Analog Placement with Current Flow and Symmetry Constraints using PCP-SP

Patyal, Abhishek; Pan, Po-Cheng; K.A., Asha; Chen, Hung-Ming; Chi, Hao-Yu; Liu, Chien-Nan Jimmy

doi:10.1109/dac.2018.8465574

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Similar constraints on enforcing the placed locations of matched cells include commoncentroid [19,33,38], regularity [7,26,39], proximity [6,18,25,[33][34][35]41] and etc. Constraints such as monotonic current flow [28,31,36] and thermal effects [19,20] have also been studied to ensure circuit performance. To ensuring the placement solutions can fit to the design floorplan, boundary constraint [14,24,25,34,35], pre-placed constrains [24,25,34,35] and etc.…”

Section: Related Workmentioning

confidence: 99%

“…As the functionalities of 1 https://github.com/krzhu/IdeaPlaceEx nets differ in AMS circuits, several efforts are made to distinguish the nets. For example, the work [41] gives higher weights on the critical nets, and the work [31] tries to minimize the width and length for parallel current paths.…”

Section: Related Workmentioning

confidence: 99%

“…However, it is not easy to be applied to other types of circuits. Another similar problem is the current flow-related constraints [28,31,36,37]. In those works, the direct current from the supply (VDD) to the sink (VSS) is constrained to be monotonic in one direction.…”

Section: Introductionmentioning

confidence: 99%

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Effective analog/mixed-signal circuit placement considering system signal flow

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

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Effective analog/mixed-signal circuit placement considering system signal flow

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Pole-Aware Analog Layout Synthesis Considering Monotonic Current Flows and Wire Crossings

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Fang

et al. 2023

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Exploiting a Deep Learning Toolbox for Human-Machine Feedback towards Analog Integrated Circuit Placement Automation

et al. 2022

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The layout design of analog integrated circuits has been defying all automation attempts, and it is still primarily a handcrafting process carried by circuit designers on traditional layout editing frameworks. This paper presents a toolbox based on deep learning techniques and a sturdy graphical user interface to assist designers during that process. The underlying mechanism of this toolbox relies on a simple pairwise device interaction circuit description, i.e., the circuits’ topological constraints, to propose valid floorplan solutions for block-level structures, including topologies and deep nanometer technology nodes not used for its training, at push-button speed. Despite its automatic functionalities, the toolbox is focused on explainable artificial intelligence, involving the designer in the synthesis flow via filtering and editing options over the candidate floorplan solutions. This constant state of human-machine feedback environment turns the designer aware of the impact of each device’s position change and inherent tradeoffs while suggesting subsequent moves, ultimately increasing the designers’ productivity in this time-consuming and iterative task. Finally, the toolbox is shown to instantly generate floorplans with similar or better constraint fulfilment than human designed solutions for state-of-the-art analog circuit blocks.

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Analog Placement with Current Flow and Symmetry Constraints using PCP-SP

Cited by 3 publications

References 6 publications

Effective analog/mixed-signal circuit placement considering system signal flow

Effective analog/mixed-signal circuit placement considering system signal flow

Pole-Aware Analog Layout Synthesis Considering Monotonic Current Flows and Wire Crossings

Exploiting a Deep Learning Toolbox for Human-Machine Feedback towards Analog Integrated Circuit Placement Automation

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