Method

Lets you select one of the following methods to run Monte Carlo sampling:

• Standard Monte Carlo
• FMC Worst Samples
• Sensitivity Accuracy
• Yield Verification - Autostop

In addition, you can also select the following options provided that the corresponding environment variables are set to t.

• Confidence Interval - Autostop
  showMethodCIAutoStop
• K-Sigma Corners
  showMethodKSigmaCorners
• Yield Verification - Reorder Samples
  showMethodYieldVerificationReorderSamples
• Worst Samples
  showMethodWorstSamples
• Scaled-Sigma Sampling
  showMethodScaledSigmaSampling
• Worst Case Distance
  showMethodWorstCaseDistance

Variation

Selects one of the following statistical variation options:

• Mismatch: For per-instance statistical variations.
• Process: For process statistical variations.
• All: For both process and per-instance statistical variations.

Max Points

Specifies the maximum number of sample points to simulate while trying to build an accurate model. If a model cannot be constructed even after simulating the maximum number of points, the Monte Carlo run is stopped.

Number of Points

Specifies the number of sample points to simulate.

You can use scientific notation to specify values in this field.

For example, you can use either 1e3 or 1k to specify 1000 points.

Max Scaling Factor

Specifies the maximum scaling factor to be used for the Scaled-Sigma Sampling method. You can specify a value between 3–7. By default, this field is set to 7, which means that seven child histories using seven different scaling factors will be generated.

Environment variable: enableMaxScalingFactorForSSS

Total Samples

Specifies the maximum number of points to be simulated for FMC Worst Sample method.

Target Yield

Specifies the yield value that you want to achieve for your design. It can be expressed either as a sigma value or as a percentage value.

The target yield can be any value between 3–6 sigma or 99.865%.

Tail Samples

Specifies the number of tail samples.

If you do not specify the number of tail samples, it is calculated automatically using Total Samples and Target Yield values.

Budget

Specifies the number of simulations to be run for FMC method.

For example, 500, which indicates that no more than 500 points are simulated for the FMC method.

This is an optional field.

Initial Points

Specifies the number of initial points based on which metrics, such as mean and standard deviations are calculated and annotated in histograms.

Specifying higher number of initial points improves the accuracy of the mean and standard deviation measurements.

In FMC method, an initial model is built after the initial sampling group finishes. The initial model can be built with additional data points by increasing the number of initial points.

This is an optional field.

Points per Job

Lets you control the grouping of Monte Carlo points (Spectre montecarlo numruns):

• Group automatically: Select this option if you want the tool to determine the grouping and to automatically set the numruns value based on the number of Max Jobs.
• Max: Lets you specify the number of Monte Carlo points. For example, if you specify 1, a separate Spectre netlist is created with numruns=1 for each Monte Carlo point.

Create Statistical Corners

Lets you create statistical corners that can further be used in optimizing and debugging the design.

This option is available only for Scaled-Sigma Sampling and Worst-Case Distance methods.

Save Waveforms (Simulation Data)

Saves output data (psf files) for every Monte Carlo iteration so that you can perform post-processing operations, such as plotting, printing, annotation, and re-evaluation on individual iterations.

This option is not available for Scaled-Sigma Sampling and Worst-Case Distance methods.

Distribution Type and Scaling

Lets you specify the distribution types for Monte Carlo process and mismatch variations.

Environment variable: showOptionDistributionTypeAndScaling

Process

Specifies the distribution type for Monte Carlo process variations. The valid values are Gaussian and Uniform.

• For Gaussian, specify the value by which you want to scale the standard deviation of process variation parameters in the Std Scale field.
• For Uniform, specify the n-scale value for process variation parameters in the N Scale field.

Mismatch

Specifies the distribution type for Monte Carlo mismatch variations. The valid values are Gaussian and Uniform.

• For Gaussian, specify the value by which you want to scale the standard deviation of mismatch variation parameters in the Std Scale field.
• For Uniform, specify the n-scale value for mismatch variation parameters in the N Scale field.

Probability

Specifies the probability value in percentage.

Probability values closer to 100% will require more simulations before the yield estimate can be determined to be lower or higher than the target. Smaller probability values require fewer simulations before autostop is triggered.

The default probability is 95%.

Environment variable: yieldProbability

Stop Percentage

Specifies the percentage value of stopping criteria for the Confidence Interval - Autostop method.

Environment variable: confidenceAutoStopPercentage

Confidence Level

Determines the confidence interval for the output standard deviation considered by the stopping criteria.

Environment variables: confidenceAutoStopLevel and showConfidenceAutoStopLevel.

Confidence Sigma

Determines the range of output variations considered by the stopping criteria.

Environment variables: confidenceAutoStopSigma and showConfidenceAutoStopSigma.

Sampling Method

Selects one of the following statistical sampling methods:

• Random
• Latin Hypercube
• Low-Discrepancy Sequence

For more information, see Statistical Sampling Methods.

Seed

Specifies a seed for the Monte Carlo analysis. You can reproduce a previous experiment by specifying the same seed. If you do not specify a seed, the default value 12345 is used.

First Point

Specifies a starting run number. The first point specifies the run that Monte Carlo begins with. By specifying this number, you can reproduce a particular run or sequence of runs from a previous experiment (for example, to examine an earlier case in more detail).

Netlist Options

Specifies additional analysis options that you want to generate in the netlist.

You cannot specify the numruns, firstrun, and seed options in this field.

For example: "nullmfactorcorrelation=yes"

Specify Instances/Devices

Click to specify the sensitive instances and devices you want to either include or exclude for applying mismatch variations.

For more information, see Specifying Instances for Monte Carlo Mismatch and Process Variation in Virtuoso ADE Explorer User Guide.

Specify Mismatch ID

Click to specify the mismatch ID.

For more information see, Introduction to Mismatch ID in Virtuoso ADE Assembler User Guide.

Specify Design Variables

Click to specify design variables that you want to vary with statistical distribution in Monte Carlo analysis.

For more information see, Varying Design Variables with Statistical Distribution in Virtuoso ADE Assembler User Guide.

Worst Case Distance Options

Provides additional options that are related to the Worst-Case Distance method.

Use Monte Carlo History

Selects a reference Monte Carlo run history from the list of available histories. It is essential that the simulation data of the selected history contains the process and mismatch data. If any one of these data is not available, an error message is displayed.

The Use Monte Carlo History option is enabled if you have already run a Monte Carlo simulation. You can use the process and mismatch data from the history of that run.

Automatic Number of Monte Carlo Points

Enables the automatic selection of number of Monte Carlo points. When you select this check box, the Number of Points and Automatic Variable Reduction fields become unavailable.

To manually specify the number of Monte Carlo points to be simulated, disable this check box.

Automatic Variable Reduction

Reduces the set of statistical variables by eliminating insignificant variables—variables that have no variation or have no influence on the WCD point. Insignificant variables bring noise and require more simulations for sensitivity analysis. Therefore, it is recommended to enable variable reduction.

By default, the Automatic Variable Reduction check box is disabled. To enable this check box, first deselect the Automatic Number of Monte Carlo Points check box.

Skip Specs With MC Yield <

Ignores the specifications for which Monte Carlo yield is less than a specified percentage. The default value of this field is 3 sigma; therefore, specifications for which the Monte Carlo yield is less than 99.86% are ignored.

If you want to run high yield estimation on all the specifications, deselect the Skip Specs With MC Yield < check box.

Max Number of Iterations

Specifies the maximum number of iterations to be run for each specification. The default number of iterations is 10.