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Margin Optimization of Single Flux Quantum Logic Cells

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Design Automation of Quantum Computers

Abstract

Single Flux Quantum (SFQ) logic family is an attractive alternative to CMOS technology with the promise of more than two orders of magnitude improvement in the energy-delay product. However, component-level parameter variations during the fabrication process of SFQ logic cells are quite high. Therefore, optimizing SFQ logic cells to maximize their operating parameter margin (and parametric yield) under variability sources is a necessity. In this chapter, a hybrid design optimization technique based on Automatic Niching Particle Swarm Optimization and Fireworks Algorithm is presented where the objective is to maximize the upper and lower bound margins of the design parameters of a SFQ logic cell. The proposed algorithm can efficiently optimize both simple and complex multi-stage logic cells with various fan-in and fan-out counts. The proposed method improves the critical margin range and parametric yield values for 6 different logic cells by 22.83% and 15.22% on average, when compared to a previously optimized open-source cell library.

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Authors and Affiliations

  1. University of Southern California, Los Angeles, CA, USA

    Mustafa Altay Karamuftuoglu, Soheil Nazar Shahsavani & Massoud Pedram

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  1. Mustafa Altay Karamuftuoglu
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  2. Soheil Nazar Shahsavani
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  3. Massoud Pedram
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Correspondence to Mustafa Altay Karamuftuoglu .

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  1. IBM, Poughkeepsie, NY, USA

    Rasit O. Topaloglu

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Karamuftuoglu, M.A., Nazar Shahsavani, S., Pedram, M. (2023). Margin Optimization of Single Flux Quantum Logic Cells. In: Topaloglu, R.O. (eds) Design Automation of Quantum Computers. Springer, Cham. https://doi.org/10.1007/978-3-031-15699-1_6

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  • DOI: https://doi.org/10.1007/978-3-031-15699-1_6

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