| Summary: | Variability has become one of the vital challenges that the
designers of integrated circuits encounter. variability becomes
increasingly important. Imperfect manufacturing process manifest
itself as variations in the design parameters. These variations
and those in the operating environment of VLSI circuits result in
unexpected changes in the timing, power, and reliability of the
circuits. With scaling transistor dimensions, process and
environmental variations become significantly important in the
modern VLSI design. A smaller feature size means that the physical
characteristics of a device are more prone to these
unaccounted-for changes. To achieve a robust design, the random
and systematic fluctuations in the manufacturing process and the
variations in the environmental parameters should be analyzed and
the impact on the parametric yield should be addressed.
This thesis studies the challenges and comprises solutions for
designing robust VLSI systems in the presence of variations.
Initially, to get some insight into the system design under
variability, the parametric yield is examined for a small circuit.
Understanding the impact of variations on the yield at the circuit
level is vital to accurately estimate and optimize the yield at
the system granularity. Motivated by the observations and results,
found at the circuit level, statistical analyses are performed,
and solutions are proposed, at the system level of abstraction, to
reduce the impact of the variations and increase the parametric
yield.
At the circuit level, the impact of the supply and threshold
voltage variations on the parametric yield is discussed. Here, a
design centering methodology is proposed to maximize the
parametric yield and optimize the power-performance trade-off
under variations. In addition, the scaling trend in the yield loss
is studied. Also, some considerations for design centering in the
current and future CMOS technologies are explored.
The investigation, at the circuit level, suggests that the
operating temperature significantly affects the parametric yield.
In addition, the yield is very sensitive to the magnitude of the
variations in supply and threshold voltage. Therefore, the spatial
variations in process and environmental variations make it
necessary to analyze the yield at a higher granularity. Here,
temperature and voltage variations are mapped across the chip to
accurately estimate the yield loss at the system level.
At the system level, initially the impact of process-induced
temperature variations on the power grid design is analyzed. Also,
an efficient verification method is provided that ensures the
robustness of the power grid in the presence of variations. Then,
a statistical analysis of the timing yield is conducted, by taking
into account both the process and environmental variations. By
considering the statistical profile of the temperature and supply
voltage, the process variations are mapped to the delay variations
across a die. This ensures an accurate estimation of the timing
yield. In addition, a method is proposed to accurately estimate
the power yield considering process-induced temperature and supply
voltage variations. This helps check the robustness of the
circuits early in the design process.
Lastly, design solutions are presented to reduce the power
consumption and increase the timing yield under the variations. In
the first solution, a guideline for floorplaning optimization in
the presence of temperature variations is offered. Non-uniformity
in the thermal profiles of integrated circuits is an issue that
impacts the parametric yield and threatens chip reliability.
Therefore, the correlation between the total power consumption and
the temperature variations across a chip is examined. As a result,
floorplanning guidelines are proposed that uses the correlation to
efficiently optimize the chip's total power and takes into account
the thermal uniformity.
The second design solution provides an optimization methodology
for assigning the power supply pads across the chip for maximizing
the timing yield. A mixed-integer nonlinear programming (MINLP)
optimization problem, subject to voltage drop and current
constraint, is efficiently solved to find the optimum number and
location of the pads.
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