System and method of simulating aging in device circuits

1. A method of simulating device aging based on a digital waveform representative of a workload of an electronic device, the method comprising:

grouping contiguous sets of cycles into a plurality of segments, each set of cycles corresponding to a segment, wherein each segment has values for a combination of segment parameters that are unique from each of the other segments and a start point that is separated from a start point of an adjacent segment by a pre-defined distance criterion; and

creating scenarios comprising collections of segments based on their distances in an objective space, wherein at least one axis of the objective space represents an amount of degradation due to aging,

wherein grouping the contiguous sets of cycles into the plurality of segments comprises, for each segment:

sampling one or more sequential cycles of the workload,

generating the segment based on the sampled contiguous cycles having a period exceeding a threshold period, and

determining the values for the combination of segment parameters; and

applying an aging model to the segments to simulate the aging for the device based on the workload, wherein the segments are a representation of the digital waveform.

2. The method of claim 1 , wherein the pre-defined distance criterion is based on a number of cycles in a segment having a period exceeding the threshold period, and wherein the combination of segment parameters comprises a duty factor (DF), a frequency (f), and a time duration (Δt) for each segment.

3. The method of claim 1 , further comprising clustering contiguous segments into a set of scenarios that correspond to aging models based on start times of the scenarios.

4. The method of claim 3 , wherein, when one of the scenarios repeats itself a number of times consecutively, one of the aging models is applied to the repeating scenario to calculate aging for the device based on a pre-defined relationship between degradation of the device and the workload of the device characterized by values for a combination of scenario parameters, wherein the combination of scenario parameters comprises a scenario duty factor (DF), a scenario frequency (f), and a scenario time duration (Δt) for each scenario and wherein the values for the combination of scenario parameters are determined based on an effective DF for the scenario.

5. The method of claim 4 , wherein the pre-defined relationship includes a linear relationship between the degradation of the device and the workload of the device and is characterized by one of the segment DF and the segment f, and each of the segment DF and the segment f is representative of the digital waveform segment.

6. The method of claim 3 , wherein a number of different scenarios is repeated at least once over the duration of the digital waveform, and wherein the degradation of each of the different scenarios is stored in a first lookup table relative to an initial condition of the degradation.

7. The method of claim 1 , wherein a duty factor (DF), a frequency (f), and a time duration (Δt) of the combination of segment parameters for the segment are averaged for the sampled cycles of the digital waveform that form the segment.

8. The method of claim 1 , wherein applying the aging model comprises accessing look up tables and using the values for the combinations of segment parameter values to simulate short-term and long-term aging for the device.

9. The method of claim 1 , wherein grouping the contiguous sets of cycles into the plurality of segments further comprises, for each segment:

determining that the period of the sampled sequential cycles does not exceed the threshold period;

aggregating one or more additional sequential cycles with the sampled sequential cycles based on the determination that the period does not exceed the threshold period;

determining that the period of the aggregated additional sequential cycles with the sampled sequential cycles exceeds the threshold period; and

generating the segment based on the sampled contiguous cycles and the additional sequential cycles.

10. The method of claim 1 , further comprising evaluating the degradation of the device based on a set of aging models for a set of scenarios occurring in an arbitrary sequence over a duration of the digital waveform.

11. The method of claim 1 , wherein another one of the at least one axis of the objective space represents energy, maximal power, footprint, or throughput latency.

12. A system for simulating device aging based on a digital waveform representative of a workload of an electronic device, the system comprising:

one or more processors configured to execute instructions; and

a non-transitory, computer readable medium configured to store the instructions that, when executed by the processor, cause the one or more processors to:

group contiguous sets of cycles into a plurality of segments, each set of cycles corresponding to a segment, wherein each segment has values for a combination of segment parameters that are unique from each of the other segments and a start point that is separated from a start point of an adjacent segment by a pre-defined distance criterion; and

create scenarios comprising collections of segments based on their distances in an objective space, wherein at least one axis of the objective space represents an amount of degradation due to aging,

wherein the instructions that cause the one or more processors to group the contiguous sets of cycles into the plurality of segments further cause the one or more processors to, for each segment:

sample one or more sequential cycles of the workload,

generate the segment based on the sampled contiguous cycles having a period exceeding a threshold period, and

determine the values for the combination of segment parameters; and

apply an aging model to the segments to simulate the aging for the device based on the workload, wherein the segments are a representation of the digital waveform.

13. The system of claim 12 , wherein another one of the at least one axis of the objective space represents energy, maximal power, footprint, or throughput latency.