measurementTime: 2 secs
# JMH 1.10.3 (released 31 days ago)
# VM version: JDK 1.8.0_51, VM 25.51-b03
# VM invoker: /opt/jdk1.8.0_51/jre/bin/java
# VM options: -XX:MaxInlineSize=400 -Xmx1g -Dverbose:gc -Didea.launcher.port=7538 -Didea.launcher.bin.path=/opt/idea-IU-142.3371.3/bin -Dfile.encoding=UTF-8
# Warmup: 20 iterations, 1 s each
# Measurement: 5 iterations, 2 s each
# Timeout: 10 min per iteration
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Sampling time
# Benchmark: net.openhft.chronicle.wire.benchmarks.ComparisonMain.bsonWithCBytes

# Run progress: 0.00% complete, ETA 00:05:00
# Fork: 1 of 10
# Warmup Iteration   1: n = 3123, mean = 317235 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 45312, 73088, 227072, 289690, 8844739, 30444093, 41549824, 41549824 ns/op
# Warmup Iteration   2: n = 13538, mean = 52518 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4464, 6344, 31232, 34304, 40334, 15760032, 31409291, 32047104 ns/op
# Warmup Iteration   3: n = 14852, mean = 22925 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4088, 5216, 6040, 6120, 7252, 8100413, 27460059, 28016640 ns/op
# Warmup Iteration   4: n = 24735, mean = 6923 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3820, 3964, 4036, 4068, 4152, 8541, 12018097, 48037888 ns/op
# Warmup Iteration   5: n = 18032, mean = 9329 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3708, 3892, 5304, 5952, 16005, 25469, 15309301, 28049408 ns/op
# Warmup Iteration   6: n = 14950, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3736, 3868, 3948, 3968, 4036, 7855, 95512, 176384 ns/op
# Warmup Iteration   7: n = 15374, mean = 3877 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3868, 3948, 3968, 4045, 5683, 16907, 18464 ns/op
# Warmup Iteration   8: n = 16346, mean = 3870 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3864, 3940, 3960, 4016, 4946, 11746, 12416 ns/op
# Warmup Iteration   9: n = 16341, mean = 3873 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3940, 3960, 4024, 6586, 14019, 15440 ns/op
# Warmup Iteration  10: n = 16370, mean = 3967 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3720, 3864, 3940, 3964, 4028, 7368, 561764, 1519616 ns/op
# Warmup Iteration  11: n = 16342, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3728, 3868, 3944, 3964, 4036, 6991, 12568, 12832 ns/op
# Warmup Iteration  12: n = 16348, mean = 3873 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3944, 3964, 4020, 4943, 13016, 14448 ns/op
# Warmup Iteration  13: n = 16320, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3944, 3964, 4028, 6647, 15861, 16640 ns/op
# Warmup Iteration  14: n = 16343, mean = 3878 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3868, 3944, 3968, 4024, 7421, 13664, 14192 ns/op
# Warmup Iteration  15: n = 16147, mean = 3875 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3944, 3964, 4020, 7351, 13186, 14032 ns/op
# Warmup Iteration  16: n = 16278, mean = 3874 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3728, 3864, 3944, 3964, 4032, 5333, 12715, 13328 ns/op
# Warmup Iteration  17: n = 16298, mean = 3875 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3944, 3964, 4024, 7519, 13512, 15104 ns/op
# Warmup Iteration  18: n = 16305, mean = 3871 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3864, 3940, 3960, 4020, 7203, 12142, 12576 ns/op
# Warmup Iteration  19: n = 16325, mean = 3970 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3716, 3864, 3944, 3964, 4028, 7289, 581271, 1560576 ns/op
# Warmup Iteration  20: n = 16284, mean = 3960 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3728, 3864, 3944, 3964, 4028, 5607, 531346, 1409024 ns/op
Iteration   1: n = 32586, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3728, 3864, 3944, 3960, 4028, 7299, 15199, 17280 ns/op
Iteration   2: n = 31812, mean = 4241 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3864, 3944, 3964, 4028, 5794, 14552, 11649024 ns/op
Iteration   3: n = 32450, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3868, 3944, 3964, 4036, 5752, 13629, 15456 ns/op
Iteration   4: n = 32426, mean = 3923 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3868, 3944, 3968, 4032, 7664, 15874, 1417216 ns/op
Iteration   5: n = 32449, mean = 3921 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3868, 3944, 3968, 4036, 6856, 15434, 1396736 ns/op

# Run progress: 10.00% complete, ETA 00:04:47
# Fork: 2 of 10
# Warmup Iteration   1: n = 2942, mean = 337710 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 45312, 69504, 232038, 375296, 9979822, 26448364, 48103424, 48103424 ns/op
# Warmup Iteration   2: n = 12424, mean = 53424 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4920, 12384, 32608, 35584, 43024, 15333786, 26249134, 26312704 ns/op
# Warmup Iteration   3: n = 14492, mean = 29684 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4504, 5248, 6152, 15563, 16480, 12009472, 27648573, 28016640 ns/op
# Warmup Iteration   4: n = 19046, mean = 11587 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4044, 5200, 5768, 6096, 9488, 10854, 14293793, 35979264 ns/op
# Warmup Iteration   5: n = 13962, mean = 12535 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3832, 3984, 5304, 5368, 5488, 12501, 25106956, 25821184 ns/op
# Warmup Iteration   6: n = 14225, mean = 9017 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3788, 3916, 3976, 3996, 4056, 7857, 24005096, 24018944 ns/op
# Warmup Iteration   7: n = 19526, mean = 5631 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3800, 3924, 3984, 4004, 4064, 8032, 12009472, 12009472 ns/op
# Warmup Iteration   8: n = 16058, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3800, 3928, 3988, 4008, 4090, 7694, 14107, 16288 ns/op
# Warmup Iteration   9: n = 16200, mean = 3934 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3924, 3984, 4004, 4052, 5443, 13550, 14800 ns/op
# Warmup Iteration  10: n = 16204, mean = 3941 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3928, 3988, 4008, 4064, 7568, 12466, 12704 ns/op
# Warmup Iteration  11: n = 15982, mean = 3934 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3788, 3920, 3980, 4004, 4069, 7587, 20846, 25632 ns/op
# Warmup Iteration  12: n = 16299, mean = 3926 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3796, 3916, 3972, 3996, 4052, 7074, 16711, 18304 ns/op
# Warmup Iteration  13: n = 16301, mean = 3926 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3800, 3916, 3972, 3996, 4056, 7032, 14207, 14832 ns/op
# Warmup Iteration  14: n = 16298, mean = 3927 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3916, 3972, 3992, 4048, 7757, 15131, 15232 ns/op
# Warmup Iteration  15: n = 16270, mean = 3927 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3796, 3916, 3972, 3996, 4052, 7644, 13378, 14000 ns/op
# Warmup Iteration  16: n = 16188, mean = 4253 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3796, 3916, 3972, 3996, 4048, 7598, 2024507, 5292032 ns/op
# Warmup Iteration  17: n = 16316, mean = 4098 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3792, 3908, 3964, 3988, 4044, 7555, 1467757, 1529856 ns/op
# Warmup Iteration  18: n = 16314, mean = 3919 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3788, 3908, 3964, 3988, 4044, 7630, 14619, 16640 ns/op
# Warmup Iteration  19: n = 16287, mean = 4010 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3908, 3964, 3988, 4044, 7687, 567513, 1458176 ns/op
# Warmup Iteration  20: n = 16291, mean = 3916 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3908, 3964, 3988, 4040, 6683, 14519, 14992 ns/op
Iteration   1: n = 32533, mean = 3918 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3908, 3964, 3988, 4044, 7483, 12878, 19968 ns/op
Iteration   2: n = 31757, mean = 4007 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3780, 3908, 3964, 3992, 4052, 7644, 15924, 1413120 ns/op
Iteration   3: n = 32468, mean = 4004 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3792, 3912, 3968, 3992, 4052, 7484, 16864, 1417216 ns/op
Iteration   4: n = 32421, mean = 4011 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3908, 3964, 3988, 4048, 7964, 17591, 1486848 ns/op
Iteration   5: n = 32431, mean = 3964 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3908, 3964, 3992, 4048, 7593, 14742, 1482752 ns/op

# Run progress: 20.00% complete, ETA 00:04:14
# Fork: 3 of 10
# Warmup Iteration   1: n = 2688, mean = 373084 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 46976, 76224, 237056, 328474, 11050025, 28495905, 33161216, 33161216 ns/op
# Warmup Iteration   2: n = 16022, mean = 43878 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4544, 6696, 27648, 32416, 38833, 12074631, 37650494, 44498944 ns/op
# Warmup Iteration   3: n = 16784, mean = 16986 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4008, 5320, 6112, 6320, 15776, 101397, 44243812, 66387968 ns/op
# Warmup Iteration   4: n = 10437, mean = 17293 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4048, 5280, 5472, 5528, 5765, 955140, 26619563, 26738688 ns/op
# Warmup Iteration   5: n = 14061, mean = 5910 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3940, 4012, 4036, 5504, 8264, 13663371, 14794752 ns/op
# Warmup Iteration   6: n = 13692, mean = 3951 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3892, 3972, 4008, 4872, 7799, 180519, 180992 ns/op
# Warmup Iteration   7: n = 15393, mean = 3903 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3880, 3948, 3968, 4020, 5154, 92800, 183808 ns/op
# Warmup Iteration   8: n = 16135, mean = 3895 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3880, 3952, 3968, 4028, 7788, 13216, 14384 ns/op
# Warmup Iteration   9: n = 16128, mean = 3899 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3952, 3972, 4032, 7961, 25059, 40896 ns/op
# Warmup Iteration  10: n = 16126, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3884, 3956, 3976, 4036, 7270, 13781, 14928 ns/op
# Warmup Iteration  11: n = 16116, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3736, 3880, 3956, 3976, 4044, 7776, 12101, 12992 ns/op
# Warmup Iteration  12: n = 16134, mean = 3895 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3952, 3972, 4036, 6830, 13902, 14128 ns/op
# Warmup Iteration  13: n = 16112, mean = 3894 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3880, 3952, 3972, 4028, 5396, 12874, 13872 ns/op
# Warmup Iteration  14: n = 16132, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3952, 3972, 4028, 6998, 14464, 17280 ns/op
# Warmup Iteration  15: n = 16105, mean = 3988 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3884, 3952, 3972, 4032, 7147, 584542, 1478656 ns/op
# Warmup Iteration  16: n = 15948, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3952, 3972, 4032, 7274, 15167, 15424 ns/op
# Warmup Iteration  17: n = 16104, mean = 3900 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3884, 3952, 3972, 4020, 7870, 16398, 17824 ns/op
# Warmup Iteration  18: n = 16080, mean = 3895 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3880, 3952, 3972, 4025, 7317, 13308, 15312 ns/op
# Warmup Iteration  19: n = 16080, mean = 3898 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3880, 3952, 3972, 4028, 7637, 15165, 17792 ns/op
# Warmup Iteration  20: n = 16078, mean = 3992 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3884, 3952, 3972, 4028, 7836, 601061, 1507328 ns/op
Iteration   1: n = 32114, mean = 3990 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3884, 3952, 3972, 4028, 7655, 15139, 1568768 ns/op
Iteration   2: n = 31446, mean = 3941 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3952, 3972, 4028, 7621, 14818, 1370112 ns/op
Iteration   3: n = 31987, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3884, 3952, 3972, 4032, 5732, 14542, 15552 ns/op
Iteration   4: n = 32008, mean = 3941 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3884, 3952, 3972, 4036, 7376, 16876, 1351680 ns/op
Iteration   5: n = 31974, mean = 3942 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3884, 3952, 3972, 4036, 7545, 13425, 1409024 ns/op

# Run progress: 30.00% complete, ETA 00:03:42
# Fork: 4 of 10
# Warmup Iteration   1: n = 2719, mean = 365538 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 47616, 72320, 263680, 398336, 10702029, 24807997, 30572544, 30572544 ns/op
# Warmup Iteration   2: n = 10018, mean = 71439 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4536, 11072, 31424, 35264, 50557, 21821391, 36036893, 36044800 ns/op
# Warmup Iteration   3: n = 19859, mean = 19665 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4032, 4384, 5664, 8032, 9376, 5533204, 24186388, 35979264 ns/op
# Warmup Iteration   4: n = 15310, mean = 9489 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3936, 6280, 7104, 15184, 29215, 13447111, 15056896 ns/op
# Warmup Iteration   5: n = 11209, mean = 9391 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3876, 4096, 5192, 5448, 9496, 34532065, 35979264 ns/op
# Warmup Iteration   6: n = 11710, mean = 4790 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3928, 5135, 5320, 5448, 7439, 6671797, 8011776 ns/op
# Warmup Iteration   7: n = 16155, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3860, 3932, 3960, 4016, 5542, 25275, 38848 ns/op
# Warmup Iteration   8: n = 16231, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3860, 3932, 3960, 4036, 6704, 13481, 15744 ns/op
# Warmup Iteration   9: n = 16200, mean = 3874 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3860, 3928, 3956, 4020, 6946, 15723, 15872 ns/op
# Warmup Iteration  10: n = 16207, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3860, 3932, 3960, 4028, 6099, 13593, 15232 ns/op
# Warmup Iteration  11: n = 16213, mean = 3872 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3856, 3928, 3956, 4028, 5443, 13428, 15168 ns/op
# Warmup Iteration  12: n = 16190, mean = 3875 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3860, 3932, 3960, 4032, 7403, 13914, 16064 ns/op
# Warmup Iteration  13: n = 16204, mean = 3879 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3860, 3932, 3960, 4036, 7709, 16307, 16704 ns/op
# Warmup Iteration  14: n = 16008, mean = 3874 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3860, 3932, 3956, 4032, 5270, 15830, 16128 ns/op
# Warmup Iteration  15: n = 16191, mean = 3874 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3860, 3932, 3960, 4032, 6947, 16647, 17152 ns/op
# Warmup Iteration  16: n = 16181, mean = 3878 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3860, 3936, 3960, 4040, 7693, 13384, 14512 ns/op
# Warmup Iteration  17: n = 16209, mean = 3956 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3852, 3924, 3948, 4020, 6902, 554484, 1435648 ns/op
# Warmup Iteration  18: n = 16187, mean = 3869 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3852, 3924, 3956, 4032, 7392, 14660, 17056 ns/op
# Warmup Iteration  19: n = 16164, mean = 3958 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3852, 3924, 3952, 4020, 7395, 559799, 1427456 ns/op
# Warmup Iteration  20: n = 16166, mean = 3954 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3852, 3924, 3952, 4028, 7281, 538003, 1378304 ns/op
Iteration   1: n = 32289, mean = 3919 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3852, 3924, 3952, 4028, 7914, 17408, 1544192 ns/op
Iteration   2: n = 31532, mean = 4095 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3852, 3928, 3956, 4036, 7371, 14261, 7077888 ns/op
Iteration   3: n = 32219, mean = 3915 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3852, 3924, 3952, 4028, 7540, 15316, 1417216 ns/op
Iteration   4: n = 32315, mean = 3869 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3852, 3924, 3952, 4024, 7194, 15834, 18112 ns/op
Iteration   5: n = 32267, mean = 3869 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3852, 3924, 3956, 4036, 6919, 15789, 17248 ns/op

# Run progress: 40.00% complete, ETA 00:03:10
# Fork: 5 of 10
# Warmup Iteration   1: n = 2485, mean = 396147 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 49984, 81280, 258867, 355738, 12119245, 30426726, 45219840, 45219840 ns/op
# Warmup Iteration   2: n = 10846, mean = 68582 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 6664, 9952, 32480, 38464, 58786, 17765433, 44460088, 44498944 ns/op
# Warmup Iteration   3: n = 11846, mean = 21993 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4192, 6064, 7386, 10608, 11944, 5405958, 24072376, 24084480 ns/op
# Warmup Iteration   4: n = 15876, mean = 7997 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3796, 4040, 5528, 6712, 16839, 19184, 12016227, 12025856 ns/op
# Warmup Iteration   5: n = 12909, mean = 5548 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3948, 4008, 4032, 4096, 9366, 10869981, 12009472 ns/op
# Warmup Iteration   6: n = 14850, mean = 4250 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3736, 3888, 3952, 3976, 4040, 7417, 2519137, 4726784 ns/op
# Warmup Iteration   7: n = 15790, mean = 3966 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3888, 3956, 3988, 5456, 9536, 177327, 177920 ns/op
# Warmup Iteration   8: n = 16059, mean = 4015 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3888, 3956, 3980, 5464, 7460, 612130, 1529856 ns/op
# Warmup Iteration   9: n = 15449, mean = 3923 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3888, 3956, 3988, 5488, 7666, 16010, 17344 ns/op
# Warmup Iteration  10: n = 16058, mean = 3920 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3888, 3956, 3984, 5456, 7135, 13357, 14656 ns/op
# Warmup Iteration  11: n = 15550, mean = 3997 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3776, 3960, 4036, 4064, 5476, 7531, 35948, 59200 ns/op
# Warmup Iteration  12: n = 15019, mean = 4091 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3824, 3960, 4032, 4060, 5472, 7605, 726598, 1443840 ns/op
# Warmup Iteration  13: n = 15867, mean = 3948 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3812, 3936, 3992, 4016, 4092, 7575, 14319, 15248 ns/op
# Warmup Iteration  14: n = 15641, mean = 3948 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3940, 3996, 4020, 4088, 5517, 15443, 15488 ns/op
# Warmup Iteration  15: n = 15991, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3936, 3992, 4012, 4076, 7312, 12902, 12912 ns/op
# Warmup Iteration  16: n = 15982, mean = 3946 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3936, 3992, 4016, 4084, 7180, 12158, 12464 ns/op
# Warmup Iteration  17: n = 15979, mean = 3942 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3928, 3984, 4008, 4080, 7546, 13670, 15392 ns/op
# Warmup Iteration  18: n = 15981, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3932, 3984, 4008, 4076, 7498, 14902, 14912 ns/op
# Warmup Iteration  19: n = 15980, mean = 4035 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3932, 3984, 4004, 4084, 7203, 610388, 1497088 ns/op
# Warmup Iteration  20: n = 15979, mean = 4030 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3932, 3988, 4008, 4080, 7328, 581720, 1421312 ns/op
Iteration   1: n = 31889, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3812, 3932, 3988, 4008, 4080, 7488, 14841, 15920 ns/op
Iteration   2: n = 31199, mean = 4030 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3932, 3988, 4008, 4084, 6765, 13100, 1409024 ns/op
Iteration   3: n = 31801, mean = 3987 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3932, 3988, 4008, 4092, 7581, 15037, 1378304 ns/op
Iteration   4: n = 31799, mean = 3987 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3800, 3932, 3988, 4012, 4096, 7440, 14047, 1421312 ns/op
Iteration   5: n = 31862, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3932, 3988, 4008, 4088, 7400, 15834, 20704 ns/op

# Run progress: 50.00% complete, ETA 00:02:39
# Fork: 6 of 10
# Warmup Iteration   1: n = 3550, mean = 276292 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 43712, 62656, 217600, 276992, 8267612, 23038624, 36241408, 36241408 ns/op
# Warmup Iteration   2: n = 12661, mean = 54453 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 5376, 11536, 32666, 37760, 45961, 15636922, 40782784, 44367872 ns/op
# Warmup Iteration   3: n = 17371, mean = 15494 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4576, 5392, 6224, 6352, 6642, 214693, 22038105, 24018944 ns/op
# Warmup Iteration   4: n = 14534, mean = 18865 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 5136, 5592, 9200, 11072, 17280, 543159, 28831465, 35979264 ns/op
# Warmup Iteration   5: n = 18738, mean = 10957 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4136, 4360, 5792, 8448, 8704, 11753, 20161456, 40435712 ns/op
# Warmup Iteration   6: n = 17241, mean = 9649 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3952, 4064, 4136, 4160, 4248, 8268, 25097778, 28016640 ns/op
# Warmup Iteration   7: n = 14323, mean = 4275 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3972, 4096, 4168, 4200, 4280, 11623, 990392, 1597440 ns/op
# Warmup Iteration   8: n = 15318, mean = 4209 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3988, 4104, 4176, 4208, 4272, 7694, 682979, 1441792 ns/op
# Warmup Iteration   9: n = 15313, mean = 4112 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3976, 4096, 4176, 4200, 4272, 7627, 14457, 15392 ns/op
# Warmup Iteration  10: n = 15299, mean = 4112 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3968, 4096, 4176, 4200, 4272, 5434, 15740, 15808 ns/op
# Warmup Iteration  11: n = 15317, mean = 4115 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3976, 4104, 4176, 4200, 4272, 8141, 13414, 13856 ns/op
# Warmup Iteration  12: n = 15088, mean = 4115 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3936, 4096, 4176, 4200, 4280, 8024, 15635, 15920 ns/op
# Warmup Iteration  13: n = 15545, mean = 4096 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3924, 4084, 4160, 4184, 4240, 7037, 15450, 15920 ns/op
# Warmup Iteration  14: n = 15531, mean = 4094 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3936, 4080, 4160, 4184, 4240, 7688, 13266, 14080 ns/op
# Warmup Iteration  15: n = 15482, mean = 4098 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3932, 4080, 4160, 4192, 4264, 7940, 15448, 15808 ns/op
# Warmup Iteration  16: n = 15303, mean = 4096 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3936, 4080, 4160, 4184, 4248, 7479, 16771, 16992 ns/op
# Warmup Iteration  17: n = 15491, mean = 4095 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3932, 4080, 4160, 4184, 4240, 7720, 15632, 15632 ns/op
# Warmup Iteration  18: n = 15502, mean = 4191 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3932, 4084, 4160, 4184, 4248, 7648, 665432, 1460224 ns/op
# Warmup Iteration  19: n = 15529, mean = 4091 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3944, 4076, 4152, 4176, 4240, 6411, 13509, 13536 ns/op
# Warmup Iteration  20: n = 15486, mean = 4186 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3924, 4080, 4152, 4176, 4240, 8096, 646925, 1384448 ns/op
Iteration   1: n = 30918, mean = 4098 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3928, 4080, 4160, 4184, 4256, 8013, 16474, 17696 ns/op
Iteration   2: n = 30243, mean = 4427 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3936, 4080, 4152, 4184, 4248, 8002, 18422, 8699904 ns/op
Iteration   3: n = 30843, mean = 4098 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3636, 4084, 4160, 4192, 4264, 7855, 16098, 18176 ns/op
Iteration   4: n = 30949, mean = 4094 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3928, 4080, 4152, 4176, 4240, 7754, 15465, 17312 ns/op
Iteration   5: n = 30908, mean = 4144 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3924, 4080, 4160, 4184, 4256, 8513, 15997, 1382400 ns/op

# Run progress: 60.00% complete, ETA 00:02:07
# Fork: 7 of 10
# Warmup Iteration   1: n = 2887, mean = 346561 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 47296, 80768, 228403, 385024, 9747825, 27701543, 38993920, 38993920 ns/op
# Warmup Iteration   2: n = 13638, mean = 47618 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4696, 8336, 33280, 34880, 41447, 12747981, 28968491, 30900224 ns/op
# Warmup Iteration   3: n = 16402, mean = 16092 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4112, 5280, 6368, 8704, 9216, 181913, 24287445, 24707072 ns/op
# Warmup Iteration   4: n = 10657, mean = 16390 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4160, 5544, 5664, 5704, 5872, 4600308, 23229799, 24018944 ns/op
# Warmup Iteration   5: n = 8650, mean = 11750 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4976, 5496, 7856, 7984, 16928, 21995, 12042240, 12042240 ns/op
# Warmup Iteration   6: n = 19262, mean = 4489 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3892, 3964, 3995, 4096, 7438, 967730, 10846208 ns/op
# Warmup Iteration   7: n = 15375, mean = 4849 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3884, 3952, 3976, 4060, 9018, 6570377, 12025856 ns/op
# Warmup Iteration   8: n = 16012, mean = 3949 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3892, 3956, 3984, 4060, 10947, 181757, 183296 ns/op
# Warmup Iteration   9: n = 15441, mean = 3908 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3896, 3964, 3992, 4064, 8192, 14555, 15104 ns/op
# Warmup Iteration  10: n = 16129, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3888, 3956, 3984, 4048, 5275, 12497, 13056 ns/op
# Warmup Iteration  11: n = 16113, mean = 3902 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3892, 3964, 3992, 4048, 7387, 13381, 15024 ns/op
# Warmup Iteration  12: n = 16114, mean = 3903 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3896, 3960, 3988, 4048, 6889, 13241, 14464 ns/op
# Warmup Iteration  13: n = 16131, mean = 3898 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3888, 3956, 3984, 4048, 5352, 12357, 13328 ns/op
# Warmup Iteration  14: n = 16089, mean = 3988 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3892, 3960, 3988, 4052, 7231, 544987, 1366016 ns/op
# Warmup Iteration  15: n = 15891, mean = 3998 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3960, 3988, 4056, 7681, 625169, 1499136 ns/op
# Warmup Iteration  16: n = 16086, mean = 3905 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3964, 3988, 4064, 7489, 14269, 15632 ns/op
# Warmup Iteration  17: n = 15768, mean = 3904 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3964, 3988, 4057, 7153, 15260, 15408 ns/op
# Warmup Iteration  18: n = 16065, mean = 3991 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3960, 3988, 4048, 5321, 576722, 1439744 ns/op
# Warmup Iteration  19: n = 16066, mean = 4034 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3892, 3960, 3988, 4045, 7026, 854867, 2150400 ns/op
# Warmup Iteration  20: n = 16079, mean = 3986 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3892, 3960, 3984, 4040, 7619, 556441, 1396736 ns/op
Iteration   1: n = 32112, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3956, 3984, 4052, 7559, 16509, 1372160 ns/op
Iteration   2: n = 31401, mean = 3900 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3960, 3984, 4056, 7058, 14527, 16112 ns/op
Iteration   3: n = 31993, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3960, 3984, 4048, 7568, 16832, 1392640 ns/op
Iteration   4: n = 32015, mean = 3990 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3888, 3960, 3984, 4052, 7519, 15494, 1478656 ns/op
Iteration   5: n = 31987, mean = 3901 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3960, 3988, 4064, 7257, 12557, 14720 ns/op

# Run progress: 70.00% complete, ETA 00:01:35
# Fork: 8 of 10
# Warmup Iteration   1: n = 3096, mean = 316835 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 37888, 70784, 226125, 280653, 8605041, 33216135, 48103424, 48103424 ns/op
# Warmup Iteration   2: n = 14612, mean = 45779 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4136, 10192, 30496, 36288, 40056, 12709724, 34081056, 38600704 ns/op
# Warmup Iteration   3: n = 25166, mean = 9633 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3828, 4368, 7024, 7256, 7992, 18938, 12097121, 15204352 ns/op
# Warmup Iteration   4: n = 16422, mean = 11838 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3876, 4040, 5472, 5592, 5840, 14797, 21020960, 24051712 ns/op
# Warmup Iteration   5: n = 12746, mean = 5273 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3712, 3832, 3896, 3948, 7643, 22018, 10757359, 14761984 ns/op
# Warmup Iteration   6: n = 15353, mean = 3896 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3856, 3912, 3932, 4000, 6865, 181486, 181760 ns/op
# Warmup Iteration   7: n = 16277, mean = 3860 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3856, 3912, 3932, 3992, 5583, 15205, 16672 ns/op
# Warmup Iteration   8: n = 16259, mean = 3861 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3856, 3912, 3928, 3988, 7744, 14773, 16576 ns/op
# Warmup Iteration   9: n = 16245, mean = 3862 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3732, 3852, 3912, 3928, 3996, 7542, 14836, 17504 ns/op
# Warmup Iteration  10: n = 16252, mean = 3860 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3852, 3908, 3928, 3984, 7612, 12390, 12480 ns/op
# Warmup Iteration  11: n = 15955, mean = 3865 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3856, 3912, 3928, 3988, 7450, 16616, 17312 ns/op
# Warmup Iteration  12: n = 16255, mean = 3865 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3856, 3912, 3932, 3996, 7680, 16511, 17152 ns/op
# Warmup Iteration  13: n = 16230, mean = 3950 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3856, 3908, 3928, 3996, 7610, 549267, 1433600 ns/op
# Warmup Iteration  14: n = 16078, mean = 3860 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3736, 3852, 3908, 3924, 3984, 6993, 13562, 15488 ns/op
# Warmup Iteration  15: n = 16228, mean = 3860 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3856, 3908, 3928, 3984, 7330, 14738, 17120 ns/op
# Warmup Iteration  16: n = 16229, mean = 3864 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3856, 3912, 3932, 4000, 7500, 16392, 16960 ns/op
# Warmup Iteration  17: n = 16325, mean = 3921 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3828, 3876, 3892, 3952, 7563, 538918, 1443840 ns/op
# Warmup Iteration  18: n = 16329, mean = 3832 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3828, 3876, 3892, 3948, 7382, 12762, 12944 ns/op
# Warmup Iteration  19: n = 16326, mean = 3836 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3828, 3876, 3896, 3956, 7868, 14477, 16896 ns/op
# Warmup Iteration  20: n = 16303, mean = 3923 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3728, 3832, 3876, 3892, 3952, 7384, 550854, 1460224 ns/op
Iteration   1: n = 32575, mean = 3876 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3716, 3828, 3876, 3892, 3952, 7480, 17314, 1404928 ns/op
Iteration   2: n = 31812, mean = 3835 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3828, 3876, 3896, 3960, 7331, 13536, 18336 ns/op
Iteration   3: n = 32493, mean = 4092 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3712, 3828, 3876, 3896, 3956, 7501, 1389065, 1462272 ns/op
Iteration   4: n = 32497, mean = 3878 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3724, 3828, 3876, 3892, 3952, 7552, 17960, 1400832 ns/op
Iteration   5: n = 32494, mean = 3960 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3716, 3828, 3876, 3892, 3952, 7836, 981495, 1406976 ns/op

# Run progress: 80.00% complete, ETA 00:01:03
# Fork: 9 of 10
# Warmup Iteration   1: n = 2876, mean = 347931 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 47744, 74368, 230477, 313651, 9677865, 26134151, 37748736, 37748736 ns/op
# Warmup Iteration   2: n = 13645, mean = 52152 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4688, 8624, 33024, 35392, 44805, 12378767, 35410556, 36438016 ns/op
# Warmup Iteration   3: n = 16949, mean = 15882 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4128, 5304, 6496, 6600, 7724, 176909, 43147919, 54853632 ns/op
# Warmup Iteration   4: n = 10786, mean = 12542 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4112, 5240, 5608, 6320, 6928, 17339, 23704325, 24018944 ns/op
# Warmup Iteration   5: n = 10898, mean = 12537 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4120, 4320, 4512, 5960, 6232, 11975, 23641876, 24018944 ns/op
# Warmup Iteration   6: n = 17032, mean = 5815 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3792, 3896, 3948, 3972, 4040, 8065, 10903277, 12009472 ns/op
# Warmup Iteration   7: n = 14132, mean = 3911 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3784, 3900, 3952, 3976, 4056, 7561, 19277, 21472 ns/op
# Warmup Iteration   8: n = 12973, mean = 4582 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3792, 3908, 3992, 6192, 15072, 15504, 3979398, 5652480 ns/op
# Warmup Iteration   9: n = 16063, mean = 3913 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3788, 3908, 3964, 3988, 4052, 6285, 12430, 12944 ns/op
# Warmup Iteration  10: n = 16105, mean = 3915 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3796, 3908, 3964, 3988, 4048, 7156, 24586, 39680 ns/op
# Warmup Iteration  11: n = 15827, mean = 3919 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3792, 3912, 3972, 3996, 4064, 7569, 14600, 16512 ns/op
# Warmup Iteration  12: n = 16014, mean = 3944 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3816, 3936, 3992, 4016, 4072, 7630, 13338, 14416 ns/op
# Warmup Iteration  13: n = 16012, mean = 3942 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3936, 3992, 4016, 4072, 7504, 11602, 16384 ns/op
# Warmup Iteration  14: n = 15989, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3812, 3932, 3992, 4016, 4076, 7672, 16506, 16736 ns/op
# Warmup Iteration  15: n = 15859, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3824, 3936, 3992, 4016, 4074, 7696, 17423, 18304 ns/op
# Warmup Iteration  16: n = 15987, mean = 3946 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3816, 3936, 3992, 4016, 4076, 7889, 17308, 18400 ns/op
# Warmup Iteration  17: n = 15991, mean = 3944 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3816, 3936, 3996, 4016, 4072, 7856, 13280, 15648 ns/op
# Warmup Iteration  18: n = 15990, mean = 3944 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3804, 3932, 3992, 4016, 4072, 7801, 14488, 15264 ns/op
# Warmup Iteration  19: n = 15967, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3820, 3932, 3992, 4016, 4076, 8049, 15945, 17568 ns/op
# Warmup Iteration  20: n = 15967, mean = 3941 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3816, 3932, 3992, 4016, 4068, 5267, 14820, 14896 ns/op
Iteration   1: n = 31894, mean = 3987 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3816, 3932, 3992, 4016, 4072, 7474, 15178, 1392640 ns/op
Iteration   2: n = 31191, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3640, 3932, 3992, 4016, 4072, 7402, 13744, 14800 ns/op
Iteration   3: n = 31791, mean = 3986 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3808, 3932, 3992, 4016, 4080, 7320, 15108, 1374208 ns/op
Iteration   4: n = 31778, mean = 3943 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3812, 3932, 3992, 4016, 4076, 7396, 14343, 15632 ns/op
Iteration   5: n = 31750, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3820, 3932, 3992, 4016, 4076, 7442, 15300, 16000 ns/op

# Run progress: 90.00% complete, ETA 00:00:31
# Fork: 10 of 10
# Warmup Iteration   1: n = 3456, mean = 289186 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 34688, 58176, 217933, 368640, 8110817, 25860637, 36241408, 36241408 ns/op
# Warmup Iteration   2: n = 12800, mean = 48824 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 6920, 12544, 27456, 33920, 40318, 12463981, 37253107, 37748736 ns/op
# Warmup Iteration   3: n = 12662, mean = 29558 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4044, 5208, 7200, 18144, 18880, 11346854, 26724634, 27623424 ns/op
# Warmup Iteration   4: n = 10240, mean = 12479 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 4768, 5120, 5376, 5912, 8224, 22332, 24401060, 24707072 ns/op
# Warmup Iteration   5: n = 11589, mean = 12396 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3988, 4160, 5136, 5360, 6584, 11492, 21640954, 23461888 ns/op
# Warmup Iteration   6: n = 16353, mean = 5541 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3880, 3944, 3964, 4040, 7826, 12009472, 12009472 ns/op
# Warmup Iteration   7: n = 15775, mean = 3938 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3876, 3936, 3956, 4028, 9170, 179928, 180224 ns/op
# Warmup Iteration   8: n = 16030, mean = 3932 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3876, 3932, 3956, 4020, 7624, 181801, 183808 ns/op
# Warmup Iteration   9: n = 15824, mean = 3900 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3956, 3984, 4120, 5770, 15571, 15664 ns/op
# Warmup Iteration  10: n = 16098, mean = 3906 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3892, 3956, 3980, 4036, 7941, 27655, 43776 ns/op
# Warmup Iteration  11: n = 16093, mean = 3904 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3768, 3892, 3960, 3988, 4060, 7252, 12078, 12176 ns/op
# Warmup Iteration  12: n = 16105, mean = 3899 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3956, 3976, 4032, 5452, 15287, 16352 ns/op
# Warmup Iteration  13: n = 16081, mean = 3901 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3744, 3892, 3956, 3976, 4040, 7543, 14762, 15920 ns/op
# Warmup Iteration  14: n = 15947, mean = 3905 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3892, 3956, 3980, 4064, 7944, 17135, 18496 ns/op
# Warmup Iteration  15: n = 16088, mean = 3897 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3888, 3956, 3976, 4036, 7343, 13150, 14592 ns/op
# Warmup Iteration  16: n = 16060, mean = 3904 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3896, 3956, 3980, 4036, 7652, 15041, 15264 ns/op
# Warmup Iteration  17: n = 16051, mean = 3900 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3956, 3976, 4032, 7080, 16044, 19840 ns/op
# Warmup Iteration  18: n = 16050, mean = 3988 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3756, 3888, 3956, 3980, 4036, 7995, 554042, 1378304 ns/op
# Warmup Iteration  19: n = 15982, mean = 3903 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3960, 3980, 4044, 7505, 14336, 15408 ns/op
# Warmup Iteration  20: n = 16025, mean = 3998 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3892, 3956, 3980, 4036, 7697, 619902, 1540096 ns/op
Iteration   1: n = 31930, mean = 3948 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3960, 3984, 4048, 7417, 16882, 1419264 ns/op
Iteration   2: n = 31241, mean = 3907 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3752, 3896, 3960, 3984, 4048, 7594, 15992, 18336 ns/op
Iteration   3: n = 31899, mean = 3951 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3764, 3892, 3960, 3984, 4056, 7906, 15161, 1378304 ns/op
Iteration   4: n = 31930, mean = 3945 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3760, 3892, 3960, 3980, 4048, 5681, 14382, 1372160 ns/op
Iteration   5: n = 31923, mean = 3946 ns/op, p{0.00, 0.50, 0.90, 0.95, 0.99, 0.999, 0.9999, 1.00} = 3748, 3892, 3960, 3984, 4052, 5611, 14200, 1404928 ns/op


Result "bsonWithCBytes":
  3972.744 ±(99.9%) 38.390 ns/op [Average]
  (min, avg, max) = (3636.000, 3972.744, 11649024.000), stdev = 14732.403
  CI (99.9%): [3934.355, 4011.134] (assumes normal distribution)
  Samples, N = 1594601
        mean =   3972.744 ±(99.9%) 38.390 ns/op
         min =   3636.000 ns/op
  p( 0.0000) =   3636.000 ns/op
  p(50.0000) =   3900.000 ns/op
  p(90.0000) =   4028.000 ns/op
  p(95.0000) =   4088.000 ns/op
  p(99.0000) =   4176.000 ns/op
  p(99.9000) =   7472.000 ns/op
  p(99.9900) =  15057.274 ns/op
  p(99.9990) = 1413341.102 ns/op
  p(99.9999) = 9895471.349 ns/op
         max = 11649024.000 ns/op


# Run complete. Total time: 00:05:18

Benchmark                        Mode      Cnt     Score    Error  Units
ComparisonMain.bsonWithCBytes  sample  1594601  3972.744 ± 38.390  ns/op