Cao, Linan, Bale, Simon J. and Trefzer, Martin A. orcid.org/0000-0002-6196-6832 (2021) Multi-objective Optimisation of Digital Circuits based on Cell Mapping in an Industrial EDA Flow. [Preprint]
Abstract
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.
Metadata
Item Type: | Preprint |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This work has been submitted to the IEEE for possible publication |
Keywords: | cs.NE |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 08 Jun 2023 23:18 |
Last Modified: | 23 Jan 2025 00:44 |
Status: | Published |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200223 |