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Monte Carlo Analysis<br />

Model-Based Approximations Example<br />

Lower Pr. Value Upper CV(%) #Runs Speedup<br />

Tail / Complementary<br />

------------------------------------------------------------------------------<br />

8.86e-05 9.60e-05/1.00e+00 1.03e-04 7.69 3530 1.9e+03<br />

Additionally, the quantile estimator returns a value of 1.74980×10 9 , which is very close to the<br />

value specified in the MCPROB extract statement. The speedup of the ISMC method over the<br />

standard Monte Carlo method is modest, but still very interesting. The standard Monte Carlo<br />

method would require 6.7 million runs to reach the same precision.<br />

Model-Based Approximations Example<br />

Netlist file: monte_carlo_ssd.cir<br />

This example centers around an 8-bit CMOS ripple carry adder, which is able to add to 7-bit<br />

binary numbers in parallel. The adder is constructed from a chain of 7 cascaded one-bit adder<br />

stages, with each stage connected to the next via a carry-link.<br />

The maximum operating frequency of such an adder is limited by the time it takes for the carry<br />

signal to propagate (ripple) through the chain, from the far-right stage to the sum6 and sum7<br />

outputs on the left. Given the circuit topology, this propagation delay depends on:<br />

• The design parameters (geometries of transistors in the carry path).<br />

• The statistical variations in transistor parameters due to manufacturing tolerances.<br />

• Environmental temperature.<br />

You, the designer, can choose the values of the design parameters. Temperature and some<br />

manufacturing process parameters may be controllable, but more often are not “designable.”<br />

The objectives for the 8-bit adder in this example are:<br />

• To simulate the fluctuation of the maximum operation speed due to manufacturing<br />

variations and as a function of temperature.<br />

• To predict the likely manufacturing yield with respect to a <strong>user</strong>-specified lower limit on<br />

the operating speed.<br />

• To compare the standard Monte Carlo method and the supersaturated design (SSD)<br />

approach.<br />

Approximation of the Parametric Yield<br />

Here, we calculate an approximation of the probability that a given circuit fails to satisfy a set<br />

performance specification. In the example, this value is obtained using the LBOUND and<br />

UBOUND arguments on the .EXTRACT command:<br />

.EXTRACT TRAN LABEL=OPFREQ (1/MAX(EXTRACT(DELAY6), EXTRACT(DELAY7)))<br />

+ LBOUND=280Meg<br />

532<br />

Eldo® User's Manual, 15.3

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