Abstract: Systems and methods associated with costs of a selected objective are disclosed. One embodiment of a system may comprise a constraint evaluator that evaluates a value set associated with a plurality of objectives to determine if a non-selected objective has violated at least one constraint. The system may further comprise a cost function configurable to evaluate a cost associated with the value set at a first cost range if the value set violates the at least one constraint associated with the non-selected objective, and to evaluate a cost associated with the value set at a second cost range associated with the selected objective if the value set does not violate the at least one constraint associated with the non-selected objective, such that the second cost range is different from the first cost range.

Abstract: Systems and methods are disclosed for selecting a value set associated with a set of parameters. A genetic algorithm generates at least one generation of speculative chromosomes that represent value set variations of a plurality of value sets. Each generation of speculative chromosomes are assigned a speculative count corresponding to a speculative chromosome generation. Validation is initiated once at least one speculative chromosome has a predetermined speculative count.

Abstract: Systems and methods are provided for selecting a value set associated with a set of parameters. A system is disclosed that includes a real cost function that generates a plurality of real costs corresponding to a plurality of real chromosomes. A real pool maintains the plurality of real chromosomes and associated real costs. An incremental cost function generates a plurality of speculative costs corresponding to a plurality of speculative chromosomes. A speculative pool maintains the plurality of speculative chromosomes and associated speculative costs.

Abstract: Systems and methods are provided for selecting a value set associated with a set of parameters. A real cost function generates a real cost for a first value set associated with a set of parameters. A genetic algorithm generates a second value set that is a variation of the first value set. A cost function approximator determines an approximate cost based on the real cost and a value set variation between the second value set and the first value set.

Abstract: Systems and methods are disclosed for selecting a value set associated with a set of parameters. Real costs are generated for each of a plurality of first value sets represented as a plurality of real chromosomes. Speculative costs are generated for each of a plurality of second value sets represented as a plurality of speculative chromosomes that represent value set variations of the first value sets. At least one subsequent generation of speculative chromosomes is generated until a predetermined validation criteria has been satisfied. Upon achieving the predetermined validation criteria, real costs are generated for at least one speculative chromosome of the plurality of speculative chromosomes.

Abstract: The iterations required for the convergence of a computer-implemented optimization process based on a genetic model are reduced, and the flexibility of the process is increased through mapping multiple characteristics of a system to be optimized to a single gene within a chromosome.

Abstract: Systems and methods are provided that can be utilized to estimate power associated with a circuit design. The estimated power is determined by employing power characterizations associated with dynamic and static power related parameters of a circuit design. The power characterizations can be determined prior to circuit design optimizations, stored and utilized during circuit design optimizations.

Abstract: Systems and methods are provided that can be utilized to estimate power associated with a circuit design. The estimated power is determined by employing power characterizations to determine power consumption associated with non-conventional circuits in the circuit design. The power characterizations can be determined prior to circuit design timing analysis, stored and utilized during circuit design timing analysis. The power estimates associated with the non-conventional circuits can be added to power estimates associated with the conventional circuits of the circuit design to compute a power associated with the circuit design.

Abstract: Systems and methods are provided that can be utilized to estimate power associated with a circuit design. The estimated power is determined by evaluating a functional relationship of estimated power based on calculated transistor gate area. One or more power coefficients can be employed with transistor gate area calculations of a circuit design to compute relative power estimates of one or more circuit design sizing instances.

Abstract: The convergence speed of a computer-implemented genetic optimization process is improved through the correction of child chromosomes containing undesirable gene combinations. Undesirable gene combinations may be identified through application of heuristic techniques, statistical techniques, or a combination of the two.

Abstract: A process for processing a circuit design. One or more critical design paths of the circuit design are determined. These paths may for example be determined relative to timing and/or current utilization. Design elements of the paths may be grouped by type (e.g., FETs, wires). The circuit design may be optimized by processing a reduced set of design elements as determined by the critical paths and grouping. Optimization may include modifying FET design element width, or a routing path of a wire design element, along a critical path of the design, and comparing the new optimization relative to preselected design goals such as timing and power consumption.