Sustainable IC design and fabrication

Donald Kline, Nikolas Parshook, A. Johnson, J. Stine, W. Stanchina, E. Brunvand, A. Jones
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引用次数: 10

Abstract

Low-energy computing in the use phase is compelling because it helps to address thermal density issues of deeply scaled CMOS, maximizes battery-life of mobile computing platforms, while also addressing sustainability. Unfortunately, environmental impacts of fabricating CMOS integrated circuits (ICs) is increasing and rapidly catching the operational phase of computing systems, particularly for low-energy and mobile computing products. This is due to trends in fabrication techniques for increasingly small geometries, such as increasing photo-lithography and metrology costs. Without attention, IC fabrication will likely become the dominant energy consumer and source of carbon emissions over an IC's lifetime. We propose a scaled parameterized model for evaluating the environmental impacts of IC fabrication, which can scale from 130nm to 32nm technology and account for stepwise changes in process technologies. As an example of the type of analysis possible using this model we demonstrate the environmental impacts of changing the metal stack at these technology nodes. Our results indicate that based on the die area calculated from a commercial design flow and our parameterized model, changing the number of metal layers from eight to six layers results in an average savings in manufacturing energy of 9.5%, 13.8%, and 13% for 130nm, 90nm, and 65nm technologies, respectively, and, depending on scenario, it can take years for operational energy savings to makeup this difference.
可持续集成电路设计和制造
使用阶段的低能耗计算是引人注目的,因为它有助于解决深度缩放CMOS的热密度问题,最大限度地延长移动计算平台的电池寿命,同时也解决了可持续性问题。不幸的是,制造CMOS集成电路(ic)对环境的影响正在增加,并迅速赶上计算系统的操作阶段,特别是对于低能耗和移动计算产品。这是由于越来越小的几何形状的制造技术的趋势,如增加光刻和计量成本。如果不加以重视,集成电路制造可能会成为主要的能源消耗和碳排放的来源,在一个集成电路的生命周期。我们提出了一个规模参数化模型来评估集成电路制造对环境的影响,该模型可以从130纳米扩展到32纳米,并考虑到工艺技术的逐步变化。作为使用该模型可能进行的分析类型的一个示例,我们展示了在这些技术节点上改变金属堆对环境的影响。我们的研究结果表明,基于商业设计流程计算的模具面积和我们的参数化模型,将金属层数从8层更改为6层,对于130nm, 90nm和65nm技术,制造能源的平均节省分别为9.5%,13.8%和13%,并且,根据不同的场景,可能需要数年的运营能源节省来弥补这一差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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