Automated circuit and layout generation is disclosed. Various embodiments may include a computer system and/or method for generating a circuit layout comprising specifying a circuit schematic to be converted to a circuit layout, receiving a layout script associated with the circuit schematic, the layout script configured to position a plurality of layout instances generated from the circuit schematic, converting the circuit schematic into the plurality of layout instances; and positioning the plurality of layout instances based on the layout script to produce the circuit layout. A circuit may be produced by fabricating a circuit using the layout.

A processing method for applying an analog dynamic circuit to a digital testing tool includes the following steps. In a step (a), a transistor-level analog dynamic circuit is provided. In a step (b), plural equivalent models are designed according to operations of plural transistors in the transistor-level analog dynamic circuit. In a step (c), a substitution operation is performed to substitute the equivalent models for dynamic logic elements in the transistor-level analog dynamic circuit. Consequently, a gate-level substitution circuit is produced. In a step (d), the gate-level substitution circuit is imported into a digital testing tool. Consequently, a test pattern is generated. In a step (e), the transistor-level analog dynamic circuit is tested according to the test pattern.

A processing method for applying an analog dynamic circuit to a digital testing tool includes the following steps. In a step (a), a transistor-level analog dynamic circuit is provided. In a step (b), plural equivalent models are designed according to operations of plural transistors in the transistor-level analog dynamic circuit. In a step (c), a substitution operation is performed to substitute the equivalent models for dynamic logic elements in the transistor-level analog dynamic circuit. Consequently, a gate-level substitution circuit is produced. In a step (d), the gate-level substitution circuit is imported into a digital testing tool. Consequently, a test pattern is generated. In a step (e), the transistor-level analog dynamic circuit is tested according to the test pattern.

A system to facilitate communication of a critical signal between functional circuitries of a system-on-chip utilizes a dynamic pattern to securely communicate the critical signal. The system includes selection and comparison circuits. The selection circuit is configured to select and output a set of dynamic pattern bits or a set of fixed reference bits, based on a logic state of the critical signal that is received from one functional circuitry. The comparison circuit is configured to output an output signal based on the set of dynamic pattern bits, and a set of intermediate bits that is derived from the set of dynamic pattern bits or the set of fixed reference bits. The output signal is provided to the other functional circuitry when a logic state of the output signal matches the logic state of the critical signal, thereby securely communicating the critical signal to the other functional circuitry.

A system to facilitate communication of a critical signal between functional circuitries of a system-on-chip utilizes a dynamic pattern to securely communicate the critical signal. The system includes selection and comparison circuits. The selection circuit is configured to select and output a set of dynamic pattern bits or a set of fixed reference bits, based on a logic state of the critical signal that is received from one functional circuitry. The comparison circuit is configured to output an output signal based on the set of dynamic pattern bits, and a set of intermediate bits that is derived from the set of dynamic pattern bits or the set of fixed reference bits. The output signal is provided to the other functional circuitry when a logic state of the output signal matches the logic state of the critical signal, thereby securely communicating the critical signal to the other functional circuitry.

In modern VLSI technology, often, stacked arrays of smaller sized MOSFETs are used to achieve the desired width and length of a design MOSFET. In analog defect simulation, each physical transistor can contribute to the circuit's defect universe and this can directly lead to tremendous increase in defect simulation time. Here we propose a method of finding equivalent defects in the context of stacked MOSFET arrays that can lead to significant reduction in defect simulation effort and yet provide accurate defect coverage results.

A technique for designing circuits including receiving a data object representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit.

A technique for designing circuits including receiving a data object representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit.

A technique for designing circuits including receiving a data object representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit.

A technique for designing circuits including receiving a data object representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit.