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Bee Colony Inspired Metamodeling Based Fast Optimization of a Nano-CMOS PLL

机译:蜂群启发元建模基于纳米CMOS PLL的快速优化

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The design and optimization complexity of analog/mixed-signal (AMS) components causes significant increase in the design cycle as the technology progresses towards deep nanoscale. This paper presents a two-tier approach to significantly reduce the design cycle time by combining accurate metamodeling and intelligent optimization. The paper first presents metamodeling which is a surrogate model of a parasitic-aware SPICE model of the circuit in order to simplify the optimization calculations and minimize the design space exploration time. The paper then introduces the Bee Colony Optimization (BCO) algorithm for nano-CMOS AMS circuit optimization. To best of the authors'' knowledge, this is the first research combining metamodel and BCO for AMS design space exploration. The proposed design optimization flow is used on 5 metamodels with 21 design parameters each, corresponding to 5 distinct Figures of Merit (FoMs) to conduct multi objective optimization. A 180 nm LC-VCO PLL frequency generation circuit is used as case study. The optimization achieved approx. 90% power and 52% jitter reduction while keeping locking time constraints on the system. In comparison to an exhaustive simulation approach, metamodeling is 10^20 times faster.
机译:模拟/混合信号(AMS)组件的设计和优化复杂性导致设计周期的显着增加,因为该技术对深纳米级进行了进展。本文提出了一种双层方法,通过组合精确的元模拟和智能优化来显着降低设计周期时间。本文首先提出了元素,它是电路的寄生感知的香料模型的代理模型,以简化优化计算并最小化设计空间探索时间。然后,本文介绍了纳米CMOS AMS电路优化的蜂菌落优化(BCO)算法。为了最好的作者的知识,这是第一次研究Metamodel和BCO的AMS设计空间探索。所提出的设计优化流量用于5个元坐标,每个元素各自为21个设计参数,对应于5个不同的优点(FOM)图形,以进行多目标优化。使用180nm LC-VCO PLL频率产生电路作为案例研究。优化实现了大约。 90%的功率和52%的抖动减少,同时保持系统上的锁定时间限制。与详尽的仿真方法相比,Metomodeling速度速度为10 ^ 20倍。

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