Statistical design with importance sampling reuse
First Claim
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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Abstract
A mechanism is provided for reusing importance sampling for efficient cell failure rate estimation of process variations and other design considerations. First, the mechanism performs a search across circuit parameters to determine failures with respect to a set of performance variables. For a single failure region, the initial search may be a uniform sampling of the parameter space. Mixture importance sampling (MIS) efficiently may estimate the single failure region. The mechanism then finds a center of gravity for each metric and finds importance samples. Then, for each new origin corresponding to a process variation or other design consideration, the mechanism finds a suitable projection and recomputes new importance sampling (IS) ratios.
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Citations
17 Claims
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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:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer program product comprising a non-transitory computer readable storage medium being configured with a computer readable program stored therein, wherein the computer readable program, when executed on at least one processor of a computing device, causes the at least one processor to implement an apparatus for determining failure rate of a device using importance sampling reuse, wherein the computer readable program causes the computing device to:
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perform a distribution sampling over a random sample space for a performance metric for a 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; determine an importance sampling weight function with respect to the origin; determine 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; apply the new importance sampling weight function to the distribution set of samples to form a weighted set of samples; determine 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. - View Dependent Claims (9, 10, 11, 12)
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13. An apparatus, comprising:
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at least one processor; and at least one memory coupled to the at least one processor, wherein the at least one memory comprises instructions which, when executed by the at least one processor, cause the at least one processor to implement an apparatus for determining failure rate of a device using importance sampling reuse, wherein the instructions cause the at least one processor to; perform a distribution sampling over a random sample space for a performance metric for a 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; determine an importance sampling weight function with respect to the origin; determine 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; apply the new importance sampling weight function to the distribution set of samples to form a weighted set of samples; determine 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. - View Dependent Claims (14, 15, 16, 17)
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Specification