Broadband Communications, Networks, and Systems. 9th International EAI Conference, Broadnets 2018, Faro, Portugal, September 19–20, 2018, Proceedings

Research Article

Fast Statistical Modelling of Temperature Variation on 28 nm FDSOI Technology

  • @INPROCEEDINGS{10.1007/978-3-030-05195-2_28,
        author={Abdelgader Abdalla and Isiaka Alimi and Manuel Gonz\^{a}lez and Issa Elfergani and Jonathan Rodriguez},
        title={Fast Statistical Modelling of Temperature Variation on 28 nm FDSOI Technology},
        proceedings={Broadband Communications, Networks, and Systems. 9th International EAI Conference, Broadnets 2018, Faro, Portugal, September 19--20, 2018, Proceedings},
        proceedings_a={BROADNETS},
        year={2019},
        month={1},
        keywords={Statistical modelling Temperature variation 28 nm FDSOI technology},
        doi={10.1007/978-3-030-05195-2_28}
    }
    
  • Abdelgader Abdalla
    Isiaka Alimi
    Manuel González
    Issa Elfergani
    Jonathan Rodriguez
    Year: 2019
    Fast Statistical Modelling of Temperature Variation on 28 nm FDSOI Technology
    BROADNETS
    Springer
    DOI: 10.1007/978-3-030-05195-2_28
Abdelgader Abdalla1,*, Isiaka Alimi1,*, Manuel González2,*, Issa Elfergani1,*, Jonathan Rodriguez1,*
  • 1: Universidade de Aveiro
  • 2: Evotel Informatica SL
*Contact email: a.m.abdalla@av.it.pt, iaalimi@ua.pt, m.gonzalez@evotel-info.com, i.t.e.elfergani@av.it.pt, jonathan@av.it.pt

Abstract

It is well known that the 28 nm fully depleted Silicon-On Insulator (FDSOI) node has a temperature effect due to the inherent pyroelectric and piezoelectric properties. In this paper, we introduce a spatial interpolation Lookup table (LUT) model considering temperature dependence of nanometer CMOS transistors. The novel methodology is used to build the bias current and capacitance LUTs for MOS transistor circuits under extensive variety of temperature values, evaluated under transient analysis. This innovative LUTs model significantly reduce the simulation runtime with sufficient accuracy using adaptive multivariate precomputed Barycentric relational interpolation for the appraisal temperature effects of 28 nm FDSOI node.