Abstract: The invention discloses a “Quasi-Monte Carlo” method originally intended for computational finance applications and applies said method to statistical circuit analysis. In doing so, it provides a means to efficiently and effectively detect and/or predict relatively rare failures or events to a wide range of industrial circuits and systems. The approach to the invention involves the representation of circuit metrics as a large multi-dimensional integral. This invention estimates such statistical circuit metric integrals by sampling the statistical variable space using a so-called “low-discrepancy sequence.” This is similar to the Monte Carlo method, the main difference being the method of sampling the variable space. Compared with standard Monte Carlo simulation, this technique, “Quasi-Monte Carlo Methods,” gives similarly reliable estimates of the result, but requiring many fewer samples of the circuit or system being evaluated.

Abstract: The invention provides methods for enhancing circuit reliability under statistical process variation. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. To combat this, the invention discloses the method called “Statistical Blockade,” a Monte Carlo-type technique that allows the efficient filtering—blocking—of unwanted samples insufficiently rare in the tail distributions of interest, with speedups of 10-100×. Additionally, the core Statistical Blockade technique is further extended in a “recursive” or “bootstrap” formulation to create even greater efficiencies under a much wider variety of circuit performance metrics, in particular two-sided metrics such a Data Retention Voltage (DRV) which prior Monte Carlo techniques could not handle.

Abstract: Method and system for evaluating design costs of an integrated circuit are disclosed. The method includes choosing a design point for evaluation, dividing circuit specifications of the design point into at least two groups comprising a first group of specifications and a second group of specifications, computing a first set of design costs for the first group of specifications, estimating a second set of design costs for the second group of specifications using a predetermined set of reference costs, and determining a design cost of the design point using the first set of design costs and the second set of design costs.

Abstract: A method and system for modeling uncertainties in integrated circuits, systems and fabrication processes may include defining interval values for each uncertain component or parameter in a circuit or system. The method may also include replacing scalar operations with interval operations in an algorithm and discontinuing interval operations in the algorithm in response to a predetermined condition. The method may also include generating a plurality of scalar samples from a plurality of intervals and determine a distribution of each uncertain component or parameter from the scalar samples of the intervals.

Abstract: Method and system for evaluating design costs of an integrated circuit are disclosed. The method includes choosing a design point for evaluation, dividing circuit specifications of the design point into at least two groups comprising a first group of specifications and a second group of specifications, computing a first set of design costs for the first group of specifications, estimating a second set of design costs for the second group of specifications using a predetermined set of reference costs, and determining a design cost of the design point using the first set of design costs and the second set of design costs.