Sometimes the simple questions are the most vexing. That hit me this week while participating in a DesignCon panel in Santa Clara, moderated by EDN Executive Editor Ron Wilson.

The title seemed easy enough: “Getting to Design Quality Closure Without Compromising Productivity.”

But really, what IS quality? How do we define it?

My fellow panelist, Camille Kokozaki, president of Design Rivers, quipped “It’s like pornography: you know it when you see it.”

Piyush Sancheti, senior director of business development at Atrenta, came close:

“Quality is meeting the design objectives you have: whether it’s area, power, timing functionality, or, in a broader sense, customer expectations. Productivity is getting there.”

Sancheti then added:

“Being able to measure it (productivity) with tools like Numetrics is important because you want to hit your objectives as fast and effectively as possible.”

Not surprisingly, our panel wrestled with one of the big issues in design quality today: verification. It deeply affects design quality and productivity. Sancheti noted that for some teams, 70 percent of the entire design development is spent on verification.

What I see first hand from customers is they struggle to understand how verification affects their productivity. Some program managers I talk to say:

“I understand the scope of logic design and physical implementation. Verification is an unknown for me. If I give the verification team another two months, they’ll take it, but how do I know that we’re better off?”

So, I think we’re seeing that verification needs to come up with some sort of model of completion so people can move on. And that’s not easy. Our data shows that some companies toggle up the tape-outs as part of a larger verification strategy, but that can hurt overall productivity.

How we fix verification is a broader issue. Do we lean on formal methods at the architectural level as opposed to time- and engineering-consuming test vectors?

For now, our role is to help teams quantify their design effort, properly staff their projects, and understand where they stand with respect to the industry’s best teams. From there they can make fact-based decisions to drive productivity improvements.

That’s our contribution to the broader challenges of verification and design quality, but as we all know, it takes a village (and many future industry panels) to come up with the solution.

(Jeff is Numetrics’ director of professional services and product marketing).

Bright lights in a dimly lit DesignCon room: (L-R) Camille Kokozaki, Design Rivers; Piyush Sancheti, Atrenta; Jeff Eversmann, Numetrics; Michel Tabusse, Satin IP

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(Summary: As the recession’s pain recedes, semiconductor companies have an excellent opportunity to take advantage of the economic crisis to drive productivity improvements throughout their R&D organization.)

The line “never let a serious crisis go to waste” was made famous a year ago by White House chief of Staff Rahm Emanuel, who was speaking to business leaders. For the semiconductor industry emerging from a sharp recession, now is the time to capitalize on the motivation implicit in Emanuel’s quotation.

Consider, first off, the proven benefits that companies get when they take advantage of a recession. A Bain & Company study found that:

• Twice as many companies move from laggards to leaders during a downturn than they do during good times.
• The majority of those companies that take steps to make that move sustained their gains long after business came back.

For those that don’t, the numbers are discouraging:

• One-third of banks and two-fifths of big American industrial companies fell from the first quartile of their industries in the recession of 2001-02, according to a McKinsey study referenced in The Economist.

There’s plenty of advice for companies willing to take advantage of a business slump. Dave Jones and Pierre Loewe, writing on ChiefExecutive.net, advise managers to re-assess “unarticulated” customer needs and redraw their industry ecosystems.

I’d amplify another of their key points: buttress your core competency. Today’s semiconductor industry is a different place than it was before the recession. The search for differentiation in core competencies needs to be focused at product development. This is crucial for fabless companies that don’t have their own manufacturing to create differentiation. But it’s also important for formerly “fabbed” companies making the transition to fabless.

Out with the old?

Some semiconductor companies emerging from this recession will be tempted to apply old templates to new designs. With understandable caution about hiring more engineers in the short-term, the tendency will be to do more with less—to demand more products faster with fewer engineers.

What will happen?

Unrealistic schedules and budget overshoot, for one thing. For another, the urge to crank out more products to take advantage of resuscitated demand will lead to portfolio-management problems.

It doesn’t have to be this way. Productivity improvements and best practices are commonplace in manufacturing; there’s no reason they can’t be employed in R&D. It would be a shame to waste a golden opportunity to exploit this moment in history, and, to finish Emanuel’s quotation, to take the “opportunity to do things you think you could not do before.”

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The concept seems simple: The more ip blocks you re-use in an IC or system design, the faster and more productively you’ll get your design done. The ITRS roadmap began identifying the benefits as long ago as 1997, showing the industry could reasonably expect 56,000 gates per designer per year when using large ip blocks (75,000-1 million gates). By 2007 that figure was up to 600,000 gates per designer per year, a tenfold increase.

There’s no doubt design reuse is here to stay. In 2007, a third of all logic was reused design blocks. That’s expected to rise to nearly 50 percent by 2015, according to the ITRS.

The numbers and the theory behind it are encouraging, but reality is much different. Making 30 percent of your design from reused IP blocks doesn’t mean you’re going to be 30 percent more productive at the end of the project. That’s because IC design teams tend to underestimate the work needed to implement the reused IP. This can cause project delays and missed market opportunities.

The challenge is that it’s very difficult to estimate design complexity, especially the impact of reuse. IC design schedules can falter because of the inability to estimate the impact of IP modifications on project effort.

Even a small percentage of reuse can add outsized effort to a development project. For example, if you add one new block of 600,000 gates to a 6 million-gate design, you’re adding 10 percent to the IC but increasing the effort required on the project by 24 percent. Adding 10 percent new circuitry to all blocks in that 6 million-gate design—with 90 percent of each block being re-used—doubles the effort required on the project, even though it increases the IC size by just 10 percent to 6.6 million gates.

This issue will be part of a larger discussion Dec. 1 at IP-ESC 2009 in Grenoble. We were invited to sit on a panel—“IP Reuse vs. IP Leverage: What’s the difference, and what are the issues?”—with Kathryn Kranen, CEO of Jasper Design Automation, and Olivier Haller, who manages the design verification team in the Functional Verification Group at STMicroelectronics. Our director of professional services, Andrea Fortunato, will represent Numetrics.

This is a well-timed panel in my opinion because re-use is an issue that transcends the industry and is crucial for its future. And how we go about optimizing design re-use is crucial to manage today.

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By Ron Collett

(Summary: As the semiconductor industry emerges from the recession, new ways of thinking are emerging as well to improve what’s becoming a new differentiator for companies: IC design development.)

All indications are the semiconductor industry is rebounding from the painful recession of the past couple of years. The latest upbeat data points include:

• Worldwide third-quarter PC microprocessor unit shipments rose 23% compared to the second quarter, reaching a new all-time high, according to market research firm International Data Corp. (IDC).
• Chip-sales growth should be 10 percent in 2010 and 8.4 percent in 2011, according to the Semiconductor Industry Association. The decline in 2009 chip sales (down 11.6 percent is now less that earlier forecast).
• Individually, companies like Marvell, TSMC and ON Semiconductor are reporting encouraging results.

But, as they say, there’s good news and bad news. The good news is obvious. The bad news is more subtle: Companies are beginning to crank up the product-development dial significantly, and this can become a challenge for R&D organizations.

As a surge of new projects occurs, hiring generally is slow to catch up to demand. This puts stress on engineering organizations. Schedules are difficult to predict, and the engineers can get shifted from one product development team to another in the race to make deadlines. Managing a portfolio of products turns into a torch-juggling exercise—spectacular to watch but done with the knowledge that the risk is high.

This is a significant problem in the fables era—a time in which IC design development is an increasingly important source of differentiation for semiconductor companies. A sudden burst of product-development activity can bring R&D organizations to their knees.

Design development productivity is something to consider as we emerge from this recession. The stakes are high, and there’s little room for error in marshalling engineering resources to get products to market quickly.

All recessions force change on business, and this one is no exception. Old ways of doing things are being replaced by new thinking on productivity—all with an eye toward making “up and to the right” last.

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(Summary: We inevitably get questions about Numetrics’ technology after webinars or live event presentations, and we’d like to share some of them in the spirit of helping you understand more about our products and solutions. Here are answers to several recent questions in the virtual mail bag).

Q: How do you define productivity?

A: We calculate complexity of the project and we divide the complexity units by total number of person weeks required to get that product out to volume production. That quotient gives you the productivity number. The typical range is 500 on the low end for a large team to 3000 for a small team.

There’s another measure, which is throughput, and throughput is complexity units per week. That’s a measure of normalized cycle team. Productivity is efficiency of the team and higher number is better.

Q: I’ve heard that in some sectors productivity decreases as team size increases. Is this true in semiconductor product development?

A: It’s a universal effect across pretty much any activity that has to do with building things. When you build larger teams, each person is doing a smaller and smaller slice of the overall work. More work has to be split apart and then put back together. Bigger teams equal more meetings and more management required. It’s universal and it’s inevitable. With the Numetrics approach, you can minimize this effect—decreasing productivity curve is flatter than it would otherwise be.

Q: It’s impossible to predict in a design project how many times customer requirements will change, when your EDA tools go buggy or if a key contributor leaves the team. So how do you quantify schedule risk with so many unpredictable variables?

A: The simple answer is our tools don’t predict things. You have a draw a line between statistical analysis and a crystal ball.

What Numetrics’ tools do is take your inputs of design parameters and measure them against the history of more than 1,500 design projects over eight generations of technology evolution (here’s a link to a demo of our tools). Using the data from those hundreds and hundreds of designs, this builds in realistic effort required to deal with those issues. It’s a way of contingency planning.

Think of it like yield modeling. You know that on each wafer a certain number of dice will fall out. Yield modeling doesn’t tell you which particle is going to hit which die and where. But they give you an accurate assessment of how your design will yield. Numetrics is like a yield model for project plans. It’s saying there’s a certain probability that if you’re going to try to achieve these targets, given what you’ve input you’re going to fail.

It allows you to make a quantitative assessments. It’s a probability model. It’s not a crystal ball.

Q: How does the complexity calculation model handle predictions for newer nodes, such as 45 and 32nm?

A: Numetrics’ IC Industry Database has collected information for eight technology generations. The technology shifts from one generation to another have been observed before. And what we’ve observed is that early users of technology nodes face considerably more complexity than later users of the same node, once the models and such are more stable. The equation has calibrated this effect which repeats from generation to generation. We’ve been able to model what the effect of the extra technology of a new node will be on a new design.

Q: Can your tools get data from existing sources or do I have to input it manually?

A: We’re dealing with milestones, staffing information and complexity information. Typically this information is copy-pasted from existing sources or customers are using XML import to get data into our tools.

(Alex is Numetrics’ director of professional services).

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By Ron Collett

The increase in semiconductor design complexity never slows. This reality always reinforces itself when I look at the agenda of a given week’s technology event. This week’s headliner is ARM Techcon3 in Santa Clara.

Here’s a sampling of the presentations:

• “How Software and Hardware Can Cooperate To Manage Power Consumption in ARM-based Systems”
• “Fireside Chat: Enabling Internet Eveywhere and Advancing Next-Generation Designs”
• “Energy Efficient Design at 65nm – What Really Works!”

And the list goes on—challenging design issues at complex technology nodes everywhere you look. It’s little wonder then that most semiconductor design projects slip schedule (see chart).

Old habits in a mature industry die hard. Engineers have built products in more or less the same way for 40 years, and they’ve had tremendous market success. So why change? Engineering intuition always seems to work, and a bottom-up approach to project staffing is the way we’ve always done things. No reason to change, right?

Wrong.

Projects slip for a number of reasons:

• We’re human. Who can predict when or if a spec change might occur or the flu takes out a few key engineers for a week?
• We often lack the context to make fact-based decisions for dizzingly complex designs. For example, if you’ve spread a design over three locations in different time zones, using a newly-acquired team designing to a new process, you’re trying to extrapolate the effect of those factors based on your experience. But you probably have never experienced those factors before because each design is different.
• Projects are late often because they are under-scoped. The schedule for the new project is based largely on the post-mortem of the last project, with the conclusion that none of the things that went wrong last time will be allowed to go wrong this time (and no other major new challenges will be allowed to creep in!).

Typical bottom-up reactions to managing such complexity tend to fall into two categories:

• Boost staff to hit schedule. This generally creates either a low-productivity, low-throughput situation or a high-throughput, low-productivity environment. Teams might hit schedule but will blow out the budget.
• Leverage a small, skilled team of engineers and drive it hard. This can marshal costs and improve decision-making, but a small team can produce only so much in a given period of time, even if it’s highly productive. Too much pressure to hit an unrealistic schedule also kills morale.

Sharp engineering managers can achieve best in class and cut or eliminate schedule slip by adopting a top-down approach that complements their traditional bottom-up planning. The top-down methodology uses:

• Quantified estimates of the chip’s complexity
• The team’s productivity
• A model of the rate at which effort will be expended on the project.

With the proper infrastructure in place, schedule estimates can be generated within just a few hours. At this point you can benchmark against your own experience or against the industry’s experience and make fact-based what-if tradeoffs to boost your schedule predictability and design ROI.

More than 80 percent of semiconductor projects slip schedule. But we can change this reality. You wouldn’t expect this from your foundry, would you? Your foundry partner gives you a precise estimate of yield on your chip based on its models and its vast experiences with similar projects. You should expect the same predictability from your product-development organization.

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By Ron Collett

For the semiconductor industry, there not only is change in the air, there’s thoughtful debate about just what that change looks like.

I’ve been mulling over a couple of intriguing posts, one by another newly minted industry blogger, Sanjay Srivastava, CEO of Denali, and the other on EDN by Kaben Wireless Silicon CEO Paul Slaby.

In Sanjay’s blog, Conversation on Innovation, he’s been mulling how fabless semiconductor startups can survive in the current climate.

He argues (in Funding Fabless Semiconductor Startups) that solutions need to look at how and where money is invested, how we “stage” investments (i.e. valuing investments in IP differently than in silicon) and how we address software investment:

I believe if we get creative about the current fabless investment model, not every semiconductor opportunity needs to be a billion-dollar opportunity before it can attract meaningful investment.

In his EDN post and in a separate webcast, Slaby argues for a “semi-fabless” model:

The semi-fabless company is essentially a combination of an IP provider, a design house, and an outsourced R&D operation. Its core competence and strength lies in specialized R&D and product development capabilities whereas it outsources product delivery operations to the ‘old’ fabless company with the entire infrastructure and the pipeline to market already in place.

There’s no doubt the investment formula needs to be reconsidered. For a semiconductor company to break even, it needs $40-$100 million and six to eight years. More troubling, however, is the selling price of semiconductor startups has been steadily declining. In 2007 it was $160 million; in 2008 it was $95 million and in 2009 the average has been $65 million, according to an EE Times story referencing Lip-Bu Tan, chairman of Walden International, and now CEO of Cadence.

The good thing is there are a lot of “smartest guys in the room” in this industry, and collectively we’re shaping the industry’s future in three main ways:

• Companies are differentiating on products

• Executives, such as Sanjay and Paul and others, are helping drive the investment conversation

• And companies like ours are illuminating the differentiation and benefits of focusing on product-development productivity—fabless companies’ key differentiator today—and overall portfolio management.

This new differentiation is key; it’s key to how companies grow and gain market share and it’s key to the industry’s future.

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(Summary: For semiconductor companies, differentiation has shifted from manufacturing to improving productivity in new-product development. That realization is the easy part; getting there requires help.)

By Ron Collett

I’m always impressed with the level of optimism I find at semiconductor industry events around the world. There may be pockets of gloom about the state of the semiconductor industry, but executives certainly don’t share it. Yes, it’s not the same industry it was 10 years ago, but, no, it’s not doomed. Far from it: The dynamics are just different.

That was my message when I presented last week at Malcolm Penn’s International Electronics Forum in Geneva. Here’s why the dynamics are different:

• The industry head count has shrunk 30 percent this decade
• Industry consolidation has picked up pace
• Cost-cutting is rampant
• There’s more pressure than ever on design teams to get great products out the door on time and on budget

Here’s how the dynamics are different: Differentiation has shifted as industry disaggregation has reached an end state. There was a time when a semiconductor company differentiated itself through manufacturing and process technology (or way back when, through making its own steppers!) No longer.

So where’s the differentiation? It’s not in cost-cutting. Everyone’s doing that.

Differentiation has shifted to the heart of the semiconductor company’s value proposition: its new-product development.

Electronics Weekly’s David Manners, in his coverage of IEF last week (“What’s the Answers to the Chip Industry’s Problems? Ask IEF”), touched on how profound this can be. He quoted Alain Dutheil, CEO of ST-Ericsson, as saying 85 percent of his 8,000 employees are in R&D.

The other part of the story, which we’ve blogged about, is that most SOC projects slip schedule and most IC teams tend to underestimate their product R&D costs.

That brings me back to our IEF presentation (“Raising the Bar on Semiconductor R&D Management, Execution, and ROI”), which we created in partnership with PRTM, one of the world’s premier operational strategy consulting firms (with deep ties to the IC industry).

Our three take-aways were:

• The bar is being significantly raised on semiconductor R&D management, execution, and achieving ROI
• Companies must continuously progress through the stages of maturity to thrive (functional, project, portfolio, and cross-enterprise excellence)
• Fact-based planning is a critical foundation for ongoing NPD success

Anyone can cut costs in challenging times but winning companies find news ways to differentiate themselves, and they are the companies that come out of recessions stronger than their competition.

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Underestimating the complexity of an SOC semiconductor design project is a growing problem in our industry. In an era where SOC projects cost tens of millions of dollars to complete, a week of schedule slip means $1 million or more in lost revenue potential. That’s unacceptable.

That was my main point last week during a panel I participated on that was part of the EE Times SOC Virtual Conference.

Former EE Times EDA Editor Richard Goering, now blogging for Cadence, captured the panel well in a post this week (Are SoC Development Costs Significantly Underestimated?).

To justify the investment in an SoC, Collett said, the available revenue stream must be 10X the development costs. Thus, if an SoC has a $500 million market opportunity, development costs should not exceed $50 million. Today, however, development costs can easily reach $40 to $80 million. Collett noted that 60 percent of this cost is labor and that the major part of the overall development cost is verification.

Richard, with a great comparison, went on to write:

Anyone who has ever been involved in a home remodeling project knows how hard it is to get a reliable estimate up front of how long it will take and how much it will cost. Underestimating time and cost is commonplace. A large SoC design project is far more complex, with many more stakeholders. There is no simple answer to the question of how development costs can be accurately predicted. But there are some ideas about how to lower development costs.

Tensilica CTO Grant Martin weighed in from the IP perspective, Xilinx VP of Product Development Steve Douglass offered the FPGA perspective, and ASIC designer Sven Andersson from Realtime Embedded AB talked about the value of verified IP blocks. It was a great conversation, and you can hear it in archived form by registering for the event.

There’s some additional information about the panel (we tweeted some highlights during the panel) that have been cataloged under the hash tag #eetsoc.And we’ve published a helpful white paper on how to measure IC development productivity in our online library.

Time really is money in the semiconductor industry, and quantifying schedule risk is an excellent way to maximize your engineering investments.

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Big changes are occurring before our eyes in the semiconductor world. And while you might say that the industry always has been in a state of flux, understanding the nature of today’s changes is key; reacting properly to that understanding is imperative.

What’s new? In short, it’s a shift in focus: The long transition toward the fabless model is almost complete. With the numbers of semiconductor companies doing their own manufacturing dwindling to a handful, the time has come for executives and engineering managers to figure out where their differentiation now lies within their companies.

Manufacturing used to be one of those differentiators. But today, with everyone buying manufacturing services from TSMC, UMC, Chartered or other foundries, there’s very little differentiation in how ICs are manufactured. But there can be enormous differentiation and value in how they’re designed.

How is this possible, in a world of well-established design-automation tools and methodologies? One approach is to bring more predictability and productivity to design projects and teams; to help engineering managers get insightful, relevant data early in the design decision-making process; and to enable a portfolio of designs to be centrally managed efficiently. That’s our business, and it’s a topic I’ll explore in detail this Wednesday (Sept. 16) during EE Times’ SoC Virtual Conference.

I’ll be presenting on a panel (Economics of Next-Generation SOC Design: A Node Too Far? 2-3 p.m. PDT) with Grant Martin, chief scientist, Tensilica; Steve Douglass, vice president, product development, Xilinx; and Sven Andersson, ASIC FPGA designer, Realtime Embedded AB. The panel will be moderated by EE Times’ Online Editor Dylan McGrath.

If you want a peek at some of what will inform my presentation, take a look at our Numetrics solutions page for starters. And then think about the implications of these two statistics:

* 60 percent of IC projects slip at least one quarter.

* 16 percent of IC projects slip more than one year.

I hope to see you live Wednesday during the virtual panel!

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