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Monte Carlo Analysis<br />

Local and Global Variations<br />

We also plot the regression line Y = aX + b which relates the dependent variable Y=IR2 to<br />

X=IR1. It is a well known result that the slope of this line is given by the formula:<br />

and the intercept is .<br />

Local and Global Variations<br />

In statistical models for transistor level simulation, there are two types of variability in device<br />

properties:<br />

• Inter-die (between chips) variations or global variations.<br />

Typical examples of statistical parameters with global tolerances are oxide thickness or<br />

channel length reduction.<br />

• Intra-die (within chip) variations are local variations that affect transistors individually.<br />

A typical example of statistical parameters with local tolerances are the transistor<br />

threshold voltages.<br />

Inter-die variability consists of the accumulated fluctuations of material characteristics between<br />

lot-to-lot, wafer-to-wafer and die-to-die (chip-to-chip). However, once the wafers have been cut<br />

into individual chips there is no longer a traceable correlation among them. Therefore, lot-to-lot,<br />

wafer-to-wafer and die-to-die variations are pooled together into one term: the inter-die<br />

variability. This variability equally affects all devices on a given chip. In simulation terms, this<br />

means that all devices of a certain type use the same statistical model.<br />

Local variations lead to an increase in the number of statistical parameters relative to the<br />

number of transistors in a circuit. In a circuit with 100 transistors, there will be one global<br />

threshold voltage V th, glob that affects all transistors equally and 100 local threshold voltages<br />

V ith, loc for i = 1, ..., 100 that affect each transistor individually and independently from others.<br />

Therefore, you can consider that the effective threshold voltage for the i-th device is the sum:<br />

According to these definitions, global statistical parameters are not correlated with local<br />

statistical parameters, and local statistical parameters are not correlated with each other.<br />

Example<br />

In this example, LOT and DEV variations are defined on the length and width of the resistor<br />

model. By definition, there are two independent random variables associated to the inter-die<br />

442<br />

Eldo® User's Manual, 15.3

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