We’ve all heard a million times the marketing claims of how a company’s products can improve time to market, improve quality, and lower costs. The three pillars of marketing rhetoric. It reminds me of those old comic book ads where some 97-pound weakling gets sand kicked in his face with his girlfriend nearby and then sends away for a body-building book. The final scene shows him as the hero of the beach after he beats up on the bully.
Times have definitely changed but the marketing hype hasn’t, though there’s certainly a place and time for pulling up a few tried and true marketing campaigns. More on that later.
Instead of marking rhetoric, I’m going to describe two real case studies where the design teams on different continents were able to reduce their design cycle time and how they did it. In both of these examples, the design teams used virtual prototyping and accurate models to drastically reduce their development time. In each case, they went into production with the designs they developed with this methodology much earlier than they would have if they didn’t use it.
Case Study #1: A large European company designing a controller application for factory automation was implementing a system on chip (SoC) with ARM Cortex R series cores. The design team had already been using 100% cycle-accurate models and virtual prototyping tools to bring up, debug and optimize its firmware prior to having silicon available. This was a key part of the methodology because in the past they found that even if the firmware ran successfully on behavioral untimed models (or Fast Models), they still found many problems in the firmware after they replaced the behavioral models with cycle-accurate models. The reason for this was due to the fact that the behavioral models lacked the details and accuracy to expose many of the firmware bugs.
The manager was confident in his methodology but wanted to quantify it somehow. He compared his virtual prototyping flow to similar projects that didn’t use virtual prototyping. For projects using virtual prototyping, he found the firmware could be debugged and validated in about 4 to 5 weeks. For projects that didn’t use virtual prototyping, he found the firmware took as much as 6 months to debug and validate.
A five-month savings! The reasons for this savings was that the 100% accuracy, 100% visibility and controllability available in the virtual prototypes made bugs much easier to find, characterize, and debug compared with hardware prototypes. Because he used cycle-accurate models, they faithfully represented the real implementation and found problems that would have otherwise been hidden and impossible to find in higher level non-timed functional models.
Case Study #2: A fabless semiconductor company in Asia’s project team was designing an SoC to go into tablet and netbook products. The design was based on a dual core ARM Cortex A processor with graphics, video, and image processing components interconnected with a complex AXI fabric. They needed to architect the system, develop their firmware and device drivers, and understand the go-to-market performance of their system in a very short timeframe.
The problem was a big one: This was their first product based on the ARM Cortex A-series cores, so everything (architecture, hardware, and firmware) had to be designed from scratch and they had no past experience to fall back on.
To overcome this daunting task, the team used a virtual prototype and 100% cycle-accurate models to provide the insight for their architectural and firmware teams to understand, optimize and debug their system. This platform allowed the architects to make quick and accurate decisions and provided the firmware engineers the insight to understand the dynamics of the new IP.
In the end, they had a working silicon prototype ready for their customers 9 months after starting the architectural phase of their project. An amazing feat –– architecture to working silicon prototypes in 9 months!
In addition, they spent less than 1 month in the lab debugging their silicon prototype before they had a system that they had enough confidence in to provide to their end customers. The team commented that, without the virtual prototype and cycle-accurate models, achieving this type of schedule would have been impossible to do.
These are just two of many examples where using virtual prototyping with accurate models has proven to reduce the design cycle time to realize an SoC.
And, while I left the marketing hype and rhetoric out of this article, I do acknowledge the importance of image building and creating interest, key aspects of a good marketing and messaging campaign. Without either, it’s unlikely I’d be able to write these short case studies. These companies in Europe and Asia would have no way of knowing about this particular virtual prototyping tool or the cycle-accurate models.About the author
Andy Ladd is vice president of Sales for Europe and Rest of World, and is a member of the founding team at Carbon
. He has more than 16 years experience in the EDA industry managing and directing field resources. Previously, he was the director of applications for cycle-based simulation at Quickturn Design Systems which was acquired by Cadence. Prior to Quickturn, Ladd was part of the initial bring-up team for Speedsim, the first commercially viable cycle-based simulation product in the industry. He also worked on supporting major accounts while working at Viewlogic. In addition to his EDA experience, he worked in microprocessor design and development at both Digital Equipment Corporation and McDonnell Douglas. Ladd holds a Bachelor of Science degree in Computer Engineering from University of Illinois and a Master of Science degree in Computer Science and Engineering from University of Michigan.
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