We investigate the duet measurement procedure, which helps improve the accuracy of performance comparison experiments conducted on shared machines by executing the measured artifacts in parallel and evaluating their relative performance together, rather than individually. Specifically, we analyze the behavior of the procedure in multiple cloud environments and use experimental evidence to answer multiple research questions concerning the assumption underlying the procedure. We demonstrate improvements in accuracy ranging from 2.3x to 12.5x (5.03x on average) for the tested ScalaBench (and DaCapo) workloads, and from 23.8x to 82.4x (37.4x on average) for the SPEC CPU 2017 workloads.

中文翻译：

---

Duet 基准测试：提高云中的测量精度

我们研究了二重奏测量程序，它通过并行执行测量的工件并一起而不是单独评估它们的相对性能，有助于提高在共享机器上进行的性能比较实验的准确性。具体来说，我们分析了该程序在多个云环境中的行为，并使用实验证据来回答与该程序背后的假设有关的多个研究问题。对于经测试的 ScalaBench（和 DaCapo）工作负载，我们展示了准确度从 2.3 倍到 12.5 倍（平均 5.03 倍）的改进，对于 SPEC CPU 2017 工作负载从 23.8 倍到 82.4 倍（平均 37.4 倍）。