Presentation
A New Frontier for Floorplanning with AI
Description5G Downlink Datapath designs contain repeated structures, the same design instantiated multiple times, which make it very difficult to identify and place the macros in a way that is optimal for routability and performance. Traditional macro placement however, has been a very manual and iterative endeavor for these and all types of complex designs where the number of macros has grown dramatically, the sizes vary widely, and the interconnectivity between them is more intricate.
In this paper, we set out to test if a P&R AI-driven macro placement capability could mimic the QoR (floorplan quality and design metrics), achieved by the expert engineers on this design but in a fraction of the time, and lessening the burden of manually placing the macros and running full-flow iterations required on our traditional flow.
In addition, we further investigated the benefits of the feature's Bayesian optimization flow on design exploration for the same block. Analyzing if the generation of various floorplans that each alone could meet the required metrics, could yield and optimal solution, unique to the needs of the design. By providing comparison results at post placement, the designers could then choose which option to push through the full P&R flow, reducing the total number of iterations and the overall turnaround time.
In this paper, we set out to test if a P&R AI-driven macro placement capability could mimic the QoR (floorplan quality and design metrics), achieved by the expert engineers on this design but in a fraction of the time, and lessening the burden of manually placing the macros and running full-flow iterations required on our traditional flow.
In addition, we further investigated the benefits of the feature's Bayesian optimization flow on design exploration for the same block. Analyzing if the generation of various floorplans that each alone could meet the required metrics, could yield and optimal solution, unique to the needs of the design. By providing comparison results at post placement, the designers could then choose which option to push through the full P&R flow, reducing the total number of iterations and the overall turnaround time.
Event Type
Back-End Design
TimeMonday, June 242:06pm - 2:24pm PDT
Location2008, 2nd Floor
Back-End Design
Design
Engineering Tracks