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Optimal demultiplexer unit design and energy estimation using quantum dot cellular automata

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Abstract

Quantum dot cellular automata (QCA)-based demultiplexer or DeMUX is a basic module of nanocommunication and nanocomputation, like a multiplexer. However, the design and analysis of demultiplexer using QCA have been neglected by researchers, unlike multiplexer. This article proposed and analyzed a simple and optimized QCA-based single-layered demultiplexer only using two majority gates, one inverter and two clocks. Our proposed area-efficient DeMUX has a complexity of 21 QCA cells, which covered a total area of 20,412 nm2 and a cell area of 6804 nm2 with area usage of 33.33%. The latency of the proposed block is 0.5 clock, and the calculated cost is 20. The energy dissipation analysis using QDE tool shows that the total energy dissipation is 8.64e−003 eV and the average energy dissipation per cycle is 7.85e−004 eV of QCA demultiplexer. Also, energy has been calculated using the popular tool QCAPro in three tunneling levels with \(\gamma =0.5E_{\mathrm{K}},\gamma =1.0E_{\mathrm{K}}\) and \(\gamma =1.5E_{\mathrm{K}}\) at 2K temperature, and the total energy dissipated as 32.86 meV, 41.41 meV and 52.21 meV, respectively.

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References

  1. Lent CS, Tougaw PD, Porod W, Bernstein GH (1993) Quantum cellular automata. Nanotechnology 4(1):49–57. https://doi.org/10.1088/0957-4484/4/1/004

    Article  Google Scholar 

  2. Ahmadpour S, Mosleh M, Heikalabad SR (2020) The design and implementation of a robust single-layer qca alu using a novel fault-tolerant three-input majority gate. J Supercomput. https://doi.org/10.1007/s11227-020-03249-3

    Article  Google Scholar 

  3. Tougaw PD, Lent CS (1994) Logical devices implemented using quantum cellular automata. J Appl Phys 75(3):1818–1825. https://doi.org/10.1063/1.356375

    Article  Google Scholar 

  4. Goswami M, Chattopadhyay S, Tripathi SB, Sen B (2020) Design of fault tolerant majority voter for error resilient TMR targeting micro to nano scale logic. Int J Comput Sci Eng 21(3):375–393. https://doi.org/10.1504/IJCSE.2020.106062

    Article  Google Scholar 

  5. Khan A, Chakrabarty R (2013) Design of high polarized binary wires using minimum number of cells & related kink energy calculations in quantum dot cellular automata. Int J Electron Commun Technol 4(Spl-2):54–57

    Google Scholar 

  6. Khan A, Chakrabarty R (2013) Novel design of high polarized inverter using minimum number of rotated cells and related kink energy calculation in quantum dot cellular automata. Int J Soft Comput Eng 3(1):165–169

    Google Scholar 

  7. Bahar AN, Ahmad F, Wani S, Al-Nisa S, Bhat GM (2019) New modified-majority voter-based efficient QCA digital logic design. Int J Electron 106(3):333–348. https://doi.org/10.1080/00207217.2018.1531315

    Article  Google Scholar 

  8. Singh G, Sarin R, Raj B (2017) Design and analysis of area efficient QCA based reversible logic gates. Microprocess Microsyst 52:59–68. https://doi.org/10.1016/j.micpro.2017.05.017

    Article  Google Scholar 

  9. Perri S, Corsonello P, Cocorullo G (2014) Area-delay efficient binary adders in QCA. IEEE Trans Very Large Scale Integr Syst 22(5):1174–1179. https://doi.org/10.1109/TVLSI.2013.2261831

    Article  Google Scholar 

  10. Balali M, Rezai A, Balali H, Rabiei F, Emadi S (2017) Towards coplanar quantum-dot cellular automata adders based on efficient three-input XOR gate. Results Phys 7:1389–1395. https://doi.org/10.1016/j.rinp.2017.04.005

    Article  Google Scholar 

  11. Mokhtari D, Rezai A, Rashidi H, Rabiei F, Emadi S, Karimi A (2018) Design of novel efficient full adder architecture for quantum-dot cellular automata technology. Facta Univ Ser Electron Energ 31(2):279–285. https://doi.org/10.2298/FUEE1802279M

    Article  Google Scholar 

  12. Roshany HR, Rezai A (2019) Novel efficient circuit design for multilayer QCA RCA. Int J Theor Phys 58:1745–1757. https://doi.org/10.1007/s10773-019-04069-9

    Article  MathSciNet  MATH  Google Scholar 

  13. Cho H, Swartzlander EE (2009) Adder and multiplier design in quantum-dot cellular automata. IEEE Trans Comput 58(6):721–727. https://doi.org/10.1109/TC.2009.21

    Article  MathSciNet  MATH  Google Scholar 

  14. AlKaldy E, Majeed AH, Zainal MS, Nor DBM (2020) Optimum multiplexer design in quantum-dot cellular automata. Indones J Electr Eng Comput Sci 17(1):148–155. https://doi.org/10.11591/ijeecs.v17.i1.pp148-155

    Article  Google Scholar 

  15. Khan A, Arya R (2019) Energy dissipation and cell displacement analysis of QCA multiplexer for nanocomputation. In: 2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP), Chennai, India, pp 1–5. https://doi.org/10.1109/ICESIP46348.2019.8938359

  16. Singh S, Pandey S, Wairya S (2016) Modular design of 2n:1 quantum dot cellular automata multiplexers and its application, via clock zone based crossover. Int J Mod Educ Comput Sci 8(7):41–52. https://doi.org/10.5815/ijmecs.2016.07.05

    Article  Google Scholar 

  17. Iqbal J, Khanday FA, Shah NA (2013) Design of quantum-dot cellular automata (qca) based modular 2n-1-2n mux–demux. In: IEEE International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT). Aligarh 2013, pp 189–193. https://doi.org/10.1109/MSPCT.2013.6782116

  18. Ahmad F (2017) An optimal design of QCA based \(2^n:1/1:2^n\) multiplexer/demultiplexer and its efficient digital logic realization. Microprocess Microsyst 56:64–75. https://doi.org/10.1016/j.micpro.2017.10.010

    Article  Google Scholar 

  19. Safoev N, Jeon J (2016) Low area complexity demultiplexer based on multilayer quantum-dot cellular automata. Int J Control Autom 9(12):165–178. https://doi.org/10.14257/ijca.2016.9.12.15

    Article  Google Scholar 

  20. Das JC, De D (2017) Circuit switching with quantum-dot cellular automata. Nano Commun Netw 14:16–28. https://doi.org/10.1016/j.nancom.2017.09.002

    Article  Google Scholar 

  21. Shah NA, Khanday FA, Bangi ZA, Iqbal J (2011) Design of quantum-dot cellular automata (QCA) based modular 1 to 2n demultiplexers. Int J Nanotechnol Appl 5(1):47–58

    Google Scholar 

  22. Das B, Mahmood M, Rabeya M, Bardhan R (2019) An effective design of 2:1 multiplexer and 1:2 demultiplexer using 3-dot QCA architecture. In: 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, pp 570–575. https://doi.org/10.1109/icrest.2019.8644353

  23. Sardinha LHB, Costa AMM, Neto OPV, Vieira LFM, Vieira MAM (2013) Nanorouter: a quantum-dot cellular automata design. IEEE J Sel Areas Commun 31(12):825–834. https://doi.org/10.1109/JSAC.2013.SUP2.12130015

    Article  Google Scholar 

  24. Huang J, Momenzadeh M, Lombardi F (2007) Design of sequential circuits by quantum-dot cellular automata. Microelectron J 38(4–5):525–537. https://doi.org/10.1016/j.mejo.2007.03.013

    Article  Google Scholar 

  25. Abdullah-Al-Shafi M, Bahar AN, Habib MA, Bhuiyan MMR, Ahmad F, Ahmad PZ, Ahmed K (2018) Designing single layer counter in quantum-dot cellular automata with energy dissipation analysis. Ain Shams Eng J 9(4):2641–2648. https://doi.org/10.1016/j.asej.2017.05.010

    Article  Google Scholar 

  26. Sabbaghi-Nadooshan R, Kianpour M (2014) A novel QCA implementation of mux-based universal shift register. J Comput Electron 13:198–210. https://doi.org/10.1007/s10825-013-0500-9

    Article  MATH  Google Scholar 

  27. Vankamamidi V, Ottavi M, Lombardi F (2005) A line-based parallel memory for QCA implementation. IEEE Trans Nanotechnol 4(6):690–698. https://doi.org/10.1109/TNANO.2005.858589

    Article  Google Scholar 

  28. Vankamamidi V, Ottavi M, Lombardi F (2008) A serial memory by quantum-dot cellular automata (QCA). IEEE Trans Comput 57(5):606–618. https://doi.org/10.1109/TC.2007.70831

    Article  MathSciNet  MATH  Google Scholar 

  29. Hu XS, Crocker M, Niemier M, Yan Minjun, Bernstein G (2006) PLAs in quantum-dot cellular automata. In: IEEE Computer Society Annual Symposium on Emerging VLSI Technologies and Architectures (ISVLSI’06). Karlsruhe 2006, p 6. https://doi.org/10.1109/ISVLSI.2006.73

  30. Niemier MT, Kontz MJ, Kogge PM (2000) A design of and design tools for a novel quantum dot based microprocessor. In: Annual Design Automation Conference (DAC ’00). Association for Computing Machinery, New York, NY, USA, 2000, pp 227–232. https://doi.org/10.1145/337292.337398

  31. De D, Das JC (2020) Nanocomputing channel fidelity of QCA code converter circuits under thermal randomness. J Comput Electron 19:419–434. https://doi.org/10.1007/s10825-019-01411-6

    Article  Google Scholar 

  32. Bahar AN, Wahid KA (2020) Design of an efficient \(N \times N\) butterfly switching network in quantum-dot cellular automata (QCA). IEEE Trans Nanotechnol 19:147–155. https://doi.org/10.1109/TNANO.2020.2969166

    Article  Google Scholar 

  33. Walus K, Dysart TJ, Jullien GA, Budiman RA (2004) QCADesigner: a rapid design and simulation tool for quantum-dot cellular automata. IEEE Trans Nanotechnol 3(1):26–31. https://doi.org/10.1109/TNANO.2003.820815

    Article  Google Scholar 

  34. QCADesigner-E (2017) https://github.com/FSillT/QCADesigner-E. Accessed 12 Mar 2019

  35. Srivastava S, Asthana A, Bhanja S, Sarkar S (2011) QCAPro—an error-power estimation tool for QCA circuit design. In: IEEE International Symposium of Circuits and Systems (ISCAS). Rio de Janeiro 2011, pp 2377–2380. https://doi.org/10.1109/ISCAS.2011.5938081

  36. Lent CS, Tougaw PD (1997) A device architecture for computing with quantum dots. Proc IEEE 85(4):541–557. https://doi.org/10.1109/5.573740

    Article  Google Scholar 

  37. Porod W, Lent C, Bernstein GH, Orlov AO, Hamlani I, Snider GL, Merz JL (1999) Quantum-dot cellular automata: computing with coupled quantum dots. Int J Electron 86(5):549–590. https://doi.org/10.1080/002072199133265

    Article  Google Scholar 

  38. Orlov AO, Amlani I, Bernstein GH, Lent CS, Snider GL (1997) Realization of a functional cell for quantum-dot cellular automata. Science 277(5328):928–930. https://doi.org/10.1126/science.277.5328.928

    Article  Google Scholar 

  39. Retallick J, Walus K (2020) Limits of adiabatic clocking in quantum-dot cellular automata. J Appl Phys 127:054502. https://doi.org/10.1063/1.5135308

    Article  Google Scholar 

  40. Chaves JF, Ribeiro MA, Torres FS, Neto OPV (2018) Enhancing fundamental energy limits of field-coupled nanocomputing circuits. In: IEEE International Symposium on Circuits and Systems (ISCAS). Florence 2018, pp 1–5. https://doi.org/10.1109/ISCAS.2018.8351150

  41. Torres FS, Niemann P, Wille R, Drechsler R (2018) Breaking Landauer’s limit using quantum-dot cellular automata. https://arxiv.org/pdf/1811.03894.pdf. Accessed 12 Jan 2019

  42. Sill Torres F, Wille R, Niemann P, Drechsler R (2018) An energy-aware model for the logic synthesis of quantum-dot cellular automata. IEEE Trans Comput-Aided Des Integr Circuits Syst 37(12):3031–3041. https://doi.org/10.1109/TCAD.2018.2789782

    Article  Google Scholar 

  43. Timler J, Lent CS (2002) Power gain and dissipation in quantum-dot cellular automata. J Appl Phys 91(2):823–831. https://doi.org/10.1063/1.1421217

    Article  Google Scholar 

  44. Srivastava S, Sarkar S, Bhanja S (2009) Estimation of upper bound of power dissipation in QCA circuits. IEEE Trans Nanotechnol 8(1):116–127. https://doi.org/10.1109/TNANO.2008.2005408

    Article  Google Scholar 

  45. Liu W, Lu L, O’Neill M, Swartzlander EE (2014) A first step toward cost functions for quantum-dot cellular automata designs. IEEE Trans Nanotechnol 13(3):476–487. https://doi.org/10.1109/TNANO.2014.2306754

    Article  Google Scholar 

  46. Khosroshahy MB, Moaiyeri MH, Navi K, Bagherzadeh N (2017) An energy and cost efficient majority-based ram cell in quantum-dot cellular automata. Results Phys 7:3543–3551. https://doi.org/10.1016/j.rinp.2017.08.067

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank A. N. Bahar, Dept. of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, Canada, for his unconditional help to simulate circuits.

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  1. Department of Electronics and Communication Engineering, National Institute of Technology, Patna, India

    Angshuman Khan & Rajeev Arya

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Khan, A., Arya, R. Optimal demultiplexer unit design and energy estimation using quantum dot cellular automata. J Supercomput 77, 1714–1738 (2021). https://doi.org/10.1007/s11227-020-03320-z

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