Thursday 7 April 2016

POCV

Advanced on-chip variation (AOCV) analysis reduces unnecessary pessimism by taking the design methodology and fabrication process variation into account. AOCV determines derating factors based on metrics of path logic depth and the physical distance traversed by a particular path. A longer path that has more gates tends to have less total variation because the random variations from gate to gate tend to cancel each other out. A path that spans a larger physical distance across the chip tends to have larger systematic variations. AOCV is less pessimistic than a traditional OCV analysis, which relies on constant derating factors that do not take path-specific metrics into account.

The AOCV analysis determines path-depth and location-based bounding box metrics to calculate a context-specific AOCV derating factor to apply to a path, replacing the use of a constant derating factor.

AOCV analysis works with all other PrimeTime features and affects all reporting commands. This solution works in both the Standard Delay Format (SDF)-based and the delay calculation based flows.



PrimeTime ADV parametric on-chip variation (POCV) models the delay of an instance as a function of a variable that is specific to the instance. That is, the instance delay is parameterized as a function of the unique delay variable for the instance.


POCV uses a statistical approach, but it doesn’t do a full SSTA analysis. Instead, it calculates delay variation by modeling the intrinsic cell delay and load parasitics (line resistance, line capacitance, and load capacitance) to determine both the mean and “sigma” (variation) of a logic stage. The cell delay can be further broken into an n-channel component and a p-channel component. They then assume that all the cells along a path have the same mean and sigma.



This means that a given path doesn’t have to be analyzed stage-by-stage; the number of stages can be counted, with the basic stage delay mean and sigma then used to calculate the path delay and accumulated variation. They claim that this keeps the run times down to just over what standard STA tools require, far faster than SSTA. They also claim speedier execution and greater accuracy than AOCV, and no derating tables are required.


POCV) is a technique that has been proposed as a means of reducing pessimism further by taking elements of SSTA and implementing them in a way that is less compute-intensive.
POCV provides the following:

•Statistical single-parameter derating for random variations

•Single input format and characterization source for both AOCV and POCV table data

•Nonstatistical timing reports

•Limited statistical reporting (mean, sigma) for timing paths

•Compatibility with existing PrimeTime functionality, except PrimeTime VX

Compared to AOCV, POCV provides


•Reduced pessimism gap between graph-based analysis and path-based analysis

•Less overhead for incremental timing analysis

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