Axiomise at #59DAC, Formal Update

Axiomise at #59DAC, Formal Update
by Daniel Payne on 07-27-2022 at 10:00 am

Dr. Ashish Darbari min 1

Monday at DAC I was able to meet with Dr. Ashish Darbari, the CEO and founder of Axiomise. Ashish had a busy DAC, appearing as a panelist at,  “Those Darn Bugs! When Will They be Exterminated for Good?”; and then presenting,  “Taming the Beast: RISC-V Formal Verification Made Easy.”

I had read a bit about Axiomise… Read More


Coding Guidelines for Datapath Verification

Coding Guidelines for Datapath Verification
by Bernard Murphy on 06-01-2022 at 6:00 am

multiplier min

It has been an article of faith that you can’t use formal tools to validate datapath logic (math components). Formal is for control logic, not datapath, we now realize. We understood the reason – wide inputs (32-bit, 64-bit or more) fed through a multiplier deliver eye-watering state space sizes. State space explosions also happen… Read More


Writing C/C++ Models for Efficient Datapath Validation Using VC Formal DPV

Writing C/C++ Models for Efficient Datapath Validation Using VC Formal DPV
by Admin on 05-18-2022 at 10:00 am

Wednesday, May 18, 2022 | 10:00 – 11:00 a.m. Pacific

AI, Graphics, CPU, and many modern designs have arithmetic intensive blocks that are hard to verify with traditional techniques. Synopsys VC Formal DPV (Datapath Validation) has been the industry’s golden standard to get closure on datapath verification.

In

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Formal Verification for Non-Specialists

Formal Verification for Non-Specialists
by Admin on 04-06-2022 at 10:00 am

Wed, Apr 6, 2022 10:00 AM – 11:00 AM PDT
Is formal verification ready for general use or do you need a PhD to use it? Larger companies continue to recruit formal PhDs into their verification teams while other less-well-qualified engineers seem reluctant to go beyond simplified formal “apps”. So, what is the truth
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Getting to Faster Closure through AI/ML, DVCon Keynote

Getting to Faster Closure through AI/ML, DVCon Keynote
by Bernard Murphy on 03-10-2022 at 10:00 am

Manish min

Manish Pandey, VP R&D and Fellow at Synopsys, gave the keynote this year. His thesis is that given the relentless growth of system complexity, now amplified by multi-chiplet systems, we must move the verification efficiency needle significantly. In this world we need more than incremental advances in performance. We need… Read More


Creative Applications of Formal at Intel

Creative Applications of Formal at Intel
by Bernard Murphy on 12-01-2021 at 6:00 am

formal image min

One of the sessions I enjoyed at the Synopsys Verification Day 2021 was a presentation on applying formal to a couple of non-traditional problem domains. I like talks of this kind because formal can sometimes be boxed into a limited set of applications, under-exploiting the potential of the technology. Intel have built a centralized… Read More


Formal Verification Approach Continues to Grow

Formal Verification Approach Continues to Grow
by Daniel Payne on 05-12-2021 at 10:00 am

formal history min

After a few decades of watching formal verification techniques being applied to SoC designs, it  certainly continues to be a growth market for EDA vendors. In the first decades from 1970-1990 the earliest forms of formal tools emerged at technical conferences, typically written by University students earning their Ph.D.s, … Read More


Formal for Post-Silicon Bug Hunting? Makes perfect sense

Formal for Post-Silicon Bug Hunting? Makes perfect sense
by Bernard Murphy on 03-31-2021 at 6:00 am

Bug hunting process for DDR problem min

You verified your product design against every scenario your team could imagine. Simulated, emulated, with constrained random to push coverage as high as possible. Maybe you even added virtualized testing against realistic external traffic. You tape out, wait with fingers crossed for first silicon to come back. Plug it into… Read More


A New ML Application, in Formal Regressions

A New ML Application, in Formal Regressions
by Bernard Murphy on 02-10-2021 at 6:00 am

A New ML Application

Machine learning (ML) is a once-in-a-generation innovation that seems like it should be applicable almost everywhere. It’s certainly revolutionized automotive safety, radiology and many other domains. In our neck of the woods, SoC implementation is advancing through learning to reduce total negative slacks and better optimize… Read More