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Statistical design with importance sampling reuse

  • US 10,387,235 B2
  • Filed: 05/23/2016
  • Issued: 08/20/2019
  • Est. Priority Date: 08/20/2010
  • Status: Active Grant
First Claim
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1. A method, in a data processing system comprising at least one processor and at least one memory, the method comprising:

  • configuring the at least one memory with instructions, which are executed by the at least one processor and configure the at least one processor to implement an apparatus for determining failure rate of a device using importance sampling reuse;

    performing, by the instructions executing on the at least one processor, a distribution sampling over a random sample space for a performance metric for the device with respect to an origin to form a distribution set of samples, wherein the origin represents nominal values for device parameters for a given design of the device, wherein the metric is an operational performance value of the device, and wherein the distribution set of samples comprises one or more failing samples;

    determining, by the instructions executing on the at least one processor, an importance sampling weight function with respect to the origin;

    determining, by the instructions executing on the at least one processor, a new importance sampling weight function with respect to a new origin, wherein the new origin represents alternative values for device parameters corresponding to a process variation or design consideration;

    applying, by the instructions executing on the at least one processor, the new importance sampling weight function to the distribution set of samples to form a weighted set of samples;

    determining, by the instructions executing on the at least one processor, a failure rate for the device for the alternative values for the device parameters based on the weighted set of samples;

    repeating selecting a new origin, determining the new importance sampling weight function for the new origin, and determining a failure rate for the device using the distribution set of samples and the new importance sampling weight function for the new origin for a set of process variations; and

    optimizing nominal values for the device parameters with respect to the determined failure rates.

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