It requires significant energy to manufacture and deploy computational devices. Traditional discussions of the energy-efficiency of compute measure operational energy, i.e.\ how many FLOPS in a 50\,MW datacenter. However, if we consider the true lifetime energy use of modern devices, the majority actually comes not from runtime use but from manufacture and deployment. In this paper, then, we suggest that perhaps the most climate-impactful action we can take is to extend the service lifetime of existing compute. We design two new metrics to measure how to balance continued service of older devices with the superlinear runtime improvements of newer machines. The first looks at carbon per raw compute, amortized across the operation and manufacture of devices. The second considers use of components beyond compute, such as batteries or radios in smartphone platforms. We use these metrics to redefine device service lifetime in terms of carbon efficiency. We then realize a real-world ``junkyard datacenter'' made up of Nexus 4 and Nexus 5 phones, which are nearly a decade past their official end-of-life dates. This new-old datacenter is able to nearly match and occasionally exceed modern cloud compute offerings.
翻译:它需要巨大的能量来制造和部署计算装置。关于计算操作能量的能源效率的传统讨论,即:在50年中有多少FLOPS,MW数据中心。然而,如果我们考虑到现代装置的真正寿命寿命能源使用量,大多数实际上不是来自运行时间的使用量,而是来自制造和部署。在本文中,我们建议,我们可能能够采取的最气候影响最大的行动是延长现有计算器的服务寿命期。我们设计了两个新的衡量标准,以衡量如何平衡老设备的持续服务与新机器超线运行时间改进之间的平衡。第一个衡量标准是每个原始计算、在设备操作和制造过程中摊销的碳。第二个衡量标准考虑的是超出计算范围的部件的使用量,如智能手机或无线电平台中的电池或无线电。我们用这些衡量标准来重新定义设备服务寿命的碳效率。然后我们发现一个真实世界的“枢纽站”数据中心由Nexus 4和 Nexus 5 手机组成,它们几乎已经超过其正式寿命的十年了。这个新的数据中心能够不定期更新并更新。