The rapid increase in computing demand and its corresponding energy consumption have focused attention on computing's impact on the climate and sustainability. Prior work proposes metrics that quantify computing's carbon footprint across several lifecycle phases, including its supply chain, operation, and end-of-life. Industry uses these metrics to optimize the carbon footprint of manufacturing hardware and running computing applications. Unfortunately, prior work on optimizing datacenters' carbon footprint often succumbs to the \emph{sunk cost fallacy} by considering embodied carbon emissions (a sunk cost) when making operational decisions (i.e., job scheduling and placement), which leads to operational decisions that do not always reduce the total carbon footprint. In this paper, we evaluate carbon-aware job scheduling and placement on a given set of servers for a number of carbon accounting metrics. Our analysis reveals state-of-the-art carbon accounting metrics that include embodied carbon emissions when making operational decisions can actually increase the total carbon footprint of executing a set of jobs. We study the factors that affect the added carbon cost of such suboptimal decision-making. We then use a real-world case study from a datacenter to demonstrate how the sunk carbon fallacy manifests itself in practice. Finally, we discuss the implications of our findings in better guiding effective carbon-aware scheduling in on-premise and cloud datacenters.

翻译：计算需求的快速增长及其相应的能源消耗，使人们日益关注计算对气候和可持续发展的影响。先前的研究提出了量化计算在多个生命周期阶段（包括供应链、运营和报废阶段）碳足迹的指标。业界利用这些指标来优化硬件制造和计算应用运行过程中的碳足迹。然而，先前关于优化数据中心碳足迹的研究在制定运营决策（即作业调度与放置）时，常因考虑隐含碳排放（一种沉没成本）而陷入**沉没成本谬误**，这导致运营决策并不总能降低总碳足迹。本文中，我们针对一系列碳核算指标，评估了在给定服务器集上的碳感知作业调度与放置策略。我们的分析表明，在制定运营决策时纳入隐含碳排放的先进碳核算指标，实际上可能增加执行一组作业的总碳足迹。我们研究了影响此类次优决策所增加碳成本的因素。随后，我们通过一个来自数据中心的真实案例研究，展示了沉没碳谬误在实践中的具体表现。最后，我们讨论了研究结果对更好地指导本地与云数据中心实施有效碳感知调度的启示。