 29 2937 11.24 0.3%
10 30 3021 12.96 0.4%
10 31 3102 11.52 0.3%
10 32 3187 10.2 0.3%
10 33 3248 11.54 0.3%
10 34 3378 25.78 0.7%
10 35 3492 16.66 0.4%
10 36 3503 12.05 0.3%
10 37 3575 8.185 0.2%
10 38 3654 8.441 0.2%
10 39 3771 6.83 0.1%
10 40 3835 11.68 0.3%
10 41 3905 13.61 0.3%
10 42 3983 4.893 0.1%
10 43 4069 7.935 0.1%
10 44 4157 8.512 0.2%
10 45 4237 5.757 0.1%
10 46 4320 14.65 0.3%
10 47 4379 9.718 0.2%
10 48 4452 4.666 0.1%
10 49 4542 6.123 0.1%
10 50 4624 6.69 0.1%
10 51 4669 7.033 0.1%
10 52 4774 8.439 0.1%
10 53 4848 13.46 0.2%
10 54 4920 6.703 0.1%
10 55 5015 3.363 0.0%
10 56 5112 12.77 0.2%
10 57 5150 5.176 0.1%
10 58 5280 5.175 0.0%
10 59 5342 6.018 0.1%
10 60 5420 9.577 0.1%
10 61 5495 6.541 0.1%
10 62 5587 11.88 0.2%
10 63 5655 6.003 0.1%
10 64 5764 11.28 0.1%
10 65 5842 6.757 0.1%
10 66 5922 8.405 0.1%
10 67 5995 11.1 0.1%
10 68 6048 8.7 0.1%
10 69 6151 11.73 0.1%
10 70 6202 10.46 0.1%
10 71 6287 13.69 0.2%
10 72 6368 10.31 0.1%
10 73 6450 7.848 0.1%
10 74 6529 14.05 0.2%
10 75 6614 4.955 0.0%
10 76 6702 15.92 0.2%
10 77 6750 7.065 0.1%
10 78 6864 9.149 0.1%
10 79 6898 9.551 0.1%
10 80 7043 5.411 0.0%
10 81 7118 11.27 0.1%
10 82 7205 9.328 0.1%
10 83 7269 12.58 0.1%
10 84 7351 15.71 0.2%
10 85 7421 19.57 0.2%
10 86 7511 13.15 0.1%
10 87 7565 6.316 0.0%
10 88 7684 5.529 0.0%
10 89 7748 14.73 0.1%
10 90 7842 17.97 0.2%
10 91 7976 58.6 0.7%
10 92 7979 18.52 0.2%
10 93 8056 12.22 0.1%
10 94 8131 6.013 0.0%
10 95 8232 7.064 0.0%
10 96 8314 13.01 0.1%
10 97 8377 15.96 0.1%
10 98 8430 11.03 0.1%
10 99 8533 7.843 0.0%
10 100 8604 14.14 0.1%

Quality and confidence:
param error
v 0.81
n 0.04

Model:
Time ~= 0
+ v 568.9
+ n 79.85
µs

Reads = 9 + (4 * v) + (3 * n)
Writes = 13 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "submit_solution_better", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 1.051
+ n 0.415
+ a 71.7
+ w 7.779
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n a w mean µs sigma µs %
200 1000 400 100 29700 91.15 0.3%
204 1000 400 100 29590 52.88 0.1%
208 1000 400 100 29790 42.93 0.1%
212 1000 400 100 29740 61.51 0.2%
216 1000 400 100 29780 35.43 0.1%
220 1000 400 100 29640 60.85 0.2%
224 1000 400 100 29860 23.82 0.0%
228 1000 400 100 29760 40.46 0.1%
232 1000 400 100 29610 64.12 0.2%
236 1000 400 100 29790 36.5 0.1%
240 1000 400 100 29760 43.02 0.1%
244 1000 400 100 29680 50.48 0.1%
248 1000 400 100 29810 31.73 0.1%
252 1000 400 100 29730 34.93 0.1%
256 1000 400 100 29850 66.19 0.2%
260 1000 400 100 29630 59.84 0.2%
264 1000 400 100 29820 79.44 0.2%
268 1000 400 100 29600 46.94 0.1%
272 1000 400 100 29620 29.73 0.1%
276 1000 400 100 29830 66.57 0.2%
280 1000 400 100 29830 67.86 0.2%
284 1000 400 100 29650 72.06 0.2%
288 1000 400 100 29710 61.64 0.2%
292 1000 400 100 29980 27.63 0.0%
296 1000 400 100 29780 66.77 0.2%
300 1000 400 100 29850 62.63 0.2%
304 1000 400 100 29680 83.94 0.2%
308 1000 400 100 29810 36.56 0.1%
312 1000 400 100 29850 45.85 0.1%
316 1000 400 100 29880 75.43 0.2%
320 1000 400 100 29900 77.7 0.2%
324 1000 400 100 29740 85.17 0.2%
328 1000 400 100 29950 37.58 0.1%
332 1000 400 100 29990 45.3 0.1%
336 1000 400 100 29920 35.54 0.1%
340 1000 400 100 29830 37.14 0.1%
344 1000 400 100 29890 78.07 0.2%
348 1000 400 100 29940 61.11 0.2%
352 1000 400 100 29930 45.31 0.1%
356 1000 400 100 29890 38.12 0.1%
360 1000 400 100 29990 49.47 0.1%
364 1000 400 100 29780 31.78 0.1%
368 1000 400 100 29790 35.61 0.1%
372 1000 400 100 29910 48.09 0.1%
376 1000 400 100 29940 38.74 0.1%
380 1000 400 100 29920 48.1 0.1%
384 1000 400 100 30050 56.8 0.1%
388 1000 400 100 29900 53.58 0.1%
392 1000 400 100 29730 57.46 0.1%
396 1000 400 100 29860 40.17 0.1%
400 500 400 100 29630 59.04 0.1%
400 510 400 100 29520 42.89 0.1%
400 520 400 100 29690 72.75 0.2%
400 530 400 100 29700 42.06 0.1%
400 540 400 100 29670 64.22 0.2%
400 550 400 100 29750 78.17 0.2%
400 560 400 100 29830 32.89 0.1%
400 570 400 100 29830 28.66 0.0%
400 580 400 100 29790 44.46 0.1%
400 590 400 100 29700 76.67 0.2%
400 600 400 100 29640 67.44 0.2%
400 610 400 100 29780 45.76 0.1%
400 620 400 100 29890 47.87 0.1%
400 630 400 100 29860 27.08 0.0%
400 640 400 100 29750 62.34 0.2%
400 650 400 100 29830 51.43 0.1%
400 660 400 100 29780 41.54 0.1%
400 670 400 100 29670 36.86 0.1%
400 680 400 100 29840 43.27 0.1%
400 690 400 100 29700 34.99 0.1%
400 700 400 100 29740 32.17 0.1%
400 710 400 100 29760 42.54 0.1%
400 720 400 100 29700 42.02 0.1%
400 730 400 100 29960 62.48 0.2%
400 740 400 100 29920 35.04 0.1%
400 750 400 100 29900 43.23 0.1%
400 760 400 100 29900 33.9 0.1%
400 770 400 100 29820 79.76 0.2%
400 780 400 100 29860 48.55 0.1%
400 790 400 100 29780 49.71 0.1%
400 800 400 100 29840 51.65 0.1%
400 810 400 100 29930 40.44 0.1%
400 820 400 100 29910 50.09 0.1%
400 830 400 100 29840 37.04 0.1%
400 840 400 100 29780 29.08 0.0%
400 850 400 100 29810 34.97 0.1%
400 860 400 100 29870 51.02 0.1%
400 870 400 100 29870 80.13 0.2%
400 880 400 100 30020 48.24 0.1%
400 890 400 100 29920 42.54 0.1%
400 900 400 100 29920 52.17 0.1%
400 910 400 100 29880 44.76 0.1%
400 920 400 100 29820 48.72 0.1%
400 930 400 100 29910 65.27 0.2%
400 940 400 100 29960 42.26 0.1%
400 950 400 100 29900 45.23 0.1%
400 960 400 100 29860 78.13 0.2%
400 970 400 100 29880 45.69 0.1%
400 980 400 100 30020 50.63 0.1%
400 990 400 100 29860 34.77 0.1%
400 1000 200 100 15400 53.39 0.3%
400 1000 204 100 15670 38.88 0.2%
400 1000 208 100 15980 8.702 0.0%
400 1000 212 100 16260 35.28 0.2%
400 1000 216 100 16560 21.62 0.1%
400 1000 220 100 16850 21.29 0.1%
400 1000 224 100 17100 39.04 0.2%
400 1000 228 100 17370 38.36 0.2%
400 1000 232 100 17830 33.53 0.1%
400 1000 236 100 18080 61.98 0.3%
400 1000 240 100 18380 16.78 0.0%
400 1000 244 100 18670 44.12 0.2%
400 1000 248 100 18950 25.6 0.1%
400 1000 252 100 19210 29.05 0.1%
400 1000 256 100 19480 37.89 0.1%
400 1000 260 100 19850 34.01 0.1%
400 1000 264 100 20110 43.59 0.2%
400 1000 268 100 20390 40.94 0.2%
400 1000 272 100 20680 32.57 0.1%
400 1000 276 100 20960 23.55 0.1%
400 1000 280 100 21260 39.01 0.1%
400 1000 284 100 21540 43.98 0.2%
400 1000 288 100 21760 47.13 0.2%
400 1000 292 100 22110 41.78 0.1%
400 1000 296 100 22350 28.3 0.1%
400 1000 300 100 22650 34.13 0.1%
400 1000 304 100 22920 27.99 0.1%
400 1000 308 100 23190 43.71 0.1%
400 1000 312 100 23470 43.79 0.1%
400 1000 316 100 23770 42.75 0.1%
400 1000 320 100 24020 45.45 0.1%
400 1000 324 100 24260 55.68 0.2%
400 1000 328 100 24600 48.71 0.1%
400 1000 332 100 24900 27.04 0.1%
400 1000 336 100 25150 41.13 0.1%
400 1000 340 100 25510 40.91 0.1%
400 1000 344 100 25740 45.41 0.1%
400 1000 348 100 26060 47.99 0.1%
400 1000 352 100 26350 61.33 0.2%
400 1000 356 100 26640 40.47 0.1%
400 1000 360 100 26900 47.46 0.1%
400 1000 364 100 27150 44.13 0.1%
400 1000 368 100 27470 61.06 0.2%
400 1000 372 100 27830 54.82 0.1%
400 1000 376 100 28040 52.31 0.1%
400 1000 380 100 28300 57.77 0.2%
400 1000 384 100 28640 44.56 0.1%
400 1000 388 100 28950 33.31 0.1%
400 1000 392 100 29180 44.72 0.1%
400 1000 396 100 29560 63.3 0.2%
400 1000 400 16 29370 47.96 0.1%
400 1000 400 17 29310 37.95 0.1%
400 1000 400 18 29340 44.59 0.1%
400 1000 400 19 29320 53.74 0.1%
400 1000 400 20 29530 46.48 0.1%
400 1000 400 21 29440 60.45 0.2%
400 1000 400 22 29290 29.07 0.0%
400 1000 400 23 29390 49.04 0.1%
400 1000 400 24 29470 67.12 0.2%
400 1000 400 25 29270 39.13 0.1%
400 1000 400 26 29340 52.56 0.1%
400 1000 400 27 29360 40.57 0.1%
400 1000 400 28 29350 27.18 0.0%
400 1000 400 29 29260 77.86 0.2%
400 1000 400 30 29450 65.97 0.2%
400 1000 400 31 29320 69.82 0.2%
400 1000 400 32 29500 54.51 0.1%
400 1000 400 33 29490 75.37 0.2%
400 1000 400 34 29490 52.43 0.1%
400 1000 400 35 29270 37.08 0.1%
400 1000 400 36 29480 98.18 0.3%
400 1000 400 37 29430 62.28 0.2%
400 1000 400 38 29570 43.99 0.1%
400 1000 400 39 29390 55.22 0.1%
400 1000 400 40 29670 76.48 0.2%
400 1000 400 41 29520 56.45 0.1%
400 1000 400 42 29500 48.7 0.1%
400 1000 400 43 29580 38.1 0.1%
400 1000 400 44 29760 58.31 0.1%
400 1000 400 45 29610 40.26 0.1%
400 1000 400 46 29550 107.8 0.3%
400 1000 400 47 29700 51.27 0.1%
400 1000 400 48 29630 90.34 0.3%
400 1000 400 49 29490 68.59 0.2%
400 1000 400 50 29620 36.58 0.1%
400 1000 400 51 29700 52.11 0.1%
400 1000 400 52 29570 34.52 0.1%
400 1000 400 53 29440 85.33 0.2%
400 1000 400 54 29390 83.25 0.2%
400 1000 400 55 29350 55.67 0.1%
400 1000 400 56 29610 35.44 0.1%
400 1000 400 57 29370 51.83 0.1%
400 1000 400 58 29430 58 0.1%
400 1000 400 59 29560 76.4 0.2%
400 1000 400 60 29640 87.68 0.2%
400 1000 400 61 29490 53.2 0.1%
400 1000 400 62 29700 46.27 0.1%
400 1000 400 63 29570 80.44 0.2%
400 1000 400 64 29670 70.28 0.2%
400 1000 400 65 29490 61.26 0.2%
400 1000 400 66 29590 44.78 0.1%
400 1000 400 67 29710 51.69 0.1%
400 1000 400 68 29690 60.46 0.2%
400 1000 400 69 29760 88.27 0.2%
400 1000 400 70 29880 58.55 0.1%
400 1000 400 71 29590 57.12 0.1%
400 1000 400 72 29760 63.15 0.2%
400 1000 400 73 29790 44.25 0.1%
400 1000 400 74 29740 111.4 0.3%
400 1000 400 75 29850 63.53 0.2%
400 1000 400 76 29740 75.62 0.2%
400 1000 400 77 30060 131.5 0.4%
400 1000 400 78 29650 74.04 0.2%
400 1000 400 79 29750 71.1 0.2%
400 1000 400 80 29700 32.86 0.1%
400 1000 400 81 29970 50.32 0.1%
400 1000 400 82 29880 65.49 0.2%
400 1000 400 83 29870 85.27 0.2%
400 1000 400 84 29890 67.26 0.2%
400 1000 400 85 29900 93.81 0.3%
400 1000 400 86 29950 54.47 0.1%
400 1000 400 87 29950 57.85 0.1%
400 1000 400 88 29940 66.35 0.2%
400 1000 400 89 30050 66.66 0.2%
400 1000 400 90 29780 82.47 0.2%
400 1000 400 91 29820 68.13 0.2%
400 1000 400 92 30020 72.55 0.2%
400 1000 400 93 30010 50.97 0.1%
400 1000 400 94 29840 58.33 0.1%
400 1000 400 95 29890 71.77 0.2%
400 1000 400 96 30090 81.34 0.2%
400 1000 400 97 29980 43.48 0.1%
400 1000 400 98 30040 62.73 0.2%
400 1000 400 99 29930 74.5 0.2%
400 1000 400 100 29850 66.62 0.2%

Quality and confidence:
param error
v 0.053
n 0.021
a 0.053
w 0.11

Model:
Time ~= 0
+ v 1.082
+ n 0.408
+ a 72.58
+ w 7.046
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 26.35
+ n 63.12
+ s 11.45
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n s mean µs sigma µs %
200 400 20 30510 38.16 0.1%
204 400 20 30520 90.37 0.2%
208 400 20 30850 39.45 0.1%
212 400 20 30740 105 0.3%
216 400 20 30740 90.1 0.2%
220 400 20 30960 32.71 0.1%
224 400 20 31220 74.52 0.2%
228 400 20 31330 69.39 0.2%
232 400 20 31070 63.33 0.2%
236 400 20 31390 70.85 0.2%
240 400 20 31470 144.7 0.4%
244 400 20 31620 68.7 0.2%
248 400 20 31920 78.61 0.2%
252 400 20 31810 62.52 0.1%
256 400 20 31940 106.8 0.3%
260 400 20 31770 135.4 0.4%
264 400 20 32240 98.93 0.3%
268 400 20 32170 105.4 0.3%
272 400 20 32120 76.63 0.2%
276 400 20 32290 35.18 0.1%
280 400 20 32740 71.33 0.2%
284 400 20 32380 64.94 0.2%
288 400 20 32750 59.69 0.1%
292 400 20 32960 116.7 0.3%
296 400 20 33220 85.49 0.2%
300 400 20 32910 45.67 0.1%
304 400 20 33300 64.53 0.1%
308 400 20 33280 36.17 0.1%
312 400 20 33050 55.78 0.1%
316 400 20 33160 88.5 0.2%
320 400 20 33730 36.73 0.1%
324 400 20 33680 72.73 0.2%
328 400 20 33410 53.51 0.1%
332 400 20 33670 69.06 0.2%
336 400 20 34210 81.83 0.2%
340 400 20 34230 45.93 0.1%
344 400 20 34330 91.55 0.2%
348 400 20 34420 95.74 0.2%
352 400 20 34590 84.74 0.2%
356 400 20 34500 74.11 0.2%
360 400 20 34840 111.1 0.3%
364 400 20 34900 63.28 0.1%
368 400 20 34700 91.12 0.2%
372 400 20 35330 45.81 0.1%
376 400 20 34960 61.24 0.1%
380 400 20 35260 84.73 0.2%
384 400 20 35400 54.15 0.1%
388 400 20 35490 178 0.5%
392 400 20 35570 84.52 0.2%
396 400 20 35610 84.16 0.2%
400 200 20 23110 57.9 0.2%
400 204 20 23090 59.87 0.2%
400 208 20 23300 77.93 0.3%
400 212 20 23850 79.93 0.3%
400 216 20 24300 65.52 0.2%
400 220 20 24650 67.22 0.2%
400 224 20 24640 54.1 0.2%
400 228 20 25060 41.07 0.1%
400 232 20 25070 47.71 0.1%
400 236 20 25050 76.4 0.3%
400 240 20 25710 75.96 0.2%
400 244 20 25560 48.19 0.1%
400 248 20 26270 92.81 0.3%
400 252 20 26320 45.25 0.1%
400 256 20 26730 60.48 0.2%
400 260 20 26510 43.98 0.1%
400 264 20 27110 58.97 0.2%
400 268 20 27080 65.18 0.2%
400 272 20 27670 99.11 0.3%
400 276 20 27560 130.1 0.4%
400 280 20 27840 42.65 0.1%
400 284 20 28500 65.78 0.2%
400 288 20 28680 80.5 0.2%
400 292 20 28880 66.35 0.2%
400 296 20 29090 84.15 0.2%
400 300 20 29020 52.05 0.1%
400 304 20 29320 49.45 0.1%
400 308 20 30010 29.01 0.0%
400 312 20 30170 70.94 0.2%
400 316 20 30660 87.71 0.2%
400 320 20 30810 65.43 0.2%
400 324 20 30640 48.58 0.1%
400 328 20 31110 49.25 0.1%
400 332 20 31290 58.62 0.1%
400 336 20 31360 54.82 0.1%
400 340 20 31860 86.34 0.2%
400 344 20 32240 122.1 0.3%
400 348 20 32680 103.5 0.3%
400 352 20 32630 103.8 0.3%
400 356 20 32610 47.79 0.1%
400 360 20 32880 46.7 0.1%
400 364 20 33450 65.49 0.1%
400 368 20 33670 72.52 0.2%
400 372 20 34140 75.71 0.2%
400 376 20 34220 67.16 0.1%
400 380 20 34250 76.63 0.2%
400 384 20 34880 34.4 0.0%
400 388 20 35120 63.02 0.1%
400 392 20 35310 59.05 0.1%
400 396 20 35360 123.9 0.3%
400 400 1 35410 65.83 0.1%
400 400 2 35140 89.99 0.2%
400 400 3 35620 69.84 0.1%
400 400 4 35460 126.5 0.3%
400 400 5 35480 87.63 0.2%
400 400 6 35010 22.51 0.0%
400 400 7 35460 140.5 0.3%
400 400 8 35490 82.37 0.2%
400 400 9 35490 85.46 0.2%
400 400 10 35540 48.43 0.1%
400 400 11 35530 98.81 0.2%
400 400 12 35630 94.91 0.2%
400 400 13 35590 95.66 0.2%
400 400 14 35690 84.27 0.2%
400 400 15 35200 60.51 0.1%
400 400 16 35870 69.48 0.1%
400 400 17 35400 105.4 0.2%
400 400 18 35360 36.23 0.1%
400 400 19 35410 59.02 0.1%
400 400 20 35660 109.8 0.3%

Quality and confidence:
param error
v 0.111
n 0.111
s 1.523

Model:
Time ~= 0
+ v 26.17
+ n 63.28
+ s 18.75
µs

Reads = 2 + (4 * v) + (3 * n) + (0 * 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 ~= 0
+ v 9.959
µs

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

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
200 1928 21.7 1.1%
204 2000 11.91 0.5%
208 2021 22.17 1.0%
212 1984 8.453 0.4%
216 2110 12.77 0.6%
220 2158 10.04 0.4%
224 2130 9.997 0.4%
228 2214 12.47 0.5%
232 2177 3.88 0.1%
236 2314 17.69 0.7%
240 2357 14.64 0.6%
244 2339 15.28 0.6%
248 2395 13.85 0.5%
252 2432 14.2 0.5%
256 2462 18.73 0.7%
260 2521 8.092 0.3%
264 2573 8.395 0.3%
268 2588 13.38 0.5%
272 2682 10.84 0.4%
276 2742 21.94 0.8%
280 2727 26.11 0.9%
284 2771 13.91 0.5%
288 2805 21.34 0.7%
292 2874 19.86 0.6%
296 2900 29.19 1.0%
300 2930 14.49 0.4%
304 2955 14.59 0.4%
308 3003 10.97 0.3%
312 3069 19.86 0.6%
316 3134 22.27 0.7%
320 3044 16.28 0.5%
324 3165 25.7 0.8%
328 3159 20.06 0.6%
332 3236 17.91 0.5%
336 3324 32.42 0.9%
340 3295 14.91 0.4%
344 3342 14.29 0.4%
348 3381 17.18 0.5%
352 3478 26.71 0.7%
356 3456 25.28 0.7%
360 3482 15.76 0.4%
364 3601 16.66 0.4%
368 3581 28.75 0.8%
372 3682 26.31 0.7%
376 3751 17.86 0.4%
380 3696 10.13 0.2%
384 3707 14.09 0.3%
388 3775 21.53 0.5%
392 3779 16.83 0.4%
396 3956 17.19 0.4%
400 3970 24.94 0.6%

Quality and confidence:
param error
v 0.03

Model:
Time ~= 0
+ v 9.982
µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)

[kianenigma]

/benchmark runtime kusama pallet_election_provider_multi_phase

[parity-benchapp]

Finished benchmark for branch: kiz-rebench

Benchmark: Benchmark Runtime Kusama Pallet

cargo run --release --features=runtime-benchmarks -- benchmark --chain=kusama-dev --steps=50 --repeat=20 --pallet=pallet_election_provider_multi_phase --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --header=./file_header.txt --output=./runtime/kusama/src/weights/

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 ~= 21.51
µs

Reads = 7
Writes = 0
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 21.51
µs

Reads = 7
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 ~= 101.4
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 101.4
µs

Reads = 8
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 ~= 100.9
µs

Reads = 8
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 100.9
µs

Reads = 8
Writes = 4
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 ~= 19.08
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 19.08
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 ~= 7220
µs

Reads = 2
Writes = 6
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 7220
µs

Reads = 2
Writes = 6
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 3.89
+ t 0.089
+ a 12.47
+ d 7.07
µs

Reads = 6 + (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 55400 68.51 0.1%
4040 1600 3000 800 55490 80.35 0.1%
4080 1600 3000 800 55700 93.99 0.1%
4120 1600 3000 800 55790 72.48 0.1%
4160 1600 3000 800 56010 90.93 0.1%
4200 1600 3000 800 56080 68.72 0.1%
4240 1600 3000 800 56270 108.1 0.1%
4280 1600 3000 800 56400 131 0.2%
4320 1600 3000 800 56680 75.27 0.1%
4360 1600 3000 800 56710 110 0.1%
4400 1600 3000 800 56850 94.34 0.1%
4440 1600 3000 800 56970 69.58 0.1%
4480 1600 3000 800 57170 129.3 0.2%
4520 1600 3000 800 57280 79.46 0.1%
4560 1600 3000 800 57450 76.6 0.1%
4600 1600 3000 800 57590 102.9 0.1%
4640 1600 3000 800 57810 79.84 0.1%
4680 1600 3000 800 57960 61.07 0.1%
4720 1600 3000 800 58190 95.28 0.1%
4760 1600 3000 800 58270 118.9 0.2%
4800 1600 3000 800 58370 71.42 0.1%
4840 1600 3000 800 58480 105.5 0.1%
4880 1600 3000 800 58680 88.53 0.1%
4920 1600 3000 800 58880 130.3 0.2%
4960 1600 3000 800 59070 67.38 0.1%
5000 1600 3000 800 59090 47.43 0.0%
5040 1600 3000 800 59350 43.2 0.0%
5080 1600 3000 800 59520 153.6 0.2%
5120 1600 3000 800 59720 60.44 0.1%
5160 1600 3000 800 59750 59.16 0.0%
5200 1600 3000 800 59970 106.9 0.1%
5240 1600 3000 800 60130 49.69 0.0%
5280 1600 3000 800 60370 127.2 0.2%
5320 1600 3000 800 60430 111.8 0.1%
5360 1600 3000 800 60530 62.08 0.1%
5400 1600 3000 800 60730 113.5 0.1%
5440 1600 3000 800 60910 67.1 0.1%
5480 1600 3000 800 60990 105.3 0.1%
5520 1600 3000 800 61260 81.99 0.1%
5560 1600 3000 800 61430 132.5 0.2%
5600 1600 3000 800 61620 113.5 0.1%
5640 1600 3000 800 61690 77.46 0.1%
5680 1600 3000 800 61950 160.9 0.2%
5720 1600 3000 800 62070 110.2 0.1%
5760 1600 3000 800 62300 110.6 0.1%
5800 1600 3000 800 62260 71.15 0.1%
5840 1600 3000 800 62540 86.27 0.1%
5880 1600 3000 800 62600 71.6 0.1%
5920 1600 3000 800 62780 76.93 0.1%
5960 1600 3000 800 62890 80.69 0.1%
6000 1000 3000 800 63130 124 0.1%
6000 1012 3000 800 63060 71.41 0.1%
6000 1024 3000 800 63120 74.31 0.1%
6000 1036 3000 800 63080 98.81 0.1%
6000 1048 3000 800 63000 83.37 0.1%
6000 1060 3000 800 63110 90.24 0.1%
6000 1072 3000 800 63120 124.5 0.1%
6000 1084 3000 800 63040 117.1 0.1%
6000 1096 3000 800 62960 103.9 0.1%
6000 1108 3000 800 63040 112 0.1%
6000 1120 3000 800 63040 89.5 0.1%
6000 1132 3000 800 63050 72.76 0.1%
6000 1144 3000 800 62940 96.77 0.1%
6000 1156 3000 800 62990 94.51 0.1%
6000 1168 3000 800 62960 111.1 0.1%
6000 1180 3000 800 63080 110.9 0.1%
6000 1192 3000 800 62960 110.3 0.1%
6000 1204 3000 800 63060 74.67 0.1%
6000 1216 3000 800 62960 81.56 0.1%
6000 1228 3000 800 63040 81.5 0.1%
6000 1240 3000 800 62940 106.8 0.1%
6000 1252 3000 800 63060 70.02 0.1%
6000 1264 3000 800 62980 104.6 0.1%
6000 1276 3000 800 63230 119 0.1%
6000 1288 3000 800 63070 60.34 0.0%
6000 1300 3000 800 63120 64.25 0.1%
6000 1312 3000 800 63120 121.1 0.1%
6000 1324 3000 800 63190 143.7 0.2%
6000 1336 3000 800 63060 63.15 0.1%
6000 1348 3000 800 63150 93.34 0.1%
6000 1360 3000 800 63110 69.35 0.1%
6000 1372 3000 800 63170 116.6 0.1%
6000 1384 3000 800 62920 100.4 0.1%
6000 1396 3000 800 63130 131.2 0.2%
6000 1408 3000 800 63260 70.48 0.1%
6000 1420 3000 800 63060 81.86 0.1%
6000 1432 3000 800 63050 74.18 0.1%
6000 1444 3000 800 63160 90.15 0.1%
6000 1456 3000 800 63000 89.04 0.1%
6000 1468 3000 800 62980 75.98 0.1%
6000 1480 3000 800 62970 107.7 0.1%
6000 1492 3000 800 63080 72.85 0.1%
6000 1504 3000 800 63080 107.8 0.1%
6000 1516 3000 800 63010 87.08 0.1%
6000 1528 3000 800 63060 91.69 0.1%
6000 1540 3000 800 62960 102.7 0.1%
6000 1552 3000 800 63130 107 0.1%
6000 1564 3000 800 63040 113.7 0.1%
6000 1576 3000 800 63140 144.8 0.2%
6000 1588 3000 800 63160 79.84 0.1%
6000 1600 1000 800 37070 104.1 0.2%
6000 1600 1040 800 37580 86.55 0.2%
6000 1600 1080 800 38130 75.88 0.1%
6000 1600 1120 800 38520 48.69 0.1%
6000 1600 1160 800 39020 19.9 0.0%
6000 1600 1200 800 39430 52.76 0.1%
6000 1600 1240 800 39830 89.41 0.2%
6000 1600 1280 800 40300 53.11 0.1%
6000 1600 1320 800 40730 53.47 0.1%
6000 1600 1360 800 41240 77.16 0.1%
6000 1600 1400 800 42720 55.64 0.1%
6000 1600 1440 800 43060 40.48 0.0%
6000 1600 1480 800 43590 114.1 0.2%
6000 1600 1520 800 44000 66.22 0.1%
6000 1600 1560 800 44600 101 0.2%
6000 1600 1600 800 45070 81.08 0.1%
6000 1600 1640 800 45630 41.59 0.0%
6000 1600 1680 800 46020 67.45 0.1%
6000 1600 1720 800 46530 81.89 0.1%
6000 1600 1760 800 47090 123.6 0.2%
6000 1600 1800 800 47570 89.57 0.1%
6000 1600 1840 800 47980 52.29 0.1%
6000 1600 1880 800 48550 68.88 0.1%
6000 1600 1920 800 48960 76.95 0.1%
6000 1600 1960 800 49490 55.82 0.1%
6000 1600 2000 800 49850 52.99 0.1%
6000 1600 2040 800 50400 66.16 0.1%
6000 1600 2080 800 50950 50.93 0.0%
6000 1600 2120 800 51380 79.53 0.1%
6000 1600 2160 800 51920 87.87 0.1%
6000 1600 2200 800 52220 64.88 0.1%
6000 1600 2240 800 52700 70.22 0.1%
6000 1600 2280 800 53030 87.13 0.1%
6000 1600 2320 800 53610 52.08 0.0%
6000 1600 2360 800 53950 72.47 0.1%
6000 1600 2400 800 54470 61.08 0.1%
6000 1600 2440 800 54820 75.05 0.1%
6000 1600 2480 800 55200 79.37 0.1%
6000 1600 2520 800 55740 50.09 0.0%
6000 1600 2560 800 56250 96.27 0.1%
6000 1600 2600 800 56630 98.21 0.1%
6000 1600 2640 800 57090 41.97 0.0%
6000 1600 2680 800 57570 81.6 0.1%
6000 1600 2720 800 58040 39.89 0.0%
6000 1600 2760 800 58490 69.07 0.1%
6000 1600 2800 800 58880 73.45 0.1%
6000 1600 2840 800 59520 82.79 0.1%
6000 1600 2880 800 61680 87.86 0.1%
6000 1600 2920 800 62230 92.26 0.1%
6000 1600 2960 800 62710 57.7 0.0%
6000 1600 3000 400 60720 60.15 0.0%
6000 1600 3000 408 60610 82.69 0.1%
6000 1600 3000 416 60520 119.6 0.1%
6000 1600 3000 424 60760 84.86 0.1%
6000 1600 3000 432 60700 104.6 0.1%
6000 1600 3000 440 60830 74.46 0.1%
6000 1600 3000 448 60830 66.57 0.1%
6000 1600 3000 456 61090 79.24 0.1%
6000 1600 3000 464 61070 66.14 0.1%
6000 1600 3000 472 61170 60.94 0.0%
6000 1600 3000 480 61220 69.01 0.1%
6000 1600 3000 488 61440 101.7 0.1%
6000 1600 3000 496 61380 80.41 0.1%
6000 1600 3000 504 61600 78.58 0.1%
6000 1600 3000 512 61590 90.15 0.1%
6000 1600 3000 520 61820 43.28 0.0%
6000 1600 3000 528 61940 56.91 0.0%
6000 1600 3000 536 62080 73.85 0.1%
6000 1600 3000 544 61950 93.45 0.1%
6000 1600 3000 552 62160 58.74 0.0%
6000 1600 3000 560 62060 120.4 0.1%
6000 1600 3000 568 62200 124.7 0.2%
6000 1600 3000 576 62310 87.67 0.1%
6000 1600 3000 584 62440 68 0.1%
6000 1600 3000 592 62490 43.06 0.0%
6000 1600 3000 600 62630 80.82 0.1%
6000 1600 3000 608 62670 89.05 0.1%
6000 1600 3000 616 62690 42.44 0.0%
6000 1600 3000 624 62870 37.47 0.0%
6000 1600 3000 632 62830 68.75 0.1%
6000 1600 3000 640 62830 92.76 0.1%
6000 1600 3000 648 62910 97.75 0.1%
6000 1600 3000 656 62940 42.47 0.0%
6000 1600 3000 664 62970 122.4 0.1%
6000 1600 3000 672 63100 74.61 0.1%
6000 1600 3000 680 63090 99.24 0.1%
6000 1600 3000 688 63110 83.37 0.1%
6000 1600 3000 696 63140 102.6 0.1%
6000 1600 3000 704 63170 68.81 0.1%
6000 1600 3000 712 63230 102.7 0.1%
6000 1600 3000 720 63210 79.85 0.1%
6000 1600 3000 728 63240 92.38 0.1%
6000 1600 3000 736 63190 58.09 0.0%
6000 1600 3000 744 63260 123.9 0.1%
6000 1600 3000 752 63130 56.31 0.0%
6000 1600 3000 760 63300 80.85 0.1%
6000 1600 3000 768 63130 71.1 0.1%
6000 1600 3000 776 63190 88.35 0.1%
6000 1600 3000 784 63290 71.54 0.1%
6000 1600 3000 792 63370 89.22 0.1%
6000 1600 3000 800 63130 81.03 0.1%

Quality and confidence:
param error
v 0.02
t 0.067
a 0.02
d 0.101

Model:
Time ~= 0
+ v 3.844
+ t 0
+ a 13.1
+ d 4.703
µs

Reads = 6 + (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 3.865
+ t 0.084
+ a 9.55
+ d 5.992
µs

Reads = 3 + (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 45080 60.11 0.1%
4040 1600 3000 800 45150 61.4 0.1%
4080 1600 3000 800 45320 48.16 0.1%
4120 1600 3000 800 45480 48.46 0.1%
4160 1600 3000 800 45660 44.65 0.0%
4200 1600 3000 800 45870 37.05 0.0%
4240 1600 3000 800 45940 60.87 0.1%
4280 1600 3000 800 46200 52.73 0.1%
4320 1600 3000 800 46240 78.1 0.1%
4360 1600 3000 800 46460 33.67 0.0%
4400 1600 3000 800 46540 78.9 0.1%
4440 1600 3000 800 46780 21.77 0.0%
4480 1600 3000 800 46870 38.86 0.0%
4520 1600 3000 800 47050 64.12 0.1%
4560 1600 3000 800 47230 83.53 0.1%
4600 1600 3000 800 47400 63.03 0.1%
4640 1600 3000 800 47540 41.85 0.0%
4680 1600 3000 800 47800 53.13 0.1%
4720 1600 3000 800 47880 119.3 0.2%
4760 1600 3000 800 48000 54.15 0.1%
4800 1600 3000 800 48180 30.06 0.0%
4840 1600 3000 800 48280 30.58 0.0%
4880 1600 3000 800 48530 36.68 0.0%
4920 1600 3000 800 48560 76.74 0.1%
4960 1600 3000 800 48700 68.43 0.1%
5000 1600 3000 800 48850 68.17 0.1%
5040 1600 3000 800 49000 65.33 0.1%
5080 1600 3000 800 49210 47.82 0.0%
5120 1600 3000 800 49380 74.35 0.1%
5160 1600 3000 800 49510 84.4 0.1%
5200 1600 3000 800 49720 61.4 0.1%
5240 1600 3000 800 49890 71.47 0.1%
5280 1600 3000 800 50010 88.28 0.1%
5320 1600 3000 800 50170 46.28 0.0%
5360 1600 3000 800 50360 35.74 0.0%
5400 1600 3000 800 50490 88.26 0.1%
5440 1600 3000 800 50580 41.79 0.0%
5480 1600 3000 800 50730 52.99 0.1%
5520 1600 3000 800 50940 83.23 0.1%
5560 1600 3000 800 51100 58.42 0.1%
5600 1600 3000 800 51260 37.3 0.0%
5640 1600 3000 800 51390 48.08 0.0%
5680 1600 3000 800 51440 108.1 0.2%
5720 1600 3000 800 51700 102.1 0.1%
5760 1600 3000 800 51910 89.35 0.1%
5800 1600 3000 800 52050 63.98 0.1%
5840 1600 3000 800 52070 101.5 0.1%
5880 1600 3000 800 52310 80.82 0.1%
5920 1600 3000 800 52460 40.96 0.0%
5960 1600 3000 800 52590 65.4 0.1%
6000 1000 3000 800 52690 86.66 0.1%
6000 1012 3000 800 52670 59.46 0.1%
6000 1024 3000 800 52800 54.92 0.1%
6000 1036 3000 800 52710 61.51 0.1%
6000 1048 3000 800 52700 77.24 0.1%
6000 1060 3000 800 52890 71.95 0.1%
6000 1072 3000 800 52860 79.67 0.1%
6000 1084 3000 800 52950 60.24 0.1%
6000 1096 3000 800 52840 59.73 0.1%
6000 1108 3000 800 52790 49.43 0.0%
6000 1120 3000 800 52890 56.68 0.1%
6000 1132 3000 800 52800 84.79 0.1%
6000 1144 3000 800 52780 70.47 0.1%
6000 1156 3000 800 52780 77.62 0.1%
6000 1168 3000 800 52690 107.8 0.2%
6000 1180 3000 800 52620 72.93 0.1%
6000 1192 3000 800 52730 84.94 0.1%
6000 1204 3000 800 52740 65.6 0.1%
6000 1216 3000 800 52680 100.1 0.1%
6000 1228 3000 800 52640 75.5 0.1%
6000 1240 3000 800 52800 50.76 0.0%
6000 1252 3000 800 52820 78.86 0.1%
6000 1264 3000 800 52730 77.56 0.1%
6000 1276 3000 800 52730 75.81 0.1%
6000 1288 3000 800 52800 38.46 0.0%
6000 1300 3000 800 52730 57.45 0.1%
6000 1312 3000 800 52730 51.28 0.0%
6000 1324 3000 800 52790 66.68 0.1%
6000 1336 3000 800 52720 104.9 0.1%
6000 1348 3000 800 52680 53.84 0.1%
6000 1360 3000 800 52720 99.77 0.1%
6000 1372 3000 800 52730 70.13 0.1%
6000 1384 3000 800 52670 71.32 0.1%
6000 1396 3000 800 52900 43.9 0.0%
6000 1408 3000 800 52860 82.2 0.1%
6000 1420 3000 800 52790 84.54 0.1%
6000 1432 3000 800 52850 59.7 0.1%
6000 1444 3000 800 52840 87.29 0.1%
6000 1456 3000 800 52700 110 0.2%
6000 1468 3000 800 52830 71.58 0.1%
6000 1480 3000 800 52860 55.45 0.1%
6000 1492 3000 800 52810 64.15 0.1%
6000 1504 3000 800 52750 40.88 0.0%
6000 1516 3000 800 52900 25.82 0.0%
6000 1528 3000 800 52910 75.17 0.1%
6000 1540 3000 800 52790 88.73 0.1%
6000 1552 3000 800 52820 36.53 0.0%
6000 1564 3000 800 52850 69.73 0.1%
6000 1576 3000 800 52800 86.9 0.1%
6000 1588 3000 800 52740 81.95 0.1%
6000 1600 1000 800 33630 73.77 0.2%
6000 1600 1040 800 34030 63.73 0.1%
6000 1600 1080 800 34380 86.59 0.2%
6000 1600 1120 800 34760 61.92 0.1%
6000 1600 1160 800 35120 48.52 0.1%
6000 1600 1200 800 35560 121.6 0.3%
6000 1600 1240 800 35880 92.46 0.2%
6000 1600 1280 800 36260 99.05 0.2%
6000 1600 1320 800 36650 89.11 0.2%
6000 1600 1360 800 37090 68.98 0.1%
6000 1600 1400 800 37470 76.87 0.2%
6000 1600 1440 800 37870 76.81 0.2%
6000 1600 1480 800 38180 53.28 0.1%
6000 1600 1520 800 38570 132.3 0.3%
6000 1600 1560 800 39070 60.25 0.1%
6000 1600 1600 800 39480 120.4 0.3%
6000 1600 1640 800 39950 44.45 0.1%
6000 1600 1680 800 40300 100.4 0.2%
6000 1600 1720 800 40780 64.91 0.1%
6000 1600 1760 800 41100 30.51 0.0%
6000 1600 1800 800 41510 61.61 0.1%
6000 1600 1840 800 42020 112.9 0.2%
6000 1600 1880 800 42430 86.21 0.2%
6000 1600 1920 800 42880 74.95 0.1%
6000 1600 1960 800 43140 107 0.2%
6000 1600 2000 800 43540 79.99 0.1%
6000 1600 2040 800 43950 80.55 0.1%
6000 1600 2080 800 44360 55.22 0.1%
6000 1600 2120 800 44680 68.3 0.1%
6000 1600 2160 800 45030 67.55 0.1%
6000 1600 2200 800 45520 61.83 0.1%
6000 1600 2240 800 45770 72.61 0.1%
6000 1600 2280 800 46080 88.19 0.1%
6000 1600 2320 800 46380 90.05 0.1%
6000 1600 2360 800 46880 56.93 0.1%
6000 1600 2400 800 47210 66 0.1%
6000 1600 2440 800 47440 98.19 0.2%
6000 1600 2480 800 47870 98.75 0.2%
6000 1600 2520 800 48140 76.41 0.1%
6000 1600 2560 800 48610 60.11 0.1%
6000 1600 2600 800 48910 82.66 0.1%
6000 1600 2640 800 49260 82.67 0.1%
6000 1600 2680 800 49640 68.16 0.1%
6000 1600 2720 800 49960 115 0.2%
6000 1600 2760 800 50340 90.7 0.1%
6000 1600 2800 800 50690 99.9 0.1%
6000 1600 2840 800 51140 59.15 0.1%
6000 1600 2880 800 51600 97.87 0.1%
6000 1600 2920 800 51950 57.82 0.1%
6000 1600 2960 800 52360 74.97 0.1%
6000 1600 3000 400 50700 95.93 0.1%
6000 1600 3000 408 50740 45.06 0.0%
6000 1600 3000 416 50720 54.72 0.1%
6000 1600 3000 424 50790 80.11 0.1%
6000 1600 3000 432 50800 92.58 0.1%
6000 1600 3000 440 50890 66.97 0.1%
6000 1600 3000 448 50940 110.6 0.2%
6000 1600 3000 456 51010 73.9 0.1%
6000 1600 3000 464 51170 32.97 0.0%
6000 1600 3000 472 51220 66.75 0.1%
6000 1600 3000 480 51300 74.43 0.1%
6000 1600 3000 488 51340 107.8 0.2%
6000 1600 3000 496 51440 113.5 0.2%
6000 1600 3000 504 51410 71.09 0.1%
6000 1600 3000 512 51560 115.5 0.2%
6000 1600 3000 520 51780 71.46 0.1%
6000 1600 3000 528 51820 80.66 0.1%
6000 1600 3000 536 51870 37.37 0.0%
6000 1600 3000 544 51930 86.42 0.1%
6000 1600 3000 552 51980 118.2 0.2%
6000 1600 3000 560 52170 81.5 0.1%
6000 1600 3000 568 52190 40.66 0.0%
6000 1600 3000 576 52320 72.87 0.1%
6000 1600 3000 584 52320 58.88 0.1%
6000 1600 3000 592 52440 92.87 0.1%
6000 1600 3000 600 52520 85.59 0.1%
6000 1600 3000 608 52570 100.2 0.1%
6000 1600 3000 616 52600 82.15 0.1%
6000 1600 3000 624 52670 96.06 0.1%
6000 1600 3000 632 52700 64.48 0.1%
6000 1600 3000 640 52780 67.36 0.1%
6000 1600 3000 648 52780 85.84 0.1%
6000 1600 3000 656 52800 73.07 0.1%
6000 1600 3000 664 52870 55.37 0.1%
6000 1600 3000 672 52960 67.14 0.1%
6000 1600 3000 680 53000 51.64 0.0%
6000 1600 3000 688 52930 111.5 0.2%
6000 1600 3000 696 52840 97.2 0.1%
6000 1600 3000 704 52890 62.95 0.1%
6000 1600 3000 712 52810 125.1 0.2%
6000 1600 3000 720 53010 27.77 0.0%
6000 1600 3000 728 52870 118.3 0.2%
6000 1600 3000 736 52950 78.65 0.1%
6000 1600 3000 744 52950 44.16 0.0%
6000 1600 3000 752 52790 120.4 0.2%
6000 1600 3000 760 52880 51 0.0%
6000 1600 3000 768 52790 66.26 0.1%
6000 1600 3000 776 52840 72.45 0.1%
6000 1600 3000 784 52920 62.87 0.1%
6000 1600 3000 792 52960 58.75 0.1%
6000 1600 3000 800 52810 69.45 0.1%

Quality and confidence:
param error
v 0.011
t 0.037
a 0.011
d 0.056

Model:
Time ~= 0
+ v 4.001
+ t 0.483
+ a 9.635
+ d 4.585
µs

Reads = 3 + (0 * v) + (0 * t) + (0 * a) + (0 * d)
Writes = 0 + (0 * v) + (0 * t) + (0 * a) + (0 * d)