CAREER: From O(N) to O(M): Scalable Algorithms for Large Scale Electromagnetics-Based Analysis and Design of Next Generation VLSI Circuits

职业：从 O(N) 到 O(M)：用于下一代 VLSI 电路的基于大规模电磁学分析和设计的可扩展算法

• 批准号: 0747578
• 负责人: Dan Jiao
• 金额: $ 40万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-02-01 至 2014-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0747578&HistoricalAwards=false
• 关键词: CAREER; Scalable; Algorithms; Large; Scale

Integrative, Hybrid and Complex SystemsPurdue UniversityDan JiaoCAREER: From O(N) to O(M): Scalable Algorithms for Large Scale Electromagnetics-Based Analysis and Design of Next Generation VLSI CircuitsIntellectual Merit: As on-chip design scales into the nanometer regime, full-wave electromagnetics (EM) analysis has increasingly become essential due to reduced feature sizes that lead to subwavelength optical lithography, increased clock frequency, the transition from single core to multicore, and increased levels of integration. However, the design of next-generation integrated circuits results in numerical problems of very large scale, requiring billions of parameters to describe accurately. State-of-the-art EM analysis algorithms require computation and memory that scales with N, the number of unknowns. This research focuses on reducing the complexity of required computation and memory to scale with M, the number of design decision parameters, which is a much smaller value than the number of unknowns. This reduction in complexity is required to enable the EM analysis of next-generation very large-scale integrated (VLSI) circuits. Instead of solving the original matrix of O(N) as it is, we construct a reduced matrix that involves only the O(M) parameters needed for the circuit design decision, while incorporating the effects of other parameters. Moreover, the original and reduced system matrices possess, or can be formulated to possess, special structure, for example a sparse banded structure. The structure will be explored or created to reduce the complexity of the reduction and the solution of the reduced system matrix under the framework of semi-separable matrices.Broader Impact: The project's education objectives are to effectively bridge the education in fields with that in circuits and to effectively introduce the human dimension into the integrated circuit-field education. Three education programs will be developed: (i) an undergraduate course in "Circuits and Fields," (ii) a graduate "High-Frequency Computer-Aided Design Studio," and (iii) a "Working-with-Differences Learning Community." Assessment tasks will evaluate the effectiveness of these programs. This research has the potential to contribute significantly to solving scalability problems with existing computational EM techniques for integrated circuit design. In addition, it has the potential to benefit a wide range of engineering applications in which large problem sizes are a bottleneck in preventing the successful design and analysis of advanced system

集成、混合和复杂系统普渡大学：从O(N)到O(M)：下一代VLSI电路基于电磁的大规模分析和设计的可扩展算法智能优势：随着芯片设计进入纳米级，全波电磁(EM)分析已变得越来越重要，因为特征尺寸减小导致亚波长光学光刻、更高的时钟频率、从单核到多核的过渡以及更高的集成水平。然而，下一代集成电路的设计导致了非常大规模的数值问题，需要数十亿个参数来准确描述。最先进的EM分析算法需要随着未知数N的增加而增加的计算和内存。这项研究的重点是降低所需的计算和内存的复杂性，以规模与M，设计决策参数的数量，这是一个比未知数小得多的值。这种复杂性的降低是实现下一代超大规模集成电路(VLSI)电路的EM分析所必需的。我们构造了一个仅涉及电路设计决策所需的O(M)参数的简化矩阵，而不是直接求解O(N)的原始矩阵，同时考虑了其他参数的影响。此外，原始和简化的系统矩阵具有或可以被表示为具有特殊结构，例如稀疏带状结构。将探索或创建该结构，以降低半可分矩阵框架下约化系统矩阵的归约和求解的复杂性。广泛影响：该项目的教育目标是有效地在领域教育和电路教育之间架起桥梁，并将人的维度有效地引入集成电路领域教育。将开发三个教育计划：(I)“电路与磁场”的本科生课程，(Ii)“高频计算机辅助设计工作室”的研究生课程，和(Iii)“求同存异的学习社区”。评估任务将评估这些计划的有效性。这项研究有可能为解决集成电路设计中现有的计算电磁技术的可扩展性问题做出重大贡献。此外，它还具有广泛的工程应用的潜力，在这些工程应用中，大问题是阻碍高级系统成功设计和分析的瓶颈