过程变异现象对绩效和质量评价的影响

G. Sery
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引用次数: 1

摘要

只提供摘要形式。逻辑产品密度和性能趋势继续遵循摩尔定律预测的过程。为了支持未来的趋势,并在本十年结束之前制造接近10亿个或更多晶体管的逻辑产品,必须面临几个挑战。这些挑战包括:1)保持晶体管/互连特征缩放,2)不断增加的功率密度困境,3)二维特征分辨率和一般关键尺寸控制的相对难度增加,4)确定成本有效的解决方案,以增加过程和设计数据库的复杂性,以及5)面对日益增长的控制,复杂性和可预测性问题,提高一般性能和质量可预测性。在解决新的晶体管结构、设计方法和产品架构(例如高k、金属栅极等)的功率密度问题的同时,晶体管缩放的趋势可以保持下去。项目3至5是这项工作的重点,也是密切相关的。一般的二维图形和分辨率控制问题需要通过设计和技术来解决,例如降低设计自由度,使用更简单的排列结构,提高均匀性,改进工具等。数据库复杂性/成本问题需要的解决方案可能涉及使用改进的数据结构、改进的层次结构以及改进的软件和硬件解决方案。绩效评估、可预见性和质量评估将受益于上述控制和复杂性问题的解决方案。此外,新的设计技术/工具以及改进的过程表征模型和方法可以解决一般的性能/质量评估挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of process variation phenomena on performance and quality assessment
Summary form only given. Logic product density and performance trends have continued to follow the course predicted by Moore's Law. To support the trends in the future and build logic products approaching one billion or more transistors before the end of the decade, several challenges must be met. These challenges include: 1) maintaining transistor/interconnect feature scaling, 2) the increasing power density dilemma, 3) increasing relative difficulty of 2-D feature resolution and general critical dimension control, 4) identifying cost effective solutions to increasing process and design database complexity, and 5), improving general performance and quality predictability in the face of the growing control, complexity and predictability issues. The trend in transistor scaling can be maintained while addressing the power density issue with new transistor structures, design approaches, and product architectures (e.g. high-k, metal gate, etc.). Items 3 to 5 are the focus of this work and are also strongly inter-related. The general 2-D patterning and resolution control problems will require several solution approaches both through design and technology e.g. reduce design degrees of freedom, use of simpler arrayed structures, improved uniformity, improved tools, etc. The data base complexity/cost problem will require solutions likely to involve use of improved data structure, improved use of hierarchy, and improved software and hardware solutions. Performance assessment, predictability and quality assessment will benefit from solutions to the control and complexity issues noted above. In addition, new design techniques/tools as well as improved process characterization models and methods can address the general performance/quality assessment challenge.
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