Twitter of RTL design – welcome to Behavioral Indexing!

Srinivasan Venkataramanan, CVC Pvt. Ltd.

Ajeetha Kumari, CVC Pvt. Ltd.

If you haven’t heard of Twitter you perhaps are living in an internet vacuum J On a positive note, the reach and impact of SNS (Social Networking Sites) into our internet life is hard to ignore – whether it is Twitter, Facebook, LinkedIn etc. To me, a successful SNS tries to capture “what is in going on in your mind right now”? A similar approach can be applied to RTL design – when a designer makes an assumption about the latency of output or the FIFO size etc., it hardly gets captured in a repeatable, executable format. True, at the end of a design phase documentation is written (usually) that attempts to capture these. However it gets too late by then to be “active comments”.

From a language perspective SystemVerilog allows assertions & functional coverage (covergroup) inline with RTL code that can help to some extent. However they are only the “specification” part. A lot more “information” gets lost during such translation such as

· “show me a proof/witness/waveform” for such an occurrence

· Can we optimize the latency to say 5

· What-if I change the FIFO size to 32 here etc.

Jasper’s recently announced ActiveDesign technology has a significant component for this “design process”. It is called “Behavioral Indexing”, you “index” the behavior with facts, assumptions, traces, bugs etc. all in a comprehensive database along with your RTL. So when a designer (or another designer who inherits, reviews the code) looks at the code again (via the ActiveDesign database of-course) he/she can get not only the assumptions (that would be similar to SVA) but also real traces, potential issues of changes to FIFO size etc. In a generic sense the indexing captures the designers state of mind “at that point in time” as a snapshot and keeps it reproducible throughout the lifetime of the RTL code! A good thinking indeed, this is why I like to call it the “Twitter of RTL design”.

There is more to Behavioral Indexing than this, will talk about it next time around, so stay tuned!

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