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    • 1. 发明授权
    • Global statistical optimization, characterization, and design
    • 全局统计优化,表征和设计
    • US08024682B2
    • 2011-09-20
    • US12396972
    • 2009-03-03
    • Trent Lorne McConaghyPat DrennanJoel CooperJeffrey DyckDavid CalleleShawn RusawSamer SallamJiangdon GeAnthony ArklesKristopher BreenSean Cocks
    • Trent Lorne McConaghyPat DrennanJoel CooperJeffrey DyckDavid CalleleShawn RusawSamer SallamJiangdon GeAnthony ArklesKristopher BreenSean Cocks
    • G06F17/50
    • G06F17/5063
    • For application to analog, mixed-signal, and custom digital circuits, a system and method to do: global statistical optimization (GSO), global statistical characterization (GSC), global statistical design (GSD), and block-specific design. GSO can perform global yield optimization on hundreds of variables, with no simplifying assumptions. GSC can capture and display mappings from design variables to performance, across the whole design space. GSC can handle hundreds of design variables in a reasonable time frame, e.g., in less than a day, for a reasonable number of simulations, e.g., less than 100,000. GSC can capture design variable interactions and other possible nonlinearities, explicitly capture uncertainties, and intuitively display them. GSD can support the user's exploration of design-to-performance mappings with fast feedback, thoroughly capturing design variable interactions in the whole space, and allow for more efficiently created, more optimal designs. Block-specific design should make it simple to design small circuit blocks, in less time and with lower overhead than optimization through optimization.
    • 对于应用于模拟,混合信号和定制数字电路的系统和方法:全局统计优化(GSO),全局统计特征(GSC),全局统计设计(GSD)和块特定设计。 GSO可以对数百个变量执行全局收益优化,而不需要简化假设。 GSC可以在整个设计空间中捕获并显示从设计变量到性能的映射。 GSC可以在合理的时间范围内处理数百个设计变量,例如在不到一天的时间内,对于合理数量的模拟,例如小于100,000。 GSC可以捕获设计变量交互和其他可能的非线性,明确地捕获不确定性,并直观显示它们。 GSD可以通过快速反馈支持用户对设计到性能映射的探索,彻底地捕获整个空间中的设计变量交互,并允许更有效地创建,更优化的设计。 块特定设计应使设计小电路块的设计变得简单,在优化过程中,在更短的时间内和更低的开销。
    • 10. 发明授权
    • Model-building optimization
    • 建模优化
    • US08006220B2
    • 2011-08-23
    • US12237069
    • 2008-09-24
    • Trent Lorne McConaghyKristopher BreenShawn RusawDavid Callele
    • Trent Lorne McConaghyKristopher BreenShawn RusawDavid Callele
    • G06F17/50
    • G06F17/5063G06F2217/08
    • A method and system for performing multi-objective optimization of a multi-parameter design having several variables and performance metrics. The optimization objectives include the performance values of surrogate models of the performance metrics and the uncertainty in the surrogate models. The uncertainty is always maximized while the performance metrics can be maximized or minimized in accordance with the definitions of the respective performance metrics. Alternatively, one of the optimization objectives can be the value of a user-defined cost function of the multi-parameter design, the cost function depending from the performance metrics and/or the variables. In this case, the other objective is the uncertainty of the cost function, which is maximized. The multi-parameter designs include electrical circuit designs such as analog, mixed-signal, and custom digital circuits.
    • 用于执行具有若干变量和性能度量的多参数设计的多目标优化的方法和系统。 优化目标包括性能指标的代理模型的性能价值和代理模型中的不确定性。 不确定性总是最大化,同时可以根据相应性能指标的定义最大化或最小化性能指标。 或者,优化目标之一可以是多参数设计的用户定义的成本函数的值,成本函数取决于性能度量和/或变量。 在这种情况下,另一个目标是成本函数的不确定性,这是最大化的。 多参数设计包括电路设计,如模拟,混合信号和定制数字电路。