Abstract: A method is provided for pre-tabulating sub-networks that (1) generates a sub-network that performs a function, (2) generates a parameter based on this function, and (3) stores the sub-network in a storage structure based on the generated parameter. In some embodiments, the generated sub-network has several circuit elements or performs a set of two or more functions. Some embodiments provide a method for producing a circuit description of a design that (1) selects a candidate sub-network from the design, (2) identifies an output function performed by the sub-network, (3) based on the identified output function, identifies a replacement sub-network from a storage structure that stores replacement sub-networks, and (4) replaces the selected candidate sub-network with the replacement sub-network in certain conditions. Some embodiments provide a data storage structure that stores a plurality of sub-networks based on parameters derived from the output functions of the sub-networks.

Abstract: Some embodiments of the invention provide a method for pre-tabulating sub-networks. This method (1) generates a sub-network that performs a function, (2) generates a parameter based on this function, and (3) stores the sub-network in a storage structure based on the generated parameter. In some embodiments, the generated sub-network has several circuit elements. Also, in some embodiments, the generated sub-network performs a set of two or more functions. Some embodiments store each generated sub-network in an encoded manner. Some embodiments provide a method for producing a circuit description of a design. This method (1) selects a candidate sub-network from the design, (2) identifies an output function performed by the sub-network, (3) based on the identified output function, identifies a replacement sub-network from a storage structure that stores replacement sub-networks, and (4) replaces the selected candidate sub-network with the identified replacement sub-network in certain conditions.

Abstract: A method and apparatus for performing nickel salicidation is disclosed. The nickel salicide process typically includes: forming a processed substrate including partially fabricated integrated circuit components and a silicon substrate; incorporating nitrogen into the processed substrate; depositing nickel onto the processed substrate; annealing the processed substrate so as to form nickel mono-silicide; removing the unreacted nickel; and performing a series procedures to complete integrated circuit fabrication. This nickel salicide process increases the annealing temperature range for which a continuous, thin nickel mono-silicide layer can be formed on silicon by salicidation. It also delays the onset of agglomeration of nickel mono-silicide thin-films to a higher annealing temperature. Moreover, this nickel salicide process delays the transformation from nickel mono-silicide to higher resistivity nickel di-silicide, to higher annealing temperature.

Abstract: A system for using machine-learning to create a model for performing integrated circuit layout extraction is disclosed. The system of the present invention has two main phases: model creation and model application. The model creation phase comprises creating one or more extraction models using machine-learning techniques. First, a complex extraction problem is decomposed into smaller simpler extraction problems. Then, each smaller extraction problem is then analyzed to identify a set of physical parameters that fully define the smaller extraction problem. Next, models are created using machine learning techniques for all of the smaller simpler extraction problems. The machine learning is performed by first creating training data sets composed of the identified parameters from typical examples of the smaller extraction problem and the answers to those example extraction problems as solved using a highly accurate physics-based field solver. The training sets are then used to train the models.