公开(公告)号：US20240362393A1

公开(公告)日：2024-10-31

申请号：US18139659

申请日：2023-04-26

Applicant: Xilinx, Inc.

Inventor： Apurva Abhijit Mirashi ,  Veeresh Pratap Singh ,  Meghraj Kalase ,  Srinivasan Dasasathyan

IPC: G06F30/394 ,  G06F30/31 ,  G06F30/323 ,  G06F30/327 ,  G06F30/392

CPC classification number: G06F30/394 ,  G06F30/31 ,  G06F30/323 ,  G06F30/327 ,  G06F30/392

Abstract: A congestion prediction machine learning model is trained to generate, prior to placement, a prediction value indicative of a congestion level likely to result from placement and routing of a netlist based on features of the netlist. In response to the prediction value indicating the congestion level is greater than a threshold, a design tool determines an implementation-flow action and performs the implementation-flow action to generate implementation data that is suitable for making an integrated circuit.