AI-driven AMP impact on productivity and QoR – Evaluation study | Maxlinear
In this session, Maxlinear shares their study on AMP, Aprisa’s AI-driven Auto Macro Placement applied on their designs, and how the results and runtime compare to their current methodology of hand-placing the macros. They will also discuss how they plan to get the most benefit out of Aprisa’s design exploration capabilities on their future projects.
Meet the speaker
Ravi Ranjan
Director of Physical Design
Ravi Ranjan is the Director of Physical Design at Maxlinear Inc. in Irvine, where he has been responsible for physical design and flow automation for designs from 0.28um to 5nm. Prior to joining Maxlinear he worked at Rockwell Semiconductors, Mindspeed Technology, and Texas Instruments. Ravi received his bachelor’s degree in Electronics and Electrical Communication from the Indian Institute of Technology, in Kharagpur.