Mentor FINALLY Acquires Solido Design

Mentor FINALLY Acquires Solido Design
by Daniel Nenni on 11-20-2017 at 5:00 pm

I say finally because it was a long time coming… almost ten years to be exact. I started doing business development work for both Solido and Berkeley Design Automation about ten years ago and have been trying to put them together ever since. The synergy was obvious, like peanut butter and jelly. In fact, this is my third time … Read More


A better way to combine PVT and Monte Carlo to improve yield

A better way to combine PVT and Monte Carlo to improve yield
by Tom Simon on 10-11-2017 at 12:00 pm

TSMC held its Open Innovation Platform Forum the other week on September 13[SUP]th[/SUP]. Each year the companies that exhibit at this event choose to highlight their latest technology. One of the most interesting presentations that I received during the event was from Solido. In recent years they have produced a number of groundbreaking… Read More


Solido Debuts New ML Tool at TSMC OIP!

Solido Debuts New ML Tool at TSMC OIP!
by Daniel Nenni on 09-08-2017 at 7:00 am

The TSMC OIP Ecosystem Forum is upon us and what better place to debut a new tool to prevent silicon failures. Solido Design Automation just launched its latest tool – PVTMC Verifier – and will be demonstrating it in their booth at OIP. This is the third product that was developed within its Machine Learning Labs and is… Read More


EDA Machine Learning from the Experts!

EDA Machine Learning from the Experts!
by Daniel Nenni on 08-16-2017 at 7:00 am

Traditionally, EDA has been a brute force methodology where we buy more software licenses and more CPUs and keep running endless jobs to keep up with the increasing design and process complexities. SPICE simulation for example; when I meet chip designers (which I do quite frequently) I ask them how many simulations they do for a … Read More


Machine Learning in EDA Flows – Solido DAC Panel

Machine Learning in EDA Flows – Solido DAC Panel
by Tom Simon on 07-12-2017 at 12:00 pm

At DAC this year you could learn a lot about hardware design for AI or Machine Learning (ML) applications. We are all familiar with the massively parallel hardware being developed for autonomous vehicles, cloud computing, search engines and the like. This includes, for instance, hardware from Nvidia and others that enable ML … Read More


EDA Powered by Machine Learning panel, 1-on-1 demos, and more!

EDA Powered by Machine Learning panel, 1-on-1 demos, and more!
by Daniel Nenni on 06-07-2017 at 12:00 pm

DAC is upon us again! The Design Automation Conference holds special meaning to me as it was the first technical conference I attended as a semiconductor professional, or professional anything for that matter. That was 33 years ago and I have not missed one since. This year my wife and I both will be walking the DAC floor and it would… Read More


We Need Libraries – Lots of Libraries

We Need Libraries – Lots of Libraries
by Tom Simon on 05-08-2017 at 12:00 pm

It was inevitable that machine learning (ML) would come to EDA. In fact, it has already been here a while in Solido’s variation tools. Now it has found an even more compelling application – library characterization. Just as ML has radically transformed other computational arenas; it looks like it will be extremely disruptive here… Read More


Webinar Offers View into TSMC IP Design Methodology

Webinar Offers View into TSMC IP Design Methodology
by Tom Simon on 10-21-2016 at 12:00 pm

Standard cell and memory IP are key enablers for new process node availability. These two items must be in place early and be completely ready for a process node to scale to volume. Development of both leaves no room for error and they require the highest performance possible. Foundries are extremely focused on this and spend a lot… Read More


TSMC and Solido to Share Experiences with Managing Variation in Webinar

TSMC and Solido to Share Experiences with Managing Variation in Webinar
by Tom Simon on 09-10-2016 at 7:00 am

TSMC knows better than anyone the effect that variation can have at advanced process nodes. Particularly in memory designs and in standard cell designs, variation has become a very critical because of its effects on yield and because of the high-cost of compensating for it. Smaller feature sizes combined with lower voltage thresholds… Read More


Statistical Simulation Provides Insight into 6T SRAM Optimization

Statistical Simulation Provides Insight into 6T SRAM Optimization
by Tom Simon on 08-24-2016 at 12:00 pm

ARM’s Azeez Bhavnagarwala recently gave a talk hosted by Solido on the benefits of variation aware design in optimizing 6T bit cells. Azeez sees higher clock rates, increasing usage of SRAM per processor and the escalating number of processors, shown in the diagram below, as trends that push designers toward 6T. Six Transistor… Read More