Cadence Design Systems, Inc.
Constrained metric optimization of a system on chip

Abstract:

A method including receiving a first configuration of a device validated against a design constraint, is provided. A configuration includes stimuli controls and stimuli parameters used as inputs in a device model. The method includes determining a quality of the first configuration based on an estimation of an output parameter including a desired behavior of the device, simulating the device in the first configuration when the first configuration quality overcomes a threshold, and requesting a second configuration of the device when the quality of the first configuration is below the selected threshold. The method also includes obtaining a regression based on multiple, high quality configurations to determine, for the device, a distribution of output parameter values and comparing the distribution of output parameter values with a baseline of a random regression to adjust the machine learning engine according to a target range of output parameter values.