设计和使用内存专用测试结构,以确保SRAM的良率和可制造性

F. Duan, R. Castagnetti, R. Venkatraman, O. Kobozeva, S. Ramesh
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引用次数: 16

摘要

高密度、高性能的单口和双口SRAM在片上系统产品设计中日益占据大部分的芯片面积。因此,良好的可产性和可制造性是SRAM必不可少的。同时,为了获得最佳的SRAM密度和性能,存在着巨大的竞争压力。我们之前已经发布并展示了业界最小和最快的嵌入式6T SRAM位单元,采用0.18 /spl mu/m和130 nm一代标准CMOS工艺。我们已经描述了这些SRAM位单元是如何在设计上健壮的,即使在积极推动密度和性能的同时。在本文中,我们讨论了sram特定测试结构的设计和使用,这些测试结构使我们能够快速评估工艺设计交互,并微调工艺和/或设计,以提高产量和可制造性。我们设计了测试结构,使用我们积极的生产位单元作为基础,以探测SRAM中任何可能的工艺或设计弱点。这些SRAM特定测试结构的结果与良率结果和在线SEM观察结果显示出良好的相关性,并使我们能够快速提高SRAM良率。我们还设计了SRAM-晶体管测试结构,以表征SRAM单元器件在实际工作环境中的特性。结果有助于评估电路的性能,并为进一步的设计改进提供指导。在开发周期的早期阶段使用这些数据对于模型验证也很有用。
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Design and use of memory-specific test structures to ensure SRAM yield and manufacturability
High-density and high-performance single-port and dual-port SRAM increasingly occupy a majority of the chip area in system-on-chip product designs. Therefore, good yieldability and manufacturability of the SRAM are essential. At the same time there is tremendous competitive pressure to get the best SRAM density and performance. We have previously published and presented the industry's smallest and fastest embedded 6T SRAM bitcells in 0.18 /spl mu/m and 130 nm generation standard CMOS process. We have described how these SRAM bitcells are robust by design even while aggressively driving density and performance. In this paper we discuss the design and use of SRAM-specific test structures that have enabled us to quickly evaluate process-design interactions and to fine-tune process and/or design for improving yields and manufacturability. We have designed test structures using our aggressive production bitcell as basis to probe for any possible weaknesses of the process or design in SRAM Results from these SRAM-specific test structures show good correlation to yield results and in-line SEM observations, and enable us to improve SRAM yields quickly. We have also designed SRAM-transistor test structures to characterize the SRAM cell devices in their real working environment. Results help to evaluate the circuit performance and provide us with guidelines for further design improvements. These data when used in the early stage of the development cycle are also useful for model validation.
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