Abstract: Methods and systems are disclosed related to region based device bypass in circuit simulation. In one embodiment, a computer implemented method of performing region based device bypass in circuit simulation includes receiving a subcircuit for simulation, where the subcircuit includes a plurality of devices, and determining node tolerance of the plurality of devices. The computer implemented method further comprises for each device in the plurality of devices, determining whether the device has entered into a bypass region using the node tolerance of the plurality of devices, performing model evaluation in response to the device has not entered the bypass region, and skipping model evaluation in response to the device has entered the bypass region.

Abstract: Methods and systems are disclosed related to dynamic load balancing in circuit simulation. In one embodiment, a computer implemented method of performing dynamic load balancing in simulating a circuit includes identifying a plurality of simulation tasks to be performed, determining estimated processing durations corresponding to performance of the plurality of simulation tasks, distributing the plurality of simulation tasks to a plurality of processors according to the estimated processing duration of each simulation task, and performing the plurality of simulation tasks at the plurality of processors in parallel.

Abstract: Methods and systems are disclosed related to multi-rate parallel circuit simulation. In one embodiment, a computer implemented method of partitioning the circuit into a plurality of partitions, wherein each partition is represented by a set of linear differential equations, determining a simulation time step for each partition of the plurality of partitions, grouping the plurality of partitions into multiple groups, wherein each group includes one or more partitions having simulation time steps within a predefined range of each other, and solving the multiple groups with their corresponding simulation time steps in parallel.

Abstract: Apparatuses and methods for measuring flicker noise are disclosed. In one embodiment, a noise measurement system may include a first circuit path configured to drive a first terminal of a device under test (DUT) in the noise measurement system, a charging circuit path configured to charge the first terminal of the DUT in a setup phase, and logic configured to charge the first terminal of the DUT to a predetermined voltage using the first circuit path and the charging circuit path in the setup phase.

Abstract: Apparatuses and methods for measuring flicker noise are disclosed. In one embodiment, a noise measurement system may include a first circuit path configured to drive a first terminal of a device under test (DUT) in the noise measurement system, an amplification circuit configured to amplify an output signal of the DUT, a second circuit path configured to drive a second terminal of the DUT, a third circuit path configured to couple a third terminal of the DUT to a circuit ground, and a decoupling circuit configured to decouple the DUT and the amplification circuit, logic configured to detect output signal characteristics of the DUT, logic configured to adjust input impedance of the amplification circuit based on the output signal characteristics of the DUT, and logic configured to measure a flicker noise of the DUT using the amplification circuit with adjusted input impedance.

Abstract: Method and system are disclosed for repetitive circuit simulation. In one embodiment, a computer implemented method for performing multiple simulations of a circuit includes providing descriptions of connectivity, instants, signal activities, and statistical parameters of the circuit, parsing the circuit in accordance with the descriptions of connectivity, instants, signal activities, and statistical parameters of the circuit to form one or more circuit partitions, performing a first pass simulation of the one or more circuit partitions in accordance with a set of stimuli to generate a history of the first pass simulation, and performing subsequent simulation of the one or more circuit partitions using the history of the first pass simulation.

Abstract: Method and system are disclosed for statistical circuit simulation. In one embodiment, a computer implemented method for statistical circuit simulation includes providing descriptions of a circuit for simulation, wherein the descriptions include variations of statistical parameters of the circuit, partitioning the circuit into groups of netlists according to variations of statistical parameters of the circuit, simulating the groups of netlists using a plurality of processors in parallel to generate a plurality of output data files, and storing the plurality of output data files in a memory. The method of partitioning the circuit into groups of netlists includes forming the groups of netlists to be simulated in a single instruction multiple data environment, and forming the groups of netlists according to proximity of variations of statistical parameters of the circuit.

Abstract: Method and system are disclosed for simulating a circuit. The method includes representing a circuit using a matrix that represents a set of linear equations to be solved, identifying a delta matrix, which is a subset of the matrix that changed states from a previous time step to a current time step, computing an update of the delta matrix using a matrix decomposition approach, generating a current state of the matrix using a previous state of the matrix and the update of the delta matrix, and storing the current state of the matrix in a memory device.

Abstract: Model evaluation and circuit simulation/verification is performed in a graphical processing unit (GPU). A multitude of first texture data corresponding to size parameters of devices are stored. A multitude of second texture data corresponding to instance parameters of the devices are stored. A multitude of third texture data corresponding to models of the devices are stored. A multitude of fourth texture data corresponding to terminal voltages received by the device are stored. A multitude of links linking each device instance to an associated device model, size parameters and instance parameters are stored. A quad having a size defined by the multitude of links is drawn by the quad in the GPU. Each thread in the quad is assigned to a different one of the multitude of links. The computations are carried out in each thread using the linked data to perform the model evaluation.