IEEE CEDA DATC: Expanding Research Foundations for IC Physical Design and ML-Enabled EDA

Abstract

This paper describes new elements in the RDF-2022 release of the DATC Robust Design Flow, along with other activities of the IEEE CEDA DATC. The RosettaStone initiated with RDF-2021 has been augmented to include 35 benchmarks and four open-source technologies (ASAP7, NanGate45 and SkyWater130HS/HD), plus timing-sensible versions created using path-cutting. The Hier-RTLMP macro placer is now part of DATC RDF, enabling macro placement for large modern designs with hundreds of macros. To establish a clear baseline for macro placers, new open-source benchmark suites on open PDKs, with corresponding flows for fully reproducible results, are provided. METRICS2.1 infrastructure in OpenROAD and OpenROAD-flow-scripts now uses native JSON metrics reporting, which is more robust and general than the previous Python script-based method. Calibrations on open enablements have also seen notable updates in the RDF. Finally, we also describe an approach to establishing a generic, cloud-native large-scale design of experiments for ML-enabled EDA. Our paper closes with future research directions related to DATC’s efforts.