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Roadblocks For ML In EDA

Successful utilization of machine learning within EDA cannot happen without confidence in the quality of results. That presents challenges.

Semiconductor Engineering


Is EDA a suitable space for utilizing machine learning (ML)? The answer depends on a number of factors, including where exactly it is being applied, how much support there is from the industry, and whether there are demonstrable advantages.
Exactly where ML will play a role has yet to be decided. Replacing existing heuristics with machine learning, for example, would require an industry-wide effort to overcome a long list of challenges, which is unlikely to happen. But there are other opportunities where ML is likely to be more successful. Tools within the EDA space, and the heuristics embedded in them, are guided by the faithfulness of the abstraction utilized for a certain purpose in the design flow…


To read the full Semiconductor Engineering article by Brian Bailey, click here.