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A methodology for concurrent process-circuit optimization

机译:并行过程电路优化的方法

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In order to optimize integrated circuit designs, it is critical not only for circuit designers to adjust circuit geometries but also for process developers to adjust device characteristics for optimal overall system performance. This paper describes concurrent process-circuit optimization (CPCO), a methodology for concurrent integrated circuit optimization that spans the fabrication process design and circuit design disciplines. CPCO enables process developers and circuit designers to work coordinately toward the common goal of optimizing a system-level objective, and therefore produces better designs than single-discipline optimization schemes. The methodology logically partitions the overall integrated circuit optimization task into loosely coupled process and circuit design tasks that may proceed concurrently-this produces substantial time savings over a flat "all-at-once" optimization approach. Finally, the CPCO method formulates a multiobjective optimization problem that may be used to negotiate tradeoffs in adjusting a single process to optimize multiple circuits, to optimize nominal circuit performances or to improve circuit yield. The implementation of the CPCO method in an extensible object-oriented software architecture is described. Results of applying the methodology to integrated circuit design examples with industrial grade simulation tools are presented. The results demonstrate substantial performance gains over separate process/circuit optimization and substantial time savings over "all-at-once" combined optimization.
机译:为了优化集成电路设计,不仅对于电路设计人员调整电路的几何形状至关重要,而且对于工艺开发人员调整器件特性以实现最佳整体系统性能也至关重要。本文介绍了并发工艺电路优化(CPCO),这是一种并发集成电路优化的方法,涵盖制造工艺设计和电路设计学科。 CPCO使过程开发人员和电路设计人员能够朝着优化系统级目标的共同目标进行协调工作,因此与单学科优化方案相比,它可以提供更好的设计。该方法在逻辑上将整个集成电路优化任务划分为可同时进行的松散耦合的过程和电路设计任务,这与平面的“一次全部”优化方法相比可节省大量时间。最后,CPCO方法提出了一个多目标优化问题,可用于协商调整单个过程以优化多个电路,优化标称电路性能或提高电路成品率时的权衡。描述了CPCO方法在可扩展的面向对象软件体系结构中的实现。给出了使用工业级仿真工具将该方法应用于集成电路设计实例的结果。结果表明,与单独的过程/电路优化相比,性能得到了显着提高;与“一次完成”的组合优化相比,可以节省大量时间。

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