  To tackle the complexity of state-of-the-art electronic systems, silicon
foundries continuously shrink the technology nodes and electronic design
automation (EDA) vendors offer hierarchical design flows to decompose systems
into smaller blocks. However, such a staged design methodology consists of
various levels of abstraction, where margins will be accumulated and result in
degradation of the overall design quality. This limits the full use of
capabilities of both the process technology and EDA tools. In this work, a
study of drive granularity of standard cells is performed and an interpolation
method is proposed for drive option expansion within original cell libraries.
These aim to investigate how industrial synthesis tools deal with the drive
strength selection using different granularity sets. In addition, a
fully-automated, multi-objective (MO) EDA digital flow is introduced for power,
performance, area (PPA) optimisation based on drive strength refinement. This
population-based search method better handles the increased difficulty of cell
selection when using larger logic libraries, producing better optimised
solutions than standard tool flow in this case. The achieved experimental
results demonstrate how the improved drive granularity cells overall enhance
the quality of designs and how a significant improvement in trading off PPA is
achieved by the MOEDA flow.
