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Analytic VLSI Placement using Electrostatic Analogy.

机译:使用静电类比分析VLSI放置。

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摘要

We develop a flat, analytic and nonlinear placement algorithm ePlace, which is more effective, generalized, simpler and faster than previous works. Based on the analogy between placement instance and electrostatic system, we develop a novel placement density function eDensity, which models every object as positive charge and the density cost as the potential energy of the electrostatic system. The electric potential and field distribution are coupled with density using a modified Poisson's equation, which is numerically solved by spectral methods using fast Fourier transform (FFT). Rather than conjugate gradient (CG) method by previous placers, we propose to use Nesterov's method for faster convergence. The efficiency bottleneck on line search is resolved by steplength prediction through an equation of Lipschitz constant. Through empirical validation, ePlace outperforms all prior placers with better quality and efficiency. On average of ISPD 2005 benchmarks, ePlace outperforms the leading placer BonnPlace with 2.83% shorter wirelength and runs 3.05x faster. On average of ISPD 2006 benchmarks, ePlace outperforms the leading placer MAPLE with 4.59% shorter wirelength and runs 2.84x faster.;Based on the above placement prototype, we develop ePlace-MS, an electrostatics based placement algorithm for mixed-size circuits. The density function eDensity is extended to handle the mixed-size placement. We conduct detailed analysis on the correctness of the gradient formulation and the numerical solution, as well as the rationale of density equalization with its advantages over prior density functions. Nesterov's method is shown with high yet stable performance over mixed-size circuits. The steplength prediction methodology is enhanced with backtracking strategy to prevent overestimation. A nonlinear preconditioner is developed to minimize the topological and physical differences between large macros and standard cells. Besides, we devise a simulated annealer for direct macro-layout legalization. All the above innovations are integrated into our mixed-size placement prototype ePlace-MS, which outperforms all the related works in literature with better quality and efficiency. Compared to the leading-edge mixed-size placer NTUplace3, ePlace-MS produces up to 22.98% and on average 8.22% shorter wirelength over all the sixteen modern mixed-size (MMS) benchmark circuits with the same runtime.
机译:我们开发了一种扁平的,解析的和非线性的放置算法ePlace,它比以前的作品更有效,更通用,更简单,更快。基于放置实例与静电系统之间的类比,我们开发了一种新颖的放置密度函数eDensity,该模型将每个对象建模为正电荷,并将密度成本建模为静电系统的势能。使用改进的泊松方程将电势和场分布与密度耦合,该方程通过使用快速傅立叶变换(FFT)的频谱方法在数值上求解。我们建议使用Nesterov方法而不是以前的放置器的共轭梯度(CG)方法来实现更快的收敛。通过Lipschitz常数方程的步长预测解决了在线搜索的效率瓶颈。通过经验验证,ePlace在质量和效率上都优于所有以前的放置器。平均而言,ISPD 2005年基准测试中,ePlace的线长缩短了2.83%,性能优于领先的放置器BonnPlace,运行速度提高了3.05倍。根据ISPD 2006的平均基准,ePlace的引线长度短了4.59%,胜过领先的放置器MAPLE,运行速度快了2.84倍。;基于上述放置原型,我们开发了ePlace-MS,这是一种用于混合尺寸电路的基于静电的放置算法。扩展密度函数eDensity以处理混合尺寸的放置。我们对梯度公式和数值解的正确性以及密度均衡的原理进行了详细的分析,它具有优于现有密度函数的优点。展示了Nesterov的方法在混合尺寸电路上具有高而稳定的性能。通过回溯策略增强了步长预测方法,以防止高估。开发了非线性预处理器,以最大程度地减少大型宏和标准单元之间的拓扑和物理差异。此外,我们设计了一种模拟退火炉,用于直接进行宏观布局合法化。以上所有创新都集成到我们的混合尺寸放置原型ePlace-MS中,该原型以更好的质量和效率优于文献中的所有相关作品。与领先的混合尺寸放置器NTUplace3相比,ePlace-MS在所有16个现代混合尺寸(MMS)基准测试电路上以相同的运行时间可产生多达22.98%的线长,平均短线长8.22%。

著录项

  • 作者

    Lu, Jingwei.;

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Computer engineering.;Computer science.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 119 p.
  • 总页数 119
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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