By Louie De Luna, Agnisys Director of Sales and Marketing

Right after Google’s AlphaGo system defeated a human Go world champion in 2015, the hype of deep learning and machine learning (ML) was quickly assimilated into mainstream technology. In EDA, the application of ML algorithms actually dates back to 2008 – when two Machine Learning-related topics were presented at DAC. The first topic, Efficient System Design Space Exploration Using Machine Learning Techniques targeted design challenges and the second, Experiences and Advances in Formal and Dynamic Verification, targeted verification challenges.

As a company focused on solving both design and verification challenges associated to Hardware/Software Interface (HSI), Agnisys has extensive experience in register code generation and verification, so applying Machine Learning to register automation is a natural next step for us. Agnisys  register tool IDesignSpec is a fully-matured solution with a large user base, where it can generate register code directly from the specification in Word, Excel, IP-XACT or SystemRDL. But in an ideal world, our users would rather use plain and simple English text to describe the register behavior rather than use special properties and syntax. Natural, plain English is still the hallmark of specifications in today’s system design and a lot of useful and actionable information is embedded in the natural language specification text.

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