DeMixGen: Deterministic Mixed-Signal Layout Generation With Separated Analog and Digital Signal Paths

Chang, Po-Hsun; Lee, Shuenn-Yuh; Graeb, Helmut

doi:10.1109/tcad.2015.2501295

Cited by 5 publications

(1 citation statement)

References 44 publications

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“…1 provides an example of such practice, where the capacitors are omitted to conserve space. While the placement and routing problems for AMS circuits have been actively explored recently [1,[3][4][5], well generation remains an unresolved challenge. Prior work [6] generated wells with a series of simple computational geometry operations, including geometric expansion and union.…”

Section: Introductionmentioning

confidence: 99%

WellGAN

Lin

Tang

et al. 2019

Proceedings of the 56th Annual Design Automation Conference 2019

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In back-end analog/mixed-signal (AMS) design flow, well generation persists as a fundamental challenge for layout compactness, routing complexity, circuit performance and robustness. The immaturity of AMS layout automation tools comes to a large extent from the difficulty in comprehending and incorporating designer expertise. To mimic the behavior of experienced designers in well generation, we propose a generative adversarial network (GAN) guided well generation framework with a post-refinement stage leveraging the previous high-quality manually-crafted layouts. Guiding regions for wells are first created by a trained GAN model, after which the well generation results are legalized through post-refinement to satisfy design rules. Experimental results show that the proposed technique is able to generate wells close to manual designs with comparable post-layout circuit performance.

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