The amount of CO$_2$ emitted per kilowatt-hour on an electricity grid varies by time of day and substantially varies by location due to the types of generation. Networked collections of warehouse scale computers, sometimes called Hyperscale Computing, emit more carbon than needed if operated without regard to these variations in carbon intensity. This paper introduces Google's system for Carbon-Intelligent Compute Management, which actively minimizes electricity-based carbon footprint and power infrastructure costs by delaying temporally flexible workloads. The core component of the system is a suite of analytical pipelines used to gather the next day's carbon intensity forecasts, train day-ahead demand prediction models, and use risk-aware optimization to generate the next day's carbon-aware Virtual Capacity Curves (VCCs) for all datacenter clusters across Google's fleet. VCCs impose hourly limits on resources available to temporally flexible workloads while preserving overall daily capacity, enabling all such workloads to complete within a day. Data from operation shows that VCCs effectively limit hourly capacity when the grid's energy supply mix is carbon intensive and delay the execution of temporally flexible workloads to "greener" times.

中文翻译：

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数据中心的碳感知计算

电网每千瓦时排放的 CO$_2$ 量因一天中的时间而异，并且由于发电类型的不同，在不同地点也有很大差异。仓库规模计算机的联网集合，有时称为超大规模计算，如果在不考虑这些碳强度变化的情况下运行，则会排放比需要更多的碳。本文介绍了 Google 的碳智能计算管理系统，该系统通过延迟时间灵活的工作负载来主动最小化基于电力的碳足迹和电力基础设施成本。该系统的核心组件是一套分析管道，用于收集次日的碳强度预测、训练日前需求预测模型，并使用风险感知优化来生成次日' 适用于 Google 机群中所有数据中心集群的碳感知虚拟容量曲线 (VCC)。VCC 对可用于临时灵活工作负载的资源施加每小时限制，同时保留总体日常容量，使所有此类工作负载能够在一天内完成。运营数据显示，当电网的能源供应组合是碳密集型时，VCC 有效地限制了每小时的容量，并将时间灵活的工作负载的执行延迟到“更环保”的时间。