Fast and Accurate Circuit Design Automation through Hierarchical Model Switching

In
computer-aided biological design, the trifecta of characterized
part libraries, accurate models and optimal design parameters is crucial
for producing reliable designs. As the number of parts and model complexity
increase, however, it becomes exponentially more difficult for any
optimization method to search the solution space, hence creating a
trade-off that hampers efficient design. To address this issue, we
present a hierarchical computer-aided design architecture that uses
a two-step approach for biological design. First, a simple model of
low computational complexity is used to predict circuit behavior and
assess candidate circuit branches through branch-and-bound methods.
Then, a complex, nonlinear circuit model is used for a fine-grained
search of the reduced solution space, thus achieving more accurate
results. Evaluation with a benchmark of 11 circuits and a library
of 102 experimental designs with known characterization parameters
demonstrates a speed-up of 3 orders of magnitude when compared to
other design methods that provide optimality guarantees.