基准测试的可靠性挑战
问题概述
基准测试往往难以得到可比且可靠的结果，因为受 CPU 负载、GC、JIT 预热、固定启动成本等因素影响。用户需要通过置信区间、多次运行和对照组比较来降低噪声，但缺乏标准化工具来自动化这些流程。
痛点标签
- 基准测试往往难以得到可比且可靠的结果，因为受 CPU 负载、GC、JIT 预热、固定启动成本等因素影响
- 受 CPU 频率调节、系统中断等因素导致结果不可重复
- 缺乏内置 warm‑up、fork、dead‑code 消除等功能的标准化基准工具
待验证问题
- 您是否需要更可靠的基准测试方法来获得可比的结果？
- 您是否愿意使用能自动处理 warm‑up、置信区间和多运行的工具？
- 您目前是否面临基准结果不可重复或噪声过大的问题？
证据
原话
I would rather say: "benchmark with confidence intervals" or maybe "benchmark with comparisons".It's very hard to say much about an absolute number. You need to compare against some alternative or control, and because of CPU load, throttling, GC, and a thousand other variables, you really should be comparing against that control _in the same run_, and importantly round robin across multiple runs to spread out the noise fairly across each implementation.Then once you have a bunch of measurements you have a distribution and shouldn't just take a mean to compare, but should calculate something like the 95% confidence interval. If you see that those confidence intervals overlap, the you might not really know which is faster. If they don't overlap, then you probably do know which is faster.
原话
Anything faster than, say, 10ms risks being skewed by fixed costs (e.g, interpreter startup).
原话
The longer you let a benchmark run, the more certain you can be that it captures other unrelated activity. His theory was you want to run a benchmark several times, for short periods of time, and take the fastest run as the benchmark.
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