This letter reveals that performing microarchitecture-dependent, or microarchitecture-independent, or ISA-independent workload characterization alone will lead to misleading or even erroneous conclusions. We present a whole-picture workload characterization (in short, WPC) methodology and the tool. WPC integrates microarchitecture-dependent, microarchitecture-independent, and ISA-independent characterization methodologies. It performs a whole-picture analysis on hierarchical profile data across Intermediate Representation (IR), ISA, and microarchitecture to sum up the inherent workload characteristics and understand the reasons behind the numbers. We contradict an influential observation using the WPC tool: having higher front-end stalls is an intrinsic characteristic of scale-out workloads. Our experiments show collecting microarchitecture metrics at only one level without understanding the reason behind the numbers might lead to erroneous conclusions. We open-source the WPC tool from the project homepage https://www.benchcouncil.org/WPC .

中文翻译：

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WPC：跨中间表示、ISA 和微体系结构的全图工作负载表征

这封信表明，单独执行依赖于微体系结构、独立于微体系结构或独立于 ISA 的工作负载表征将导致误导甚至错误的结论。我们提出了一个全面的工作负载表征（简称 WPC）方法和工具。WPC 集成了依赖于微体系结构、独立于微体系结构和独立于 ISA 的表征方法。它对跨中间表示 (IR)、ISA 和微体系结构的分层配置文件数据执行全面分析，以总结固有的工作负载特征并了解数字背后的原因。我们与使用 WPC 工具的一个有影响力的观察相矛盾：具有更高的前端停顿是横向扩展工作负载的内在特征。我们的实验表明，在不了解数字背后的原因的情况下仅在一个级别收集微架构指标可能会导致错误的结论。我们从项目主页开源了 WPC 工具https://www.benchcouncil.org/WPC .