With technological upgradation, AI and Machine Learning are transforming every industry with exceptionally great inputs. Referring to the VLSI industry, there has been a considerable amount of required changes done by machine learning. Machine Learning (ML) has benefited the VLSI industry so far by using EDA tools to their maximum usage which helps in reducing design time and cost to production. Machine learning in VLSI design helps EDA tools find the better solution for use case scenarios by predicting the defects on the chip which in turn saves loss during production.
Benefits of machine learning in VLSI design
1) Ease in the verification process:
- As the data generated from complex chips keep exploding, machine learning in VLSI design and verification are much needed to ensure smooth functioning without compromising on its performance and cost.
- Consider RTL design course (a VLSI course) for a better understanding
- ML helps to formulate test cases and suggest better design flows for RTL implementation.
- From RTL design and its verification till synthesis, it helps to focus on improving the current ongoing strategies.
2) Time-saving:
A technique like linear regression associated with ML helps to break down the complexity and resulting in faster verification.
3) 3 P’s ( Power, Performance, Price) :
Synopsys and Cadence are some of the EDA tools which are constantly utilizing machine learning techniques for more efficient design stimulation and revamp the 3 P’s.
Also read: artificial intelligence in VLSI design
Conclusion
The high-end solutions driven by machine learning techniques in chip designs and ease in the verification process are commendable. They have been bringing innovations in the VLSI fields and helping to save the most essential asset- time!
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