TY - JOUR
T1 - Multi-objective Digital Design Optimisation via Improved Drive Granularity Standard Cells
AU - Cao, Linan
AU - Bale, Simon Jonathan
AU - Trefzer, Martin Albrecht
PY - 2021/9/8
Y1 - 2021/9/8
N2 - 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.
AB - 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.
KW - circuits
KW - systems
KW - digital design
KW - electronic design automation EDA
KW - multi-objective optimisation
UR - https://ieeexplore.ieee.org/document/9531341
U2 - 10.1109/TCSI.2021.3109239
DO - 10.1109/TCSI.2021.3109239
M3 - Article
SN - 1549-8328
VL - 68
SP - 4660
EP - 4671
JO - Ieee transactions on circuits and systems i-Regular papers
JF - Ieee transactions on circuits and systems i-Regular papers
IS - 11
ER -