  Modern electronic design automation (EDA) tools can handle the complexity of
state-of-the-art electronic systems by decomposing them into smaller blocks or
cells, introducing different levels of abstraction and staged design flows.
However, throughout each independent-optimised design step, overhead and
inefficiency can accumulate in the resulting overall design. Performing
design-specific optimisation from a more global viewpoint requires more time
due to the larger search space, but has the potential to provide solutions with
improved performance. In this work, a fully-automated, multi-objective (MO) EDA
flow is introduced to address this issue. It specifically tunes drive strength
mapping, preceding physical implementation, through multi-objective
population-based search algorithms. Designs are evaluated with respect to their
power, performance and area (PPA). The proposed approach is aimed at digital
circuit optimisation at the block-level, where it is capable of expanding the
design space and offers a set of trade-off solutions for different
case-specific utilisation. We have applied the proposed MOEDA framework to
ISCAS-85 and EPFL benchmark circuits using a commercial 65nm standard cell
library. The experimental results demonstrate how the MOEDA flow enhances the
solutions initially generated by the standard digital flow, and how
simultaneously a significant improvement in PPA metrics is achieved.
