Parameterized Model Reduction Techniques for Simulation and Optimization of Mixed-Signal Systems

用于混合信号系统仿真和优化的参数化模型简化技术

• 批准号: 0306588
• 负责人: Jacob White
• 金额: $ 30万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-15 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0306588&HistoricalAwards=false
• 关键词: Parameterized; Model; Reduction; Techniques; Simulation

The notion of prototyping is pervasive in engineering design; one investigates the viability of a new idea by constructing a single implementation, a prototype. Whether the problem is designing an integrated circuit transceiver, a micromachining-based thumbnail-sized chemical agent detector, or an aircraft, the cost and time required toconstruct prototypes is high enough to discourage comprehensive design exploration. It is possible to dramatically reduce the need for physical prototypes by substituting computer models, a process referred to as computational prototyping. The promise of using computational prototyping is that the ease of testing alternative designs will allow designers to examine more radical, and possibility much more efficient, design alternatives. The challenge of computational prototyping is in developing accurate modeling algorithms and techniques which are both flexible and fast enough to allow designers to examine a wide range of design alternatives.For complicated systems, which may have millions of interacting components, computational prototyping using direct numerical simulation is too slow for designers to use in design exploration. Instead, it is necessary to exploit hierarchy in the computational prototype, and most hierarchical computer verification and optimization tools rely on manually generated high-level models for function blocks in the design. This ``by-hand'' process is time-consuming and error-prone, and interferes with rapid deployment of new technology. For this reason, there is strong interest in developing techniques which automatically generate accurate high-level models from more detailed numerical simulation.Over the past decade, substantial effort has been devoted to finding automatic strategies for extracting high-level models from linear interconnect and packaging. This effort was successful in a very practical sense, commercial computer-aided companies now provide users with a wide range of very sophisticated techniques for extractinghigh-level models of interconnect. Chip designers are no longer required to be signal integrity experts. In addition, the research also substantially deepened the understanding of the general problem of model reduction. And it is from this only recently achievedvantage point that we now think we can start to tackle the next two problems: generating {\it parameterized} reduced-order models for use in hierarchical optimization, and automatically reducing the nonlinear systems associated with micromachined devices or analog subsystems. We originally proposed to investigate both the problems of nonlinear modelreduction and parameterized model reduction. With the reduced budget,we will investigate only the nonlinear model reduction problem, to automatically generate low-order models of micromachined devices andanalog subsystems. We will be examining strategies involving nonlineargeneralizations of balanced realizations, and combining such strategieswith trajectory piecewise linearizations to generate accurate subsystemmodels.

原型设计的概念在工程设计中普遍存在。一个人通过构建单个实现，一个原型来研究新想法的生存能力。 问题是设计集成电路收发器，基于微加工的缩略图化学剂检测器还是飞机，Tocrounts原型所需的成本和时间都足以阻止全面的设计探索。可以通过替换计算机模型来大大减少对物理原型的需求，该过程称为计算原型。 使用计算原型制作的希望是，测试替代设计的便捷性将使设计人员能够更加激进，并且可能更有效地设计设计替代方案。 计算原型制作的挑战在于开发准确的建模算法和技术，这些算法和技术既灵活又足够快，以使设计人员能够检查广泛的设计替代方案。对于复杂的系统，对于数百万的相互作用组件，使用直接数值模拟的计算原型可能太慢而无法用于设计勘探。取而代之的是，有必要在计算原型中利用层次结构，并且大多数层次结构的计算机验证和优化工具都依赖于手动生成的高级模型来用于设计中的功能块。这个``副手''过程是耗时且容易出错的过程，并且会干扰新技术的快速部署。因此，人们对开发技术产生了浓厚的兴趣，这些技术会自动从更详细的数值模拟中自动生成准确的高级模型。在过去的十年中，已经致力于从线性互连和包装中提取高级模型的自动策略。 从实际意义上讲，这项工作是成功的，商业计算机辅助公司现在为用户提供了多种非常复杂的技术来提取互连的高级模型。不再需要芯片设计师成为信号完整性专家。此外，该研究还大大加深对模型降低的一般问题的理解。 正是从最近才能实现的点，我们现在认为我们可以开始解决接下来的两个问题：生成用于层次优化的{\ it参数化}降低级别模型，并自动降低与微机械设备或模拟子系统相关的非线性系统。我们最初建议研究非线性模型删除的问题和参数化模型还原。 随着预算降低，我们将仅研究非线性模型减少问题，以自动生成微机械设备和Analag子系统的低阶模型。 我们将研究涉及平衡实现的非线性一般化的策略，并将此类策略与轨迹分段线性化相结合以生成准确的子系统模型。