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Optimization-Based Placer

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Analog Integrated Circuit Design Automation

Abstract

This Chapter addresses the optimization-based Placer proposed in the automatic layout generation tool, AIDA-L. Unlike, AIDA-L’s template-based Placer, presented in Chapter 4 of this book, the optimization-based Placer dispenses most of the information contained in the template file. Instead, it applies a multi-objective algorithm to an absolute floorplan representation in order to determine the cells’ locations. Cells can be organized in proximity groups which implement the desired set of symmetry and proximity requirements, bridging the difficulties found on the state-of-the-art works on fulfilling the proximity constraints. Moreover, and to reduce the problem complexity, the intrinsic hierarchy of analog integrated circuit layout is explored, where the Pareto fronts for each proximity group of the problem are combined in a bottom-up fashion. This methodology provides the designer with a Pareto front of placements representing the feasible tradeoffs between the optimization objectives. The first Section of this Chapter covers the general architecture of the Placer, followed by the multi-objective algorithm developed. In Section “XML Description for Optimization-based Placement”, the relevant information contained in the template file is described. After, the problem of placement optimization with constraint handling in absolute coordinates is defined, as well as the hierarchical framework. Finally, the current-flow constraints and current-density considerations taken during placement optimization are detailed, in order to improve circuit’s routability, performance and post-layout reliability.

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References

  1. B. Suman, P. Kumar, A survey of simulated annealing as a tool for single and multiobjective optimization. J. Oper. Res. Soc. 57, 1143–1160 (2006)

    Article  MATH  Google Scholar 

  2. D.K. Nam, C.H. Park, Multiobjective simulated annealing: A comparative study to evolutionary algorithms. Int. J. Fuzzy Syst. 2(2), 87–97 (2000)

    Google Scholar 

  3. M. Hapke, A. Jaszkiewicz, R. Slowinski, Pareto simulated annealing for fuzzy multi-objective combinatorial optimization. J. Heuristics 6(3), 329–345 (2000)

    Article  MATH  Google Scholar 

  4. A. Suppapitnarm, K.A. Seffen, G.T. Parks, P.J. Clarkson, A simulated annealing algorithm for multiobjective optimization. Eng. Optim. 33(1), 59–85 (1999)

    Article  Google Scholar 

  5. E.L. Ulungu, J. Teghaem, P. Fortemps, D. Tuyttens, MOSA method: A tool for solving multiobjective combinatorial decision problems. J. Multi-Criteria Decis. Anal. 8(4), 221–236 (1999)

    Article  MATH  Google Scholar 

  6. I. Das, J. Dennis, A closer look at drawbacks of minimizing weighted sums of objectives for pareto set generation in multicriteria optimization problems. Struct. Optim. 14(1), 63–69 (1997)

    Article  Google Scholar 

  7. S. Bandyopadhyay, S. Saha, U. Maulik, K. Deb, A simulated annealing-based multiobjective optimization algorithm: AMOSA. IEEE Trans. Evol. Comput. 12(3), 269–283 (2008)

    Article  Google Scholar 

  8. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  9. J. Knowles, D. Corne, The Pareto archived evolution strategy: A new baseline algorithm for multiobjective optimization, in Proceedings of the 1999 Congress on Evolutionary Computation, July 1999, pp. 98–105

    Google Scholar 

  10. M. Eick, M. Strasser, K. Lu, U. Schlichtmann, H. Graeb, Comprehensive generation of hierarchical placement rules for analog integrated circuits. IEEE Trans. Comput. Aided Des. Integr. Circ. Syst. 30(2), 180–193 (2011)

    Article  Google Scholar 

  11. P.-H. Lin, S.-C. Lin, Analog placement based on novel symmetry-island formulation, in Proceedings of the 44th ACM/IEEE Design Automation Conference (DAC), June 2007, pp. 465–470

    Google Scholar 

  12. P.-H. Lin, S.-C. Lin, Analog placement based on hierarchical module clustering, in Proceedings of the 45th ACM/IEEE Design Automation Conference (DAC), June 2008, pp. 50–55

    Google Scholar 

  13. P.-H. Lin, Y.-W. Chang, S.-C. Lin, Analog placement based on symmetry-island formulation. IEEE Trans. Comput. Aided Des. 28(6), 791–804 (2009)

    Article  Google Scholar 

  14. P.-H. Wu, M. Lin, T.-C. Chen, C.-F. Yeh, T.-Y. Ho, B.-D. Liu, Exploring feasibilities of symmetry islands and monotonic current paths in slicing trees for analog placement. IEEE Trans. Comput. Aided Des. Integr. Circ. Syst. 33(6), 879–892 (2014)

    Article  Google Scholar 

  15. H.-C. Ou, H.-C. Chien, Y.W. Chang, Simultaneously analog placement and routing with current flow and current density considerations, in Proceedings of the 50th ACM/IEEE Design Automation Conference (DAC), June 2013, pp. 1–6

    Google Scholar 

  16. P.-H. Wu, M. Lin, Y.-R. Chen, B.-S. Chou, T.-C. Chen, T.-Y. Ho, B.-D. Liu, Performance-driven analog placement considering monotonic current paths, in Proceedings of the International Conference on Computer-Aided Design (ICCAD), Nov 2012, pp. 613–619

    Google Scholar 

  17. R. Póvoa, N. Lourenço, N. Horta, R. Santos-Tavares, J. Goes, Single-stage amplifiers with gain enhancement and improved energy-efficiency employing voltage-combiners, in 21st IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), Oct 2013, pp. 19–22

    Google Scholar 

  18. J. Lienig, Electromigration-aware physical design of integrated circuits, in 18th International Conference on VLSI Design, Jan 2005, pp. 77–82

    Google Scholar 

  19. D. Long, X. Hong, S. Dong, Signal-path driven partition and placement for analog circuit, in Asia and South Pacific Conference on Design Automation (ASP-DAC), Jan 2006, pp. 694–699

    Google Scholar 

  20. R. Martins, R. Póvoa, N. Lourenço and N. Horta, Current-flow & current-density-aware multi-objective optimization of analog ic placement. Integr. VLSI J. (in press, 2016). Reprinted from Integration, the VLSI Journal. With permission from Elsevier

    Google Scholar 

  21. R. Martins, N. Lourenco, N. Horta, Multi-objective optimization of analog integrated circuit placement hierarchy in absolute coordinates. Expert Syst. Appl. 42(23), 9137–9151 (2015). doi:10.1016/j.eswa.2015.08.020. Reprinted from Expert Syst. Appl. With permission from Elsevier

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Martins, R., Lourenço, N., Horta, N. (2017). Optimization-Based Placer. In: Analog Integrated Circuit Design Automation. Springer, Cham. https://doi.org/10.1007/978-3-319-34060-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-34060-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34059-3

  • Online ISBN: 978-3-319-34060-9

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