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@andrebrait
Created December 28, 2018 22:03
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REMEMBER: The numbers below are just data. To gain reusable insights, you need to follow up on
why the numbers are the way they are. Use profilers (see -prof, -lprof), design factorial
experiments, perform baseline and negative tests that provide experimental control, make sure
the benchmarking environment is safe on JVM/OS/HW level, ask for reviews from the domain experts.
Do not assume the numbers tell you what you want them to tell.
Benchmark (listSize) Mode Cnt Score Error Units
MyBenchmark.atomicLong 1000000 avgt 5 0.026 ± 0.001 s/op
MyBenchmark.atomicLong 10000000 avgt 5 0.263 ± 0.003 s/op
MyBenchmark.atomicLong 100000000 avgt 5 2.504 ± 0.466 s/op
MyBenchmark.longAdder 1000000 avgt 5 0.005 ± 0.002 s/op
MyBenchmark.longAdder 10000000 avgt 5 0.053 ± 0.016 s/op
MyBenchmark.longAdder 100000000 avgt 5 0.469 ± 0.065 s/op
MyBenchmark.longStreamSum 1000000 avgt 5 0.004 ± 0.001 s/op
MyBenchmark.longStreamSum 10000000 avgt 5 0.012 ± 0.001 s/op
MyBenchmark.longStreamSum 100000000 avgt 5 0.199 ± 0.425 s/op
MyBenchmark.volatileLong 1000000 avgt 5 0.052 ± 0.019 s/op
MyBenchmark.volatileLong 10000000 avgt 5 0.528 ± 0.098 s/op
MyBenchmark.volatileLong 100000000 avgt 5 5.070 ± 0.302 s/op
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