Abstract: Techniques for use in integrated circuit design systems for extracting noise threshold data for selected cells. For example, a method comprises the following steps. A cell is selected from one or more cells in a given collection of standardized cells. Each of the one or more cells represents one or more functional circuit design blocks that are usable as part of a design of an integrated circuit. A noise signal is generated or selected. The noise signal is applied to an input node of the selected cell. Noise threshold data is identified using a noise analysis module, for a given set of process, voltage and temperature variations, for an output node of the selected cell based on the noise signal applied to the input node of the selected cell.

Abstract: Techniques for use in integrated circuit design systems for extracting noise threshold data for selected cells. For example, a method comprises the following steps. A cell is selected from one or more cells in a given collection of standardized cells. Each of the one or more cells represents one or more functional circuit design blocks that are usable as part of a design of an integrated circuit. A noise signal is generated or selected. The noise signal is applied to an input node of the selected cell. Noise threshold data is identified using a noise analysis module, for a given set of process, voltage and temperature variations, for an output node of the selected cell based on the noise signal applied to the input node of the selected cell.

Abstract: Methods, systems and processor-readable media for automatic self-tracking of input deliverables for noise characterization. A noise characterization run to generate a noise model thereof can be automatically initiated. The noise model can be delivered into a repository in response to completing the noise characterization run and generating the noise model. Data associated with the noise model can be tracked for subsequent analysis including checking completeness and a correctness of the noise model delivered into the repository, The data associated with the noise model can then be rendered for the subsequent analysis. Data associated with the noise model can include, for example, information regarding pending tasks, assignment information, and data contained in a noise database.