Optimization method of integrated circuit process parameter models

Optimization method of integrated circuit process parameter models

  • CN 101,840,451 B
  • Filed: 04/21/2010
  • Issued: 05/28/2014
  • Est. Priority Date: 04/21/2010
  • Status: Active Grant
First Claim
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1. an optimization method for integrated circuit process parameter models, is characterized in that this optimization method comprises the following steps:

  • 1. according to design needs, from existing integrated circuit process parameter models database, select several process parameter models as object to be optimized, and each parameter grouping is shown, observe the distribution situation of parameter, understand the general trend of technique change;

    Whether the number that 2. judges above model parameter is identical, if different, take the maximum model of number of parameters as benchmark, uses the default parameter value of the type model to supply parameter;

    If when number of parameters is identical, skip this step;

    3. according to the type of design circuit and feature, select suitable optimization method to be optimized parameter model, these optimization methods have;

    model parameter arithmetic mean optimization, model parameter square mean optimization or model parameter median optimization, whether concrete optimization method or the optimum results selected suit the requirements, and are judged and are verified by emulation;

    4., after Model Parameter Optimization finishes, generate and derive the process parameter models after optimizing;

    Or optimum results is shown to output together with other parameters, intuitively observe;

    5. use this Optimized model to design circuit and compare with the process modeling in the scope of choosing, judging whether its design result can adapt to the variation of technological parameter, if the designing requirement of energy Adaptive change coincidence circuit stops this process;

    If do not met, return to the 3rd step and reselect optimization method and again model is optimized, until meet the requirements.

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