Posts Tagged ‘formal verification’

17 March, 2015


With a name like “Fitzpatrick,” you knew I’d be celebrating today, right?

Well, there’s no better way to celebrate this fine day than to announce that our latest edition of Verification Horizons is available online! Now that Spring is almost here, there’s a bit less snow on the ground than there was when I wrote my introduction, but everything is still covered. I’m considering spray-painting it all green in honor of the occasion, so at least it looks like I have a lawn again.

In this issue of Verification Horizons, I’d particularly like to draw your attention to “Successive Refinement: A Methodology for Incremental Specification of Power Intent,” by my friend and colleague Erich Marschner and several of our friends at ARM® Ltd. In this article, you’ll find out how the Unified Power Format (UPF) specification can be used to specify and verify your power architecture abstractly, and then add implementation information later in the process. This methodology is still relatively new in the industry, so if you’re thinking about making your next design PowerAware, you’ll want to read this article to be up on the very latest approach.

In addition to that, we’ve also got Harry Foster discussing some of the results from his latest industry study in “Does Design Size Influence First Silicon Success?” Harry is also blogging about his survey results on Verification Horizons here and here (with more to come).

Our friends at L&T Technology Services Ltd. share some of their experience in doing PowerAware design in “PowerAware RTL Verification of USB 3.0 IPs,” in which you’ll see how UPF can let you explore two different power management architectures for the same RTL.

Next, History class is in session, with Dr. Lauro Rizzatti, long-time EDA guru, giving us part 1 of a 3-part lesson in “Hardware Emulation: Three Decades of Evolution.”

Our friends at Oracle® are up next with “Evolving the Use of Formal Model Checking in SoC Design Verification,” in which they share a case study of their use of formal methods as the central piece in verifying an SoC design they recently completed with first-pass silicon success. By the way, I’d also like to take this opportunity to congratulate the author of this article, Ram Narayan, for his Best Paper award at DVCon(US) 2015. Well done, Ram!

We round out the issue with our famous “Partners’ Corner” section, which includes two articles. In “Small, Maintainable Tests,” our friends at Sondrel IC Design Services show you a few tricks on how to make use of UVM virtual sequences to raise the level of abstraction of your tests. In “Functional Coverage Development Tips: Do’s and Don’ts,” our friends at eInfochips give you a great overview of functional coverage, especially the covergroup and related features in SystemVerilog.

I’d also like to take a moment to thank all of you who came by our Verification Academy booth at DVCon to say hi. I found it incredibly humbling and gratifying to hear from so many of you who have learned new verification skills from the Verification Academy. That’s a big part of why we do what we do, and I appreciate you letting us know about it.

Now, it’s time to celebrate St. Patrick’s Day for real!

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17 November, 2014

Few verification tasks are more challenging than trying to achieve code coverage goals for a complex system that, by design, has numerous layers of configuration options and modes of operation.  When the verification effort gets underway and the coverage holes start appearing, even the most creative and thorough UVM testbench architect can be bogged down devising new tests – either constrained-random or even highly directed tests — to reach uncovered areas.

At the recent ARM® Techcon, Nguyen Le, a Principal Design Verification Engineer in the Interactive Entertainment Business Unit at Microsoft Corp. documented a real world case study on this exact situation.  Specifically, in the paper titled “Advanced Verification Management and Coverage Closure Techniques”, Nguyen outlined his initial pain in verification management and improving cover closure metrics, and how he conquered both these challenges – speeding up his regression run time by 3x, while simultaneously moving the overall coverage needle up to 97%, and saving 4 man-months in the process!  Here are the highlights:

* DUT in question
— SoC with multi-million gate internal IP blocks
— Consumer electronics end-market = very high volume production = very high cost of failure!

* Verification flow
— Constrained-random, coverage driven approach using UVM, with IP block-level testbenches as well as  SoC level
— Rigorous testplan requirements tracking, supported by a variety of coverage metrics including functional coverage with SystemVerilog covergroups, assertion coverage with SVA covers, and code coverage on statements, Branches, Expressions, Conditions, and FSMs

* Sign-off requirements
— All test requirements tracked through to completion
— 100% functional, assertion and code coverage

* Pain points
— Code coverage: code coverage holes can come from a variety of expected and unforeseen sources: dead code can be due to unused functions in reused IP blocks, from specific configuration settings, or a bug in the code.  Given the rapid pace of the customer’s development cycle, it’s all too easy for dead code to slip into the DUT due to the frequent changes in the RTL, or due to different interpretations of the spec.  “Unexplainably dead” code coverage areas were manually inspected, and the exclusions for properly unreachable code were manually addressed with the addition of pragmas.  Both procedures were time consuming and error prone
— Verification management: the verification cycle and the generated data were managed through manually-maintained scripting.  Optimizing the results display, throughput, and tool control became a growing maintenance burden.

* New automation
— Questa Verification Manager: built around the Unified Coverage Database (UCDB) standard, the tool supports a dynamic verification plan cross-linked with the functional coverage points and code coverage of the DUT.  In this way the dispersed project teams now had a unified view which told them at a glance which tests were contributing the most value, and which areas of the DUT needed more attention.  In parallel, the included administrative features enabled efficient control of large regressions, merging of results, and quick triage of failures.

— Questa CoverCheck: this tool reads code coverage results from simulation in UCDB, and then leverages formal technology under-the-hood to mathematically prove that no stimulus could ever activate the code in question. If it’s OK for a given block of code to be dead due to a particular configuration choice, etc., the user can automatically generate wavers to refine the code coverage results.  Additionally, the tool can also identify segments of code that, though difficult to reach, might someday be exercised in silicon. In such cases, CoverCheck helps point the way to testbench enhancements to better reach these parts of the design.

— The above tools used in concert (along with Questasim) enabled a very straightforward coverage score improvement process as follows:
1 – Run full regression and merge the UCDB files
2 – Run Questa CoverCheck with the master UCDB created in (1)
3 – Use CoverCheck to generate exclusions for “legitimate” unreachable holes, and apply said exclusions to the UCDB
4 – Use CoverCheck to generate waveforms for reachable holes, and share these with the testbench developer(s) to refine the stimulus
5 – Report the new & improved coverage results in Verification Manager

* Results
— Automation with Verification Manager enabled Microsoft to reduce the variation of test sequences from 10x runtime down to a focused 2x variation.  Additionally, using the coverage reporting to rank and optimize their tests, they increased their regression throughput by 3x!
— With CoverCheck, the Microsoft engineers improved code coverage by 10 – 15% in most hand-coded RTL blocks, saw up to 20% coverage improvement for auto-generated RTL code, and in a matter of hours were able to increase their overall coverage number from 87% to 97%!
— Bottom-line: the customer estimated that they saved 4 man-months on one project with this process

2014 MSFT presentation at ARM Techcon -- cover check ROI

Taking a step back, success stories like this one, where automated, formal-based applications leverage the exhaustive nature of formal analysis to tame once intractable problems (which require no prior knowledge of formal or assertion-based verification), are becoming more common by the day.  In this case, Mentor’s formal-based CoverCheck is clearly the right tool for this specific verification need, literally filling in the gaps in a traditional UVM testbench verification flow.  Hence, I believe the overall moral of the story is a simple rule of thumb: when you are grappling with a “last mile problem” of unearthing all the unexpected, yet potentially damaging corner cases, consider a formal-based application as the best tool for job.  Wouldn’t you agree?

Joe Hupcey III

Reference links:

Direct link to the presentation slides:

ARM Techcon 2014 Proceedings:

Official paper citation:
Advanced Verification Management and Coverage Closure Techniques, Nguyen Le, Microsoft; Harsh Patel, Roger Sabbagh, Darron May, Josef Derner, Mentor Graphics

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5 November, 2014

Between 2006 and 2014, the average number of IPs integrated into an advanced SoC increased from about 30 to over 120. In the same period, the average number of embedded processors found in an advanced SoC increased from one to as many as 20. However, increased design size is only one dimension of the growing verification complexity challenge. Beyond this growing-functionality phenomenon are new layers of requirements that must be verified. Many of these verification requirements did not exist ten years ago, such as multiple asynchronous clock domains, interacting power domains, security domains, and complex HW/SW dependencies. Add all these challenges together, and you have the perfect storm brewing.

It’s not just the challenges in design and verification that have been changing, of course. New technologies have been developed to address emerging verification challenges. For example, new automated ways of applying formal verification have been developed that allow non-Formal experts to take advantage of the significant benefits of formal verification. New technology for stimulus generation have also been developed that allow verification engineers to develop complex stimulus scenarios 10x more efficiently than with directed tests and execute those tests 10x more efficiently than with pure-random generation.

It’s not just technology, of course. Along with new technologies, new methodologies are needed to make adoption of new technologies efficient and repeatable. The UVM is one example of these new methodologies that make it easier to build complex and modular testbench environments by enabling reuse – both of verification components and knowledge.

The Verification Academy website provides great resources for learning about new technologies and methodologies that make verification more effective and efficient. This year, we tried something new and took Verification Academy on the road with live events in Austin, Santa Clara, and Denver. It was great to see so many verification engineers and managers attending to learn about new verification techniques and share their experiences applying these techniques with their colleagues.


If you weren’t able to attend one of the live events – or if you did attend and really want to see a particular session again – you’re in luck. The presentations from the Verification Academy Live seminars are now available on the Verification Academy site:

  • Navigating the Perfect Storm: New School Verification Solutions
  • New School Coverage Closure
  • New School Connectivity Checking
  • New School Stimulus Generation Techniques
  • New School Thinking for Fast and Efficient Verification using EZ-VIP
  • Verification and Debug: Old School Meets New School
  • New Low Power Verification Techniques
  • Establishing a company-wide verification reuse library with UVM
  • Full SoC Emulation from Device Drivers to Peripheral Interfaces

You can find all the sessions via the following link:

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25 February, 2014

As DVCon expands, we at Mentor Graphics have grown our sponsored sessions as well.  Would you expect less?

In DVCon’s recent past, it was a tradition for the North American SystemC User Group (NASCUG) to sponsor a day of activity before the official start of the conference.  When OSCI merged with Accellera, the day before the official conference start grew to become Accellera Day with a broader set of meetings and activities covering many of Accellera’s standards.  This has all grown into a more official part of the DVCon program.  On Monday at DVCon – or as many still call it – Accellera Day – the tradeshow now joins in opening.  I covered this in detail in an earlier blog, so I won’t repeat myself now.

The pre-conference education and meet-up to discuss the latest in standards development is joined by an end of conference tutorial series that has expanded to allow four parallel sessions from three.  Instead of the one tutorial we at Mentor Graphics would otherwise sponsor at DVCon, we will offer two in this expanded series. Given the impact verification has on design it would seem right that more time be devoted to topics that address this.  One half-day tutorial is just to short to give the subject its due respect.

The two Mentor Graphics sponsored tutorials at DVCon, to be run in series, will devote a day to explore the application of current verification technology by us and users like you.  If you are already attending DVCon, you are making your tutorial selections now.  And for those who might only be interested to attend the tutorials themselves, DVCon offers a tutorials-only package ($145/Tutorial).  Mentor’s two tutorials are:

The first tutorial references “smooth sailing,” not because this will be a “no-pirate zone,” although I can tell you that since International Talk Like a Pirate Day is in late September, one won’t have to worry about a morning of pirate talk! [Interesting Fun Fact: Mentor Graphics’ headquarters in Wilsonville, OR USA is a short 50 miles (~80 km) north of the creators of this parotic holiday.]  The smooth sailing comes from the ability to easily use multiple engines from simulation, formal, emulation, FPGA prototyping to address your block to system-level verification needs.

The second tutorial is all about formal.  Or, in a more colloquial way to say it, we will answer the question: Whatsup with formal?  No, I doubt we will find more slang terms for formal technology being used and created in the tutorial.  But the tutorial will certainly look at more focused applications of formal technology.  As a pioneer in focused formal applications (like clock domain crossing) the creation of these focused formal applications has greatly simplified use and expanded technology access to verification teams with RTL design checks, X-state verification, and more joining the list.  Maybe we should ask Whatsapp with formal! But wait!  That slang question is already taken – and Facebook affirmed ownership with a $19B purchase of it recently.  Oh well, I lament.  Join me at this tutorial and we can explore something suitable and not yet taken as a replacement.  I can’t think of a better way to close DVCon than to see if we can invent another $19B term (or app).

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30 October, 2013


This week ARM® TechCon® 2013 is being held at the Santa Clara Convention Center from Tuesday October 29 through Thursday October 31st, but don’t worry, there’s nothing to be scared about.  The theme is “Where Intelligence Counts”, and in fact as a platinum sponsor of the event, Mentor Graphics is excited to present no less than ten technical and training sessions about using intelligent technology to design and verify ARM-based designs.

My personal favorite is scheduled for Halloween Day at 1:30pm, where I’ll tell you about a trick that Altera used to shave several months off their schedule, while verifying the functionality and performance of an ARM AXI™ fabric interconnect subsystem.  And the real treat is that they achieved first silicon success as well.  In keeping with the event’s theme, they used something called “intelligent” testbench automation.

And whether you’re designing multi-core designs with AXI fabrics, wireless designs with AMBA® 4 ACE™ extensions, or even enterprise computing systems with ARM’s latest AMBA® 5 CHI™ architecture, these sessions show you how to take advantage of the very latest simulation and formal technology to verify SoC connectivity, ensure correct interconnect functional operation, and even analyze on-chip network performance.

On Tuesday at 10:30am, Gordon Allan described how an intelligent performance analysis solution can leverage the power of an SQL database to analyze and verify interconnect performance in ways that traditional verification techniques cannot.  He showed a wide range of dynamic visual representations produced by SoC regressions that can be quickly and easily manipulated by engineers to verify performance to avoid expensive overdesign.

Right after Gordon’s session, Ping Yeung discussed using intelligent formal verification to automate SoC connectivity, overcoming observability and controllability challenges faced by simulation-only solutions.  Formal verification can examine all possible scenarios exhaustively, verifying on-chip bus connectivity, pin multiplexing of constrained interfaces, connectivity of clock and reset signals, as well as power control and scan test signal connectivity.

On Wednesday, Mark Peryer shows how to verify AMBA interconnect performance using intelligent database analysis and intelligent testbench automation for traffic scenario generation.  These techniques enable automatic testbench instrumentation for configurable ARM-based interconnect subsystems, as well as highly-efficient dense, medium, sparse, and varied bus traffic generation that covers even the most difficult to achieve corner-case conditions.

And finally also on Halloween, Andy Meyer offers an intelligent workshop for those that are designing high performance systems with hierarchical and distributed caches, using either ARM’s AMBA 5 CHI architecture or ARM’s AMBA 4 ACE architecture.  He’ll cover topics including how caching works, how to improve caching performance, and how to verify cache coherency.

For more information about these sessions, be sure to visit the ARM TechCon program website.  Or if you miss any of them, and would like to learn about how this intelligent technology can help you verify your ARM designs, don’t be afraid to email me at   Happy Halloween!

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26 August, 2013

Verification Techniques & Technologies Adoption Trends (Continued)

This blog is a continuation of a series of blogs that present the highlights from the 2012 Wilson Research Group Functional Verification Study (for a background on the study, click here).

In my previous blog (Part 10 click here), I presented verification techniques and technologies adoption trends, as identified by the 2012 Wilson Research Group study. In this blog, I continue those discussions and focus on formal verification, acceleration/emulation, and FPGA prototyping.

For years, the term “formal verification” has bugged me since it is quite often misunderstood in the industry. The problem originated back in the mid 1990’s with the emergence of formal equivalence checking tools from various EDA vendors, such as Chrysalis Symbolic Design. These tools were introduced to the market as formal verification, which is technically a true statement. However, there are a range of tools available under the category formal verification, such as formal property checkers and equivalence checkers.

So, what’s the problem? The question related to formal property checking in prior studies could have been misinterpreted by some participants to mean equivalence checking, which reduces the confidence in the results. To prevent this misinterpretation, we decided to change the question in 2012 to clarify that we were talking about the formal verification of assertions and clearly state “not equivalence checking” in the question.

One other thing we wanted to learn in the formal verification space during this study was what percentage of the market was using these auto-formal analysis tools (such as X safety checks, deadlock detection, reset analysis, etc.) versus formal property checking tools. The previous studies never made this distinction.

The fact that we changed the question related to formal property checking while adding in auto-formal in the 2012 study means that there is no meaningful way to compare this study’s formal verification results to the formal verification results from prior studies.

Formal Technology Adoption Trends

Figure 1 shows the adoption percentages for formal property checking and auto-formal techniques.

Figure 1. Formal Technology Adoption

We found that about five percent of the participants who are applying auto-formal techniques are not doing formal property checking. This means that the combined adoption of formal property checking and auto-formal techniques is about 32 percent. As a point of reference, the 2007 FarWest Research study found 19 percent adoption for formal verification—and the 2010 study found the adoption at 29 percent. Both the 2007 and 2010 studies included the potential erroneous responses associated with formal equivalence checking, as well as auto-formal usage.

Figure 2 provides a different analysis of the formal property adoption data by partitioning the results by design sizes. The design size partitions are represented as: less than 5M gates, 5M to 20M gates, and greater than 20M gates.

Figure 2. Formal property checking adoption by design size

Acceleration/Emulation & FPGA Prototyping Adoption Trends

The amount of time spent in a simulation regression is an increasing concern for many projects. Intuitively, we tend to think that the design size influences simulation performance. However, there are two equally important factors that must be considered: number of tests in the simulation regression suite and the length of each test in terms of clock cycles.

For example, a project might have a small or moderate-sized design, yet verification of this design requires a long running test (e.g., a video input stream). Hence, in this example, the simulation regression time is influenced by the number of clock cycles required for the test and not necessarily the design size itself.

Figure 3 shows the number of directed tests created to verify a design in simulation (i.e., the regression suite). The findings obviously varied dramatically from a handful of tests to thousands of tests in a regression suite, depending on the design.

Figure 3. Number directed test created to verify a design

The increase in tests in the range of 1-100 is interesting to note. Is this due to the increase in adoption of constrained-random verification techniques in the past few years? Or possibly, something else is going on here. This line of questioning illustrates the value of reviewing various industry studies. That is, it is not so much in the absolute values a study presents, but the questions the new data raises.

Next, let’s look at regression times as shown in Figure 5. As you can see, it also varies dramatically from short regression times for some projects to multiple days for other projects. The median simulation regression time is about 16-24 hours. Here, we also see an increase in shorter regression times. Again this data raises some interesting questions that are worth exploring.

Figure 4. Simulation regression time trends

One technique that is often used to speed up simulation regressions (either due to very long tests and lots of tests) is either hardware-assisted acceleration or emulation. In addition, FPGA prototyping, while historically used as a platform for software development, has recently served a role in SoC integration validation.

Figure 5 shows the adoption trend for both HW-assisted acceleration/emulation and FPGA prototyping by comparing the 2007 Far West Research study (in gray), the 2010 Wilson Research Group study (in blue), and the 2012 Wilson Research Group study (in green). We see a continual rise in HW acceleration and emulation. This is not only due to the need to verify larger designs, or designs with long test times. HW acceleration and emulation has become the key platform for SoC Integration verification, where both hardware and software are integrated into a system for the first time. In addition, emulation is being used increasingly as a software development platform.

Figure 5. HW-assisted acceleration/emulation and FPGA Prototyping trends

Note that the adoption of FPGA prototyping has remained flat (or decreased slightly as the 2012 data suggest). This might seem counter-intuitive since we previously saw a trend in terms of the increase in SoC class designs. So what’s going on?

Figure 6 partitions the data for HW-assisted acceleration/emulation and FPGA prototyping adoption by design size: less than 1M gates, 1M to 20M gates, and greater than 20M gates. Notice that the adoption of HW-assisted acceleration/emulation continues to increase as design sizes increase. However, the adoption of FPGA prototyping rapidly drops off as design sizes increase beyond 20M gates. 

Figure 6. Acceleration/emulation and FPGA prototyping adoption by design size

This graph illustrates one of the problems with FPGA prototyping of very large designs, which is that there is an increased engineering effort required to partition designs across multiple FPGAs. In fact, what I have found is that FPGA prototyping of very large designs is often a major engineering effort in itself, and that many projects are seeking alternative solutions to address this problem.

In my next blog (click here), I will present the final data I plan to share from the Wilson Research Group study. This blog will focus on results in terms of meeting schedules, required spins, and classes of bugs contributing to respins. I will then wrap up this series of blogs in what I call the Epilogue—which will discuss potential gotchas and cautions on interpreting certain aspects of the data and thoughts about how the data could be used constructively.

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29 July, 2013

Testbench Characteristics and Simulation Strategies

This blog is a continuation of a series of blogs that present the highlights from the 2012 Wilson Research Group Functional Verification Study (for background on the study, click here).

In my previous blog (click here), I focused on the controversial topic of effort spent in verification. In this blog, I focus on some of the 2012 Wilson Research Group findings related to testbench characteristics and simulation strategies. Although I am shifting the focus away from verification effort, I believe that the data I present in this blog is related to my previous blog and really needs to be considered when calculating effort.

Time Spent in full-chip versus Subsystem-Level Simulation

Let’s begin by looking at Figure 1, which shows the percentage of time (on average) that a project spends in full-chip or SoC integration-level verification versus subsystem and IP block-level verification. The mean time performing full chip verification is represented by the dark green bar, while the mean time performing subsystem verification is represented by the light green bar. Keep in mind that this graph represents the industry average. Some projects spend more time in full-chip verification, while other projects spend less time.

Figure 1. Mean time spent in full chip versus subsystem simulation

Number of Tests Created to Verify the Design in Simulation

Next, let’s look at Figure 2, which shows the number of tests various projects create to verify their designs using simulation. The graph represents the findings from the 2007 Far West Research study (in gray), the 2010 Wilson Research Group study (in blue), and the 2012 Wilson Research Group study (in green). Note that the curves look remarkably similar over the past five years. The median number of tests created to verify the design is within the range of (>200 – 500) tests. It is interesting to see a sharp percentage increase in the number of participants who claimed that fewer tests (1 – 100) were created to verify a design in 2012. It’s hard to determine exactly why this was the case—perhaps it is due to the increased use of constrained random (which I will talk about shortly). Or perhaps there has been an increased use of legacy tests. The study was not design to go deeper into this issue and try to uncover the root cause. This is something I intend to informally study this next year through discussions with various industry thought leaders.

Figure 2. Number of tests created to verify a design in simulation

Percentage of Directed Tests versus Constrained-Random Tests

Now let’s compare the percentage of directed testing that is performed on a project to the percentage of constrained-random testing. Of course, in reality there is a wide range in the amount of directed and constrained-random testing that is actually performed on various projects. For example, some projects spend all of their time doing directed testing, while other projects combine techniques and spend part of their time doing directed testing—and the other part doing constrained-random. For our comparison, we will look at the industry average, as shown in Figure 3. The average percentage of tests that were directed is represented by the dark green bar, while the average percentage of tests that are constrained-random is represented by the light green bar.

Figure 3. Mean directed versus constrained-random testing performed on a project

Notice how the percentage mix of directed versus constrained-random testing has changed over the past two years.Today we see that, on average, a project performs more constrained-random simulation. In fact, between 2010 and 2012 there has been a 39 percent increase in the use of constrained-random simulation on a project. One driving force behind this increase has been the maturing and acceptance of both the SystemVerilog and UVM standards—since two standards facilitate an easier implementation of a constrained-random testbench. In addition, today we find that an entire ecosystem has emerged around both the SystemVerilog and UVM standards. This ecosystem consists of tools, verification IP, and industry expertise, such as consulting and training.

Nonetheless, even with the increased adoption of constrained-random simulation on a project, you will find that constrained-random simulation is generally only performed at the IP block or subsystem level. For the full SoC level simulation, directed testing and processor-driven verification are the prominent simulation-based techniques in use today.

Simulation Regression Time

Now let’s look at the time that various projects spend in a simulation regression. Figure 4 shows the trends in terms of simulation regression time by comparing the 2007 Far West Research study (in gray) with the 2010 Wilson Research Group study (in blue), and the 2012 Wilson Research Group study (in green). There really hasn’t been a significant change in the time spent in a simulation regression within the past three years. You will find that some teams spend days or even weeks in a regression. Yet today, the industry median is between 8 and 16 hours, and for many projects, there has been a decrease in regression time over the past few years. Of course, this is another example of where deeper analysis is required to truly understand what is going on. To begin with, these questions should probably be refined to better understand simulation times related to IP versus SoC integration-level regressions. We will likely do that in future studies—with the understanding that we will not be able to show trends (or at least not initially).

Figure 4. Simulation regression time trends

In my next blog (click here), I’ll focus on design and verification language trends, as identified by the 2012 Wilson Research Group study.

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22 July, 2013

Effort Spent On Verification (Continued)

This blog is a continuation of a series of blogs that present the highlights from the 2012 Wilson Research Group Functional Verification Study (for a background on the study, click here).

In my previous blog (click here), I focused on the controversial topic of effort spent in verification. This blog continues that discussion.

I stated in my previous blog that I don’t believe there is a simple answer to the question, “how much effort was spent on verification in your last project?” I believe that it is necessary to look at multiple data points to truly get a sense of the real effort involved in verification today. So, let’s look at a few additional findings from the study.

Time designers spend in verification

It’s important to note that verification engineers are not the only project members involved in functional verification. Design engineers spend a significant amount of their time in verification too, as shown in Figure 1.

Figure 1. Average (mean) time design engineers spend in design vs. verification

In fact, you might note that design engineers now actually spend more time doing verification than design. This time expenditure has shifted in the last five years. In fact, the amount of time that design engineers spend doing verification has increased by 15 percent since 2007, while the amount of time they spend doing design has decreased by about 13 percent.

The designer’s involvement in verification ranges from:

  • Small sandbox testing to explore various aspects of the implementation
  • Full functional testing of IP blocks and SoC integration
  • Debugging verification problems identified by a separate verification team

Percentage of time verification engineers spends in various task

Next, let’s look at the mean time verification engineers spend in performing various tasks related to their specific project. You might note that verification engineers spend most of their time in debugging. Ideally, if all the tasks were optimized, then you would expect this. Yet, unfortunately, the time spent in debugging can vary significantly from project-to-project, which presents scheduling challenges for managers during a project’s verification planning process.

Figure 2. Average (mean) time verification engineers spend in various task

Number of formal analysis, FPGA prototyping, and emulation Engineers

Functional verification is not limited to simulation-based techniques. Hence, it’s important to gather data related to other functional verification techniques, such as the number of verification engineers involved in formal analysis, FPGA prototyping, and emulation.

Figure 3 presents the trends in terms of the number of verification engineers focused on formal analysis on a project. In 2007, the mean number of verification engineers focused on formal analysis on a project was 1.68, while in 2010 the mean number increased to 1.84. For some reason, we did see a slight decreased in the mean number of verification engineers who focus on formal in 2012. Regardless, the curve is remarkably consistent for the past five years.

Figure 3. Median number of verification engineers focused on formal analysis

Although FPGA prototyping is a common technique used to create platforms for software development, it is also sometimes used by projects for SoC integration verification and system validation. Figure 4 presents the trends in terms of the number of verification engineers focused on FPGA prototyping. In 2007, the mean number of verification engineers focused on FPGA prototyping on a project was 1.42, while in 2010 the mean number was 1.86. In 2012 we saw a slight decline in mean number of verification engineers focused on FPGA prototyping. However, the curve has been remarkably similar for the past five years.

Figure 4. Number of verification engineers focused on FPGA prototyping

Figure 5 presents the trends in terms of the number of verification engineers focused on hardware-assisted acceleration and emulation. In 2007, the mean number of verification engineers focused on hardware-assisted acceleration and emulation on a project was 1.31, while in 2010 the mean number was 1.86. In 2012, we see a slight decrease in the mean number of verification engineers who focus on hardware-assisted acceleration and emulation.

Figure 5. Number of verification engineers focused on emulation

Again, noticed how the curve has been consistent over the past five years. In other words, we are not seeing any big trends in terms of increased verification engineers focused predominately on formal, FPGA prototyping, and hardware-assisted acceleration and emulation. This trend was certainly not true for general verification engineers who focus on simulation-based techniques, as I presented in my previous blog, where we saw a 75 percent increase in the peak number verification engineers involved on a project within the past five years.

A few more thoughts on verification effort

So, can I conclusively state that 70 percent of a project’s effort is spent in verification today as some people have claimed? No. In fact, even after reviewing the data on different aspects of today’s verification process, I would still find it difficult to state quantitatively what the effort is. Yet, the data that I’ve presented so far seems to indicate that the effort (whatever it is) is increasing. And there is still additional data relevant to the verification effort discussion that I plan to present in upcoming blogs. However, in my next blog (click here), I shift the discussion from verification effort, and focus on some of the 2012 Wilson Research Group findings related to testbench characteristics and simulation strategies.

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8 July, 2013

Reuse Trends

This blog is a continuation of a series of blogs that present the highlights from the 2012 Wilson Research Group Functional Verification Study (click here).  In my previous blog (click here), I focused on clocking and power management.  In this blog, I focus on design and verification reuse trends. As I mentioned in my prologue blog to this series (click here), one interesting trend that emerged from the study is that reuse adoption is increasing.

Design Composition Trends

Figure 1 shows the mean design composition trends graph, which compares the 2007 Far West Research study (in blue) with the 2012 Wilson Research Group study (in green).

New logic development has decreased by 34 percent in the last five years, while external IP adoption has increased by 69 percent. This increase in adoption has been driven by IP demand required for SoC development, such as embedded processor cores and standard interface cores. 

Figure 1. Mean design composition trends

Figure 2 compares today’s design composition between FPGA designs (in red) with Non-FPGA designs (in green). Currently, more new designs (i.e., new RTL) are created for FPGA versus Non-FPGA designs. However, as FPGAs get larger in terms of transistors, reuse will become even more important to address the design productivity gap that could arise between the number of transistors that can be manufactured on an FPGA and the amount of time to design for a given project.

Figure 2. Mean composition comparison between FPGA and Non-FPGA designs.


Verification Testbench Composition Trends

Figure 3 shows the mean testbench composition trends graph, which compares the 2007 Far West Research study (in blue) with the 2012 Wilson Research Group study (in green).

Notice that new verification code development has decreased by 24 percent in the last three years, while external verification IP adoption has increased by 138 percent. This increase has been driven by the emergence of standard on-chip and off-chip bus architectures.

Figure 3. Mean testbench composition trends

Figure 4 compares today’s testbench composition between FPGA (in red) and Non-FPGA (in green) designs. Again, we see that more new code is written today for FPGA than Non-FPGA testbenches, and I expect this will change over time to be more in line with Non-FPGA designs. 

Figure 4. Mean testbench composition comparison between FPGA and Non-FPGA designs

In my next blog (click here), I’ll shift my focus from design trends to project resource trends. I’ll also present our findings on the project effort spent in verification.

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23 April, 2013

This is the first in a series of blogs that presents the results from the 2012 Wilson Research Group Functional Verification Study.

Study Overview

In 2002 and 2004, Ron Collett International, Inc. conducted its well known ASIC/IC functional verification studies, which provided invaluable insight into the state of the electronic industry and its trends in design and verification. However, after the 2004 study, no other industry studies were conducted, which left a void in identifying industry trends.

To address this void, Mentor Graphics commissioned Far West Research to conduct an industry study on functional verification in the fall of 2007. Then in the fall of 2010, Mentor commissioned Wilson Research Group to conduct another functional verification study. Both of these studies were conducted as blind studies to avoid influencing the results. This means that the survey participants did not know that the study was commissioned by Mentor Graphics. In addition, to support trend analysis on the data, both studies followed the same format and questions (when possible) as the original 2002 and 2004 Collett studies.

In the fall of 2012, Mentor Graphics commissioned Wilson Research Group again to conduct a new functional verification study. This study was also a blind study and follows the same format as the Collett, Far West Research, and previous Wilson Research Group studies. The 2012 Wilson Research Group study is one of the largest functional verification studies ever conducted. The overall confidence level of the study was calculated to be 95% with a margin of error of 4.05%.

Unlike the previous Collett and Far West Research studies that were conducted only in North America, both the 2010 and 2012 Wilson Research Group studies were worldwide studies. The regions targeted were:

  • North America:Canada,United States
  • Europe/Israel:Finland,France,Germany,Israel,Italy,Sweden,UK
  • Asia (minusIndia):China,Korea,Japan,Taiwan
  • India

The survey results are compiled both globally and regionally for analysis.

Another difference between the Wilson Research Group and previous industry studies is that both of the Wilson Research Group studies also included FPGA projects. Hence for the first time, we are able to present some emerging trends in the FPGA functional verification space.

Figure 1 shows the percentage makeup of survey participants by their job description. The red bars represents the FPGA participants while the green bars represent the non-FPGA (i.e., IC/ASIC) participants.


Figure 1: Survey participants job title description

Figure 2 shows the percentage makeup of survey participants by company type. Again, the red bars represents the FPGA participants while the green bars represents the non-FPGA (i.e., IC/ASIC) participants.

Figure 2: Survey participants company description

In a future set of blogs, over the course of the next few months, I plan to present the highlights from the 2012 Wilson Research Group study along with my analysis, comments, and obviously, opinions. A few interesting observations emerged from the study, which include:

  1. FPGA projects are beginning to adopt advanced verification techniques due to increased design complexity.
  2. The effort spent on verification is increasing.
  3. The industry is converging on common processes driven by maturing industry standards.

A few final comments concerning the 2012 Wilson Research Group Study.  As I mentioned, the study was based on the original 2002 and 2004 Collett studies.  To ensure consistency in terms of proper interpretation (or potential error related to mis-interpretation of the questions), we have avoided changing or modifying the questions over the years—with the exception of questions that relate to shrinking geometries sizes and gate counts. One other exception relates  introducing a few new questions related to verification techniques that were not a major concern ten years ago (such as low-power functional verification).  Ensuring consistency in the line of questioning enables us to have high confidence in the trends that emerge over the years.

Also, the method in which the study pools was created follows the same process as the original Collett studies.  It is important to note that the data presented in this series of blogs does not represent trends related to silicon volume (that is, a few projects could dominate in terms of the volume of manufactured silicon and not represent the broader industry).  The data in this series of blogs represents trends related to the study pool—which is a fair proxy for active design projects.

My next blog presents current design trends that were identified by the survey. This will be followed by a set of blogs focused on the functional verification results.

Also, to learn more about the 2012 Wilson Reserach Group study, view my pre-recorded Functional Verification Study web-seminar, which is located out on the Verification Academy website.

Quick links to the 2012 Wilson Research Group Study results (so far…)

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