Nvidia is one of the leading designers of chips used for artificial intelligence (AI) and machine learning (ML) acceleration. Therefore it is apt that it looks set to be one of the pioneers in applying AI to chip design. Today, it published a paper and blog post revealing how its AutoDMP system can accelerate modern chip floor-planning using GPU-accelerated AI/ML optimization, resulting in a 30X speedup over previous methods.
AutoDMP is short for Automated DREAMPlace-based Macro Placement. It is designed to plug into an Electronic Design Automation (EDA) system used by chip designers, to accelerate and optimize the time-consuming process of finding optimal placements for the building blocks of processors. In one of Nvidia’s examples of AutoDMP at work, the tool leveraged its AI on the problem of determining an optimal layout of 256 RSIC-V cores, accounting for 2.7 million standard cells and 320 memory macros. AutoDMP took 3.5 hours to come up with an optimal layout on a single Nvidia DGX Station A100.
