Name
Abstract | ||
|---|---|---|
Growing circuit complexity and design uncertainty has made it difficult to predict whether large circuits meet target property specifications. To address this, we conservatively approximate the failure probability estimate by defining an interval that bounds this probability. Doing so using an arbitrary sampling distribution requires a learner. Given that the learner's knowledge is imperfect, the interval must first capture its uncertainty. An ensemble of such learners can then be used to compensate for the bias. Lastly, we develop an adaptive sampling scheme to tighten the obtained interval with increased simulation resources, thus controlling the accuracy vs. turn-around-time trade-off. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2593069.2593091 | Design Automation Conference |
Keywords | Field | DocType |
circuit complexity,integrated circuit reliability,mixed analogue-digital integrated circuits,probability,adaptive sampling,approximate property checking,arbitrary sampling distribution,circuit complexity,design uncertainty,failure probability estimate,mixed signal circuits,turn-around-time tradeoff,Analog circuits,Mixed analog digital integrated circuits,Model checking,Sampling methods,Yield estimation | Sampling distribution,Model checking,Analogue electronics,Circuit complexity,Adaptive sampling,Computer science,Electronic engineering,Sampling (statistics),Mixed-signal integrated circuit,Electronic circuit | Conference |
ISSN | Citations | PageRank |
0738-100X | 3 | 0.46 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Parijat Mukherjee | 1 | 9 | 2.07 |
| Chirayu S. Amin | 2 | 136 | 10.12 |
| Peng Li | 3 | 1912 | 152.85 |