Gate sizing and device technology selection algorithms for high-performance industrial designs

Muhammet Mustafa Ozdal, S. Burns, Jiang Hu
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引用次数: 60

Abstract

It is becoming more and more important to design high performance designs with as low power as possible. In this paper, we study the gate sizing and device technology selection problem for today's industrial designs. We first outline the typical practical problems that make it difficult to use the traditional algorithms on high-performance industrial designs. Then, we propose a Lagrangian Relaxation (LR) based formulation that decouples timing analysis from optimization without resulting in loss of accuracy. We also propose a graph model that accurately captures discrete cell type characteristics based on library data. We model the relaxed Lagrangian subproblem as a discrete graph problem, and propose algorithms to solve it. In our experiments, we demonstrate the importance of using the signoff timing engine to guide the optimization. Compared to a state-of-the art industrial optimization flow, we show that our algorithms can obtain up to 38% leakage power reductions and better overall timing for real high-performance microprocessor blocks.
高性能工业设计的栅极尺寸和器件技术选择算法
以尽可能低的功耗设计高性能的设计变得越来越重要。本文研究了当今工业设计中闸门尺寸和器件技术选择问题。我们首先概述了在高性能工业设计中难以使用传统算法的典型实际问题。然后,我们提出了一个基于拉格朗日松弛(LR)的公式,该公式将时间分析与优化解耦,而不会导致精度损失。我们还提出了一个基于库数据准确捕获离散单元格类型特征的图模型。我们将松弛拉格朗日子问题建模为离散图问题,并提出了求解该问题的算法。在我们的实验中,我们证明了使用签名定时引擎来指导优化的重要性。与最先进的工业优化流程相比,我们的算法可以为真正的高性能微处理器块获得高达38%的泄漏功耗降低和更好的整体时序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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