As a leading venture capitalist in the electronics technology, as well as CEO of Cadence, Lip-Bu Tan has unique insights into ongoing changes that will impact EDA providers and users. Tan shared some of those insights in a “fireside chat” with Ed Sperling, editor in chief of Semiconductor Engineering, at the Design Automation Conference (DAC 2015) on June 9.

Topics of this discussion included industry consolidation, the need for more talent and more startups, Internet of Things (IoT) opportunities and challenges, the shift from ICs to full product development, and the challenges of advanced nodes. Following are some excerpts from this conversation, held at the DAC Pavilion theater on the exhibit floor.

Ed Sperling (left) and Lip-Bu Tan (right) discuss trends in semiconductors and EDA

Q: As you look out over the semiconductor and EDA industries these days, what worries you most?

Tan: At the top of my list is all the consolidation that is going on. Secondly, chip design complexity is increasing substantially. Time-to-market pressure is growing and advanced nodes have challenges.

The other thing I worry about is that we need to have more startups. There’s a lot of innovation that needs to happen. And this industry needs more top talent. At Cadence, we have a program to recruit over 10% of new hires every year from college graduates. We need new blood and new ideas.

Q: EDA vendors were acquiring companies for many years, but now the startups are pretty much gone. Where does the next wave of innovation come from?

Tan: I’ve been an EDA CEO for the last seven years and I really enjoy it because so much innovation is needed. System providers have very big challenges and very different needs. You have to find the opportunities and go out and provide the solutions.

The opportunities are not just in basic tools. Massive parallelism is critical, and the power challenge is huge. Time to market is critical, and for the IoT companies, cost is going to be critical. If you want to take on some good engineering challenges, this is the most exciting time.

Q: You live two lives—you’re a CEO but you’re also an investor. Where are the investments going these days and where are we likely to see new startups?

Tan: Clearly everybody is chasing the IoT. There is a lot of opportunity in the cloud, in the data center. Also, I’m a big believer in video, so I back companies that are video related. A big area is automotive. ADAS [Advanced Driver Assistance Systems] is a tremendous opportunity.

These companies can help us understand how the industry is transforming, and then we can provide solutions, either in terms of IP, tools, or the PCB. Then we need to connect from the system level down to semiconductors. I think it’s a different way to design.

Q: What happens as we start moving from companies looking to design a semiconductor to system companies who are doing things from the perspective that we have this purpose for our software?

Tan: We are extending from EDA to what we call system design enablement, and we are becoming more application driven. The application at the system level will drive the silicon design. We need to help companies look at the whole system including the power envelope and signal integrity. You don’t want to be in a position where you design a chip all the way to fabrication and then find the power is too high.

We help the customers with hardware/software co-design and co-verification. We have a design suite and a verification suite that can provide customers with high-level abstractions, as well as verify IP blocks at the system level. Then we can break things down to the component level with system constraints in mind, and drive power-aware, system-aware design.

We are starting to move into vertical markets. For example, medical is a tremendous opportunity.

Q: How does this approach change what you provide to customers?

Tan: Every year I spend time meeting with customers. I think it is very important to understand what they are trying to design, and it is also important to know the customer’s customer requirements. We might say, “Wait a minute, for this design you may want to think about power or the library you’re using.” We help them understand what foundry they should use and what process they should use. They don’t view me as a vendor—they view me as a partner.

We also work very closely with our IP and foundry partners. We work as one team—the ultimate goal is customer success.

Q: Is everybody going to say, FinFETs are beautiful, we’re going to go down to 10nm or 7nm—or is it a smaller number of companies who will continue down that path?

Tan: Some of the analog/mixed-signal companies don’t need to go that far. We love those customers—we have close to 50% of that business. But we also have customers in the graphics or processor area who are really pushing the envelope, and need to be in 16nm, 14nm, or 10nm. We work very closely with those guys to make sure they can go into FinFETs.

We always want to work with the customer to make sure they have a first-time silicon success. If you have to do a re-spin, you miss the opportunity and it’s very costly.

Q: There’s a new market that is starting to explode—IoT. How real is that world to you? Everyone talks about large numbers, but is it showing up in terms of tools?

Tan: Everybody is talking about huge profits, but a lot of the time I think it is just connecting old devices that you have. Billions of units, absolutely yes, but if you look close enough the silicon percentage of that revenue is very tiny. A lot of the profit is on the service side. So you really need to look at the service killer app you are trying to provide.

What’s most important to us in the IoT market is the IP business. That’s why we bought Tensilica—it’s programmable, so you can find the killer app more quickly. The other challenges are time to market, low power, and low cost.

Q: Where is system design enablement going? Does it expand outside the traditional market for EDA?

Tan: It’s not just about tools. IP is now 11% of our revenue. At the PCB level, we acquired a company called Sigrity, and through that we are able to drive system analysis for power, signal integrity, and thermal. And then we look at some of the verticals and provide modeling all the way from the system level to the component level. We make sure that we provide a solution to the end customer, rather than something piecemeal.

Q: What do you think DAC will look like in five years?

Tan: It’s getting smaller. We need to see more startups and innovative IP solutions. I saw a few here this year, and that’s good. We need to encourage small startups.

Q: Where do we get the people to pull this off? I don’t see too many people coming into EDA.

Tan: I talk to a lot of university students, and I tell them that this small industry is a gold mine. A lot of innovation is needed. We need them to come in [to EDA] rather than join Google or Facebook. Those are great companies, but there is a lot of fundamental physical innovation we need.

Richard Goering

Related Blog Posts

- Gary Smith at DAC 2015: How EDA Can Expand Into New Directions

- DAC 2015: Google Smart Contact Lens Project Stretches Limits of IC Design

- Q&A with Nimish Modi: Going Beyond Traditional EDA

Design and verification standards are critical if we want to get a new generation of Internet of Things (IoT) devices into the market, according to panelists at an Accellera Systems Initiative breakfast at the Design Automation Conference (DAC 2015) June 9. However, IoT devices for different vertical markets pose very different challenges and requirements, making the standards picture extremely complicated.

The panel was titled “Design and Verification Standards in the Era of IoT.” It was moderated by industry editor John Blyler, CEO of JB Systems Media and Technology. Panelists were as follows, shown left to right in the photo below:

• Lu Dai, director of engineering, Qualcomm
• Wael William Diab, senior director for strategy marketing, industry development and standardization, Huawei
• Chris Rowen, CTO, IP Group, Cadence Design Systems, Inc.

In opening remarks, Blyler recalled a conversation from the recent IEEE International Microwave Symposium in which a panelist pointed to the networking and application layers as the key problem areas for RF and wireless standardization. Similarly, in the IoT space, we need to look “higher up” at the systems level and consider both software and hardware development, Blyler said.

Rowen helped set some context for the discussion by noting three important points about IoT:

• IoT is not a product segment. Vertical product segments such as automotive, medical devices, and home automation all have very different characteristics.
• IoT “devices” are components within a hierarchy of systems that includes sensors, applications, user interface, gateway application (such as cell phone), and finally the cloud, where all data is aggregated.
• A bifurcation is taking place in design. We are going from extreme scale SoCs to “extreme fit” SoCs that are specialized, low energy, and very low cost.

Here are some of the questions and answers that were addressed during the panel discussion.

Q: The claim was recently made that given the level of interaction between sensors and gateways, 50X more verification nodes would have to be checked for IoT. What standards need to be enhanced or changed to accomplish that?

Rowen: That’s a huge number of design dimensions, and the way you attack a problem of that scale is by modularization. You define areas that are protected and encapsulated by standards, and you prove that individual elements will be compliant with that interface. We will see that many interesting problems will be in the software layers.

Q: Why is standardization so important for IoT?

Dai: A company that is trying to make a lot of chips has to deal with a variety of standards. If you have to deal with hundreds of standards, it’s a big bottleneck for bringing your products to market. If you have good standardization within the development process of the IC, that helps time to market.

When I first joined Qualcomm a few years ago, there was no internal verification methodology. When we had a new hire, it took months to ramp up on our internal methodology to become effective. Then came UVM [Universal Verification Methodology], and as UVM became standard, we reduced our ramp-up time tremendously. We’ve seen good engineers ramp up within days.

Diab: When we start to look at standards, we have to do a better job of understanding how they’re all going to play with each other. I don’t think one set of standards can solve the IoT problem. Some standards can grow vertically in markets like industrial, and other standards are getting more horizontal. Security is very important and is probably one thing that goes horizontally.

Requirements for verticals may be different, but processing capability, latency, bandwidth, and messaging capability are common [horizontal] concerns. I think a lot of standards organizations this year will work on horizontal slices [of IoT].

Q: IoT interoperability is important. Any suggestions for getting that done and moving forward?

Rowen: The interoperability problem is that many of these [IoT] devices are wireless. Wireless is interesting because it is really hard – it’s not like a USB plug. Wireless lacks the infrastructure that exists today around wired standards. If we do things in a heavily wireless way, there will be major barriers to overcome.

Dai: There are different standards for 4G LTE technology for different [geographical] markets. We have to make a chip that can work for 20 or 30 wireless technologies, and the cost for that is tremendous. The U.S., Europe, and China all have different tweaks. A good standard that works across the globe would reduce the cost a lot.

Q: If we’re talking about the need to define requirements, a good example to look at is power. Certainly you have UPF [Unified Power Format] for the chip, board, and module.

Rowen: There is certainly a big role for standards about power management. But there is also a domain in which we’re woefully under-equipped, and that is the ability to accurately model the different power usage scenarios at the applications level. Too often power devolves into something that runs over thousands of cycles to confirm that you can switch between power management levels successfully. That’s important, but it tells you very little about how much power your system is going to dissipate.

Dai: There are products that claim to be UPF compliant, but my biggest problem with my most recent chip was still with UPF. These tools are not necessarily 100% UPF compliant.

One other concern I have is that I cannot get one simulator to pass my Verilog code and then go to another that will pass. Even though we have a lot of tools, there is no certification process for a language standard.

Q: When we create a standard, does there need to be a companion compliance test?

Rowen: I think compliance is important. Compliance is being able to prove that you followed what you said you would follow. It also plays into functional safety requirements, where you need to prove you adhered to the flow.

Dai: When we [Qualcomm] sell our 4G chips, we have to go through a lot of certifications. It’s often a differentiating factor.

Q: For IoT you need power management and verification that includes analog. Comments?

Rowen: Small, cheap sensor nodes tend to be very analog-rich, lower scale in terms of digital content, and have lots of software. Part of understanding what’s different about standardization is built on understanding what’s different about the design process, and what does it mean to have a software-rich and analog-rich world.

Dai: Analog is important in this era of IoT. Analog needs to come into the standards community.

Richard Goering

Cadence Blog Posts About DAC 2015

Gary Smith at DAC 2015: How EDA Can Expand Into New Directions

DAC 2015: Google Smart Contact Lens Project Stretches Limits of IC Design

DAC 2015: Lip-Bu Tan, Cadence CEO, Sees Profound Changes in Semiconductors and EDA

DAC 2015: “Level of Compute in Vision Processing Extraordinary” – Chris Rowen

DAC 2015: Can We Build a Virtual Silicon Valley?

DAC 2015: Cadence Vision-Design Presentation Wins Best Paper Honors

Let’s face it – the EDA industry needs new people and new ideas. One of the best places to find both is academia, and a presentation at the Cadence Theater at the recent Design Automation Conference (DAC 2015) described collaboration models that are working today.

The presentation was titled “Industry/Academia Engagement Models – From PhD Contests to R&D Collaborations.” It included these speakers, shown from left to right in the photo below:

• Prof. Xin Li, Electrical and Computer Engineering, Carnegie-Mellon University (CMU)
• Chuck Alpert, Senior Software Architect, Cadence
• Prof. Laleh Behjat, Department of Electrical and Computer Engineering, University of Calgary

Alpert, who was filling in for Zhuo Li, Software Architect at Cadence, was the vice chair of DAC 2015 and will be the general chair of DAC 2016 in Austin, Texas. “My team at Cadence really likes to collaborate with universities,” he said. “We’re a big proponent of education because we really need the best and brightest students in our industry.”

Contests Boost EDA Research

One way that Cadence collaborates with academia is participation in contests. “It’s a great way to formulate problems to academia,” Alpert said. “We can have the universities work on these problems and get some strategic direction.”

For example, Cadence has been involved with the annual CAD contest at the International Conference on Computer-Aided Design (ICCAD) since the contest was launched in 2012. This is the largest worldwide EDA R&D contest, and it is sponsored by the IEEE Council on EDA (CEDA) and the Taiwan Ministry of Education. Its goals are to boost EDA research in advanced real-world problems and to foster industry-academia collaboration.

Contestants can participate in one of more problems in the three areas of system design, logic synthesis and verification, and physical design. The 2015 contest has attracted 112 teams from 12 regions. Cadence contributes one problem per year in the logic synthesis area. Zhuo Li was the 2012 co-chair and the 2013 chair. The awards will be given at ICCAD in November 2015.

Another step that Cadence has taken, Alpert said, is to “hire lots of interns.” His own team has four interns at the moment. One advantage to interning at Cadence, he said, is that students get to see real-world designs and understand how the tools work. “It helps you drive your research in a more practical and useful direction,” he said.

The Cadence Academic Network co-sponsors the ACM SIGDA PhD Forum at DAC, and Xin Li and Zhuo Li are on the organizing committee. This event is a poster session for PhD students to present and discuss their dissertation research with people in the EDA community. This year’s forum was “packed,” Alpert said, and it’s clear that the event needs a bigger room.

Finally, Alpert noted, Cadence researchers write and publish technical papers at DAC and other conferences, and Cadence people serve on the DAC technical program committee. “We try to be involved with the academic community on a regular basis,” Alpert said. “We want the best and the brightest people to go into EDA because there is still so much innovation that’s needed. It’s a really cool place to be.”

Research Collaboration Exposes Failure Rates

Xin Li presented an example of a successful research collaboration between CMU and Cadence. The challenge was to find a better way to estimate potential failure rates in memory. As noted in a previous blog post, PhD student Shupeng Sun met this challenge with a new statistical methodology that won a Best Poster award at the ACM SIGDA PhD Forum at DAC 2014.

The new methodology is called Scaled-Sigma Sampling (SSS). It calculates the failure rate and accounts for variability in the manufacturing process while only requiring a few hundred, or a few thousand, sample circuit blocks. Previously, millions of samples were required for an accurate validation of a new design, and each sample could take minutes or hours to simulate. It could take a few weeks or months to run one validation.

The SSS methodology requires greatly reduced simulation times. It makes it possible, Li noted, to run simulations overnight and see the results in the morning.

Li shared his secret for success in collaborations. “I want to emphasize that before the collaboration, you have to understand the goal. If you don’t have a clear goal, don’t collaborate. Once you define the goal, stick to it and make it happen.”

Contest Provides Learning Experience

Last year Laleh Behjat handed two of her new PhD students a challenge. “I told them there is an ISPD [International Symposium for Physical Design] contest on placement, and I expect you to participate and I expect you to win. Not knowing anything about placement, I don’t think they realized what I was asking them.”

The 2015 contest was called the Blockage-Aware Detailed Routing-Driven Placement Contest. Results were announced at the end of March at ISPD. And the University of Calgary team, despite its lack of placement experience, took second place.

Such contests provide a good learning tool, according to Behjat. Graduate students in EDA, she said, “have to be good programmers. They have to work in teams and be collaborative, be able to innovate, and solve the hardest problems I have seen in engineering and science. And they have to think outside the box.” A contest can bring out all these attributes, she said.

Further, Behjat noted, contest participants had access to benchmarks and to a placement tool. They didn’t have to write tools to find out if their results were good. Industry sponsors, meanwhile, got access to good students and new approaches for solving problems.

“You can see Cadence putting a big amount of time, effort and money to get students here and get them excited about doing contests,” she said. She advised students in the theater audience to “talk to people in the Cadence booth and see if you can have more ideas for collaboration.”

Richard Goering

Related Blog Posts

EDA Plus Academia: A Perfect Game, Set and Match

Cadence Aims to Strengthen Academic Partnerships

BSIM-CMG FinFET Model – How Academia and Industry Empowered the Next Transistor

EDA investor and former executive Jim Hogan is optimistic about automotive electronics, but he has some concerns as well. At the recent Design Automation Conference (DAC 2015), he delivered a speech titled “The Looming Quality, Reliability, and Safety Crisis in Automotive Electronics...Why is it and what can we do to avoid it?"

Hogan gave the keynote speech for IP Talks!, a series of over 30 half-hour presentations located at the ChipEstimate.com booth. Presenters included ARM, Cadence, eSilicon, Kilopass, Sidense, SilabTech, Sonics, Synopsys, True Circuits, and TSMC. Held in an informal setting, the talks addressed the challenges faced by SoC design teams and showed how the latest developments in semiconductor IP can contribute to design success.

Jim Hogan delivers keynote speech at DAC 2015 IP Talks!

Hogan talked about several phases of automotive electronics. These include assisted driving to avoid collisions, controlled automation of isolated tasks such as parallel parking, and, finally, fully autonomous vehicles, which Hogan expects to see in 15 to 20 years. The top immediate priorities for automotive electronics designers, he said, will be government regulation, fuel economy, advanced safety, and infotainment.

More Code than a Boeing 777

According to Hogan, today’s automobiles use 50-100 microcontrollers per car, resulting in a worldwide automotive semiconductor market of around $40 billion. The global market for advanced automotive electronics is expected to reach $240 billion by 2020. Software is growing faster in the automotive market than it is in smartphones. Hogan quoted a Ford vice president who observed that there are more lines of code in a Ford Fusion car than a Boeing 777 airplane.

One unique challenge for automotive electronics designers is long-term reliability. This is because a typical U.S. car stays on the road for 15 years, Hogan said. Americans are holding onto new vehicles for a record 71.4 months.

Another challenge is regulatory compliance. Aeronautics is highly regulated from manufacturing to air traffic control, and the same will probably be true of automated cars. Hogan speculated that the Department of Transportation will be the regulatory authority for autonomous cars. Today, automotive electronics providers must comply with the ISO26262 automotive functional safety specification.

So where do we go from here? “We’ve got to change our mindset,” Hogan said. “We’ve got to focus on safety and reliability and demand a different kind of engineering discipline.” You can watch Hogan’s entire presentation by clicking on the video icon below, or clicking here. You can also watch other IP Talks! videos from DAC 2015 here.

https://youtu.be/qL4kAEu-PNw

Richard Goering

Related Blog Posts

DAC 2015: See the Latest in Semiconductor IP at “IP Talks!”

Automotive Functional Safety Drives New Chapter in IC Verification

In 1985, as a relatively new editor at Computer Design magazine, I was asked to go forth and cover a new business called CAE (computer-aided engineering). I knew nothing about it, but I had been writing about design for test, so there seemed to be somewhat of a connection. Little did I know that “CAE” would turn into “EDA” and that I’d write about it for the next 30 years, for Computer Design, EE Times, Cadence, and a few others.

Now that I’m about to retire, I’m looking back over those 30 years. What a ride it has been! By the numbers I covered 31 Design Automation Conferences (DACs), hundreds of new products, dozens of acquisitions and startups, dozens of lawsuits, and some blind alleys that didn’t work out (like “silicon compilation”). Chip design went from gate arrays and PLDs with a few thousand gates to processors and SoCs with billions of transistors.

In 1985 there were three big CAE vendors – Daisy Systems, Mentor Graphics, and Valid Logic. All sold bundled packages that included workstations and CAE software; in fact, Daisy and Valid designed and manufactured their own workstations. In the early 1980s a workstation with schematic capture and gate-level logic simulation might have set you back $120,000. In 1985 OrCAD, now part of Cadence, came out with a $500 schematic capture package running on IBM PCs.

Cadence and Synopsys emerged in the late 1980s, and by the 1990s the EDA industry was pretty much a software-only business (apart from specialized machines like simulation accelerators). Since the early 1990s the “big three” EDA vendors have been Cadence, Synopsys, and Mentor, giving the industry stability but allowing for competition and innovation.

Here, in my view, are some of the highlights that occurred during the past 30 years of EDA.

EDA is a Highlight

The biggest highlight in EDA is the existence of a commercial EDA industry! Marching hand in hand with the fabless semiconductor revolution, commercial EDA made it possible for hundreds of companies to design semiconductors, as opposed to a small handful that could afford large internal CAD operations and fabs. With hundreds of semiconductor companies as opposed to a half-dozen, there’s a lot more creativity, and you get the level of sophistication and intelligence that you see in your smartphone, video camera, tablet, gaming console, and car today.

CAE + CAD = EDA. This is not just a terminology issue. By the mid-1980s it became clear that front-end design (CAE) and physical design (CAD) belonged together. The big CAE vendors got involved in IC and PCB CAD, and presented increasingly integrated solutions. People got tired of writing “CAE/CAD” and “EDA” was born.

The move from gate-level design to RTL. This move happened around 1990, and in my view this is EDA’s primary technology success story during the past 30 years. Moving up in abstraction made the design and verification of much larger chips possible. Going from gate-level schematics to a hardware description language (HDL) revolutionized logic design and verification. Which would you rather do – draw all the gates that form an adder, or write a few lines of code and let a synthesis tool find an adder in your chosen technology?

Two developments made this shift in design possible. One was the emergence of commercial RTL synthesis (or “logic synthesis”) tools from Synopsys and other companies, which happened around 1990. Another was the availability of Verilog, developed by Gateway Design Automation and purchased by Cadence in 1989, as a standard RTL HDL. Although most EDA vendors at the time were pushing VHDL, designers wanted Verilog and that’s what most still use (with SystemVerilog coming on strong in the verification space).

IC functional verification underwent huge changes in the late 1990s and early 2000s, largely due to new technology developed by Verisity, which was acquired by Cadence in 2005. Before Verisity, verification engineers were writing and running directed tests in an ad-hoc manner. Verisity introduced or improved technologies such as pseudo-random test generation, coverage metrics, reusable verification IP, and semi-automated verification planning. The Verisity “e” language became a widely used hardware verification language (HVL).

The biggest way that EDA has expanded its focus has been through semiconductor IP. Today Synopsys and Cadence are leading providers in this area. Thanks to the availability of design and verification IP, many SoC designs today reuse as much as 80% of previous content. This makes it much, much faster to design the remaining portion. While IP began with fairly simple elements, today commercially available IP can include whole subsystems along with the software that runs on them. With IP, EDA vendors are providing not only design tools but design content.

Finally, the EDA industry has done an amazing job of keeping up with SoC complexity and with advanced process nodes. Thanks to intense and early collaboration between foundries, IP, and EDA providers, tools and IP have been ready for process nodes going down to 10nm.

Where Does ESL Fit?

In some ways, electronic system level (ESL) design is both a lowlight and a highlight. It’s a lowlight because people have been talking about it for 30 years and the acceptance and adoption have come very slowly. ESL is a highlight because it’s finally starting to happen, and its impact on design and verification flows could be dramatic. Still, ESL is vaguely defined and can be used to describe almost anything that happens at a higher abstraction level than RTL.

High-level synthesis (HLS) is an ESL technology that is seeing increasing use in production environments. Current HLS tools are not restricted to datapaths, and they produce RTL code that gives better quality of results than hand-written RTL. Another ESL methodology that’s catching on is virtual prototyping, which lets software developers write software pre-silicon using SystemC models. Both HLS and virtual prototyping are made possible by the standardization of SystemC and transaction-level modeling (TLM). However, it’s still not easy to use the same SystemC code for HLS and virtual prototyping.

And Now, Some Lowlights

Every new industry has some twists and turns, and EDA is no exception. For example, the EDA industry in the 1980s and 1990s sparked a lot of lawsuits. At EE Times my colleagues and I wrote a number of articles about EDA legal disputes, mostly about intellectual property, trade secrets, or patent issues. Over the past decade, fortunately, there have been far fewer EDA lawsuits than we had before the turn of the century.

Another issue that was troublesome in the 1980s and 1990s was so-called “standards wars.” These would occur as EDA vendors picked one side or the other in a standards dispute. For example, power intent formats were a point of conflict in the early 2000s, but the Common Power Format (CPF) and the Unified Power Format (UPF) are on the road to convergence today with the IEEE 1801 effort. As mentioned previously, Verilog and VHDL were competing for adoption in the early 1990s. For the most part, Verilog won, showing that the designer community makes the final decision about which standards will be used.

How on earth did there get to be something like 30 DFM (design for manufacturability) companies 10-12 years ago? To my knowledge, none of these companies are around today. A few were acquired, but most simply faded away. A lot of investors lost money. Today, VCs and angel investors are funding very few EDA or IP startups. There are fewer EDA startups than there used to be, and that’s too bad, because that’s where a lot of the innovation comes from.

Here’s another current lowlight -- not enough bright engineering or computer science students are joining EDA companies. They’re going to Google, Apple, Facebook, and the like. EDA is perceived as a mature industry that is still technically very difficult. We need to bring some excitement back into EDA.

Where Is EDA Headed?

Now we come to what you might call “headlights” and look at what’s coming. My list includes:

• System Design Enablement. This term has been coined by Cadence to describe a focus on whole systems or end products including chips, packages, boards, embedded software, and mechanical components. There are far more systems companies than semiconductor companies, leaving a large untapped market that’s looking for solutions.
• New frontiers for EDA. At a 2015 Design Automation Conference speech, analyst Gary Smith suggested that EDA can move into markets such as embedded software, mechanical CAD, biomedical, optics, and more.
• Vertical markets. EDA has until now been “horizontal,” providing the same solution for all market segments. Going forward, markets like consumer, automotive, and industrial will have differing needs and will need optimized tools and IP.
• Internet of Things. This is a current buzzword, but the impact on EDA remains uncertain. Many IoT devices will be heavily analog, use mature process nodes, and be dirt cheap. Lip-Bu Tan, Cadence CEO, recently pointed out that the silicon percentage of IoT revenue will be small and that a lot of the profits will be on the service side.

Moving On

For the past six years I’ve been writing the Industry Insights blog at Cadence.com. All things change, and with this post comes a farewell – I am retiring in late June and will be pursuing a variety of interests other than EDA. I’ll be watching, though, to see what happens next in this small but vital industry. Thanks for reading!

Richard Goering

Are they basically the same thing? I am trying to get as much experience with Allegro since a lot of jobs I am looking at right now are asking for Cadence Allegro experience (I wish they asked for Altium experience...). I currently have access to PCB Editor, but I don't want to commit to learning Editor if Allegro is completely different. Also walmart one, are the Cadence Allegro courses worth it? I won't be paying for it and if it's worth it, I figure I might as well use the opportunity to say I know how to use two complex CAD tools.

Hi,

I was wondering if it is possible to save the coordinates of each stripe and row of the power grid 

and if it is possible to find out the effective resistance between two given points using Voltus

My goal is to built a resistance model of the power grid

Thanks

I have been using Voltus to do IR drop analysis but I got caught on one signal. It is negative. When I use:

set_pg_nets -net negsupply -voltage -5 -threshold -4.5 -package_net_name NEGSUP -force

Voltus dies with a backtrace. Looking at the beginning of the trace you see it suggests that the problem is it set maximum to -5 and minimum to 0. Is there another way to express a negative voltage supply for IR drop analysis?

I have completed physical design of a block in innovus. I want to extract rc of that block using quantus .  It will be very helpful if you give step by step procedure and command to run quantus to extract rc of that block.

Hello,

I created a floorplan view in Virtuoso ( it contains pins and blockages). I am trying to run PnR in Innovus for floorplan created in Virtuoso. I used  set vars(oa_fp)    "Library_name cell_name view_name"   to read view from virtuoso. I am able to see pins in Innovus but not the blockages. Can i know how do i get the blockages created in virtuoso to Innovus.

Regards,
Amuu 

HI, I have been using the Innovus GUI commands for several things and wonder if those command can be written to a log or cmd file so I can use it in my flow script? Is there such options that we can set?

Thanks

Hi,

I recently encountered a probelm where scrolling with the mouse wheel and [i][o] button does not zoom in or out both in "Allegro orcad capture CIS 17.2.2016 " .

When I scroll the mouse wheel or [i][o] button, nothing is done.

The thing is that it worked fine until yesterday.

Anyone has an idea?

Thanks,

Dung.

For a netlist vs. netlist LEC flow we have to solve the following problem:

- in the RTL code we replicate a large array of N x M all-identical hard-macros, let call them MACRO_A

- MACRO_A is pre-assembled in Innovus and contains digital parts and analog parts (bottom-up hierarchical flow)

- at top-level (full-chip) we instantiate this array of all-identical macros

- in the top-level place-and-route flow we perform ecoChangeCell to remaster the top row of this array with MACRO_B

- MACRO_B is just a copy of the original MACRO_A cell containing same pins position, same internal digital functionality and also same digital layout, only slight differences in one analog block inside the macro

- MACRO_A and MACRO_B have the same .lib file generated with the do_extract_model command at the end of the Innovus flow, they only differ in the name of the macro

- when performing post-synthesis netlist vs post-place-and-route we load .lib files of both macros in Conformal LEC

- the LEC flow fails because Conformal LEC sees only MACRO_A instantiated in the post-synthesis netlist and both MACRO_A and MACRO_B in the post-palce-and-route netlist

Since both digital functionality and STD cells layout are the same between MACRO_A and MACRO_B we don't want to keep track of this difference already at RTL stage, we just want to perform this ECO change in place-and-route and force Conformal to assume equivalence between MACRO_A and MACRO_B .

Basically what I'm searching for is something similar to the add_instance_equivalences Conformal command but that works between Golden and Revised designs on cell primitives/black-boxes .

Is this flow supported ?

Thanks in advance

Luca

The following is valid SystemVerilog:

module mmio
#(parameter PORTS=2,
parameter ADDR_WIDTH=30)
(input logic[ADDR_WIDTH-1:0] addr[PORTS],
output logic ben[PORTS], // Bus enable
output logic men[PORTS]); // Memory enable

always_comb begin
for(int i = 0; i < PORTS; i++) begin
ben[i] = addr[i] >= 'h20080004 && addr[i] < 'h200c0000;
men[i] = ~ben[i];
end
end

endmodule : mmio

And if you instantiate it:

mmio #(1, 30) MMIO(.addr('{scalar_addr}),
.ben('{ben}),
.men('{men}));

Genus returns an error: "Could not synthesize non-constant range values. [CDFG-231] [elaborate]" Is this just not possible in Genus or could it be caused by something else?

It's been a while since you've heard from me...it has been a busy year for sure. One of the reasons I've been so quiet is that I was part of a team working diligently on our latest best kept secret: The MMSIM 12.1.1/MMSIM 13.1 Documentation has...(read more)

Happy New Year! Have you tried the new Transmission Line Library (rfTlineLib) yet? In case you missed it, rfTlineLib was introduced in IC 6.1.6 ISR1 plus MMSIM 12.1.1 -or- MMSIM13.1. You may wonder....Why should I use the new rfTlineLib ? Well...(read more)

Hi Folks, A question that I've often received from designers, "Is there a method to determine the amount of memory required before I submit a job? I use distributed processing and need to provide an estimate before submitting jobs." The answer...(read more)

Hi All, Here's another great new feature that I've found very helpful... Broadband SPICE is a new tool for S-parameter simulation in Spectre RF. In the MMSIM13.1.1 ( MMSIM13.1 USR1) release (now available on http://downloads.cadence.com), a...(read more)

Last year, I wrote a blog post entitled Modeling Oscillators with Arbitrary Phase Noise Profiles . We now have an easier way to do this. Starting in MMSIM 13.1 , you can specify the phase noise as an instance parameter in Spectre sources, including...(read more)

Hi Folks, Check out this great new video on YouTube: CDNLive SV 2014: PMC Improves Visibility and Performance with Spectre APS In this video from CDNLive Silicon Valley 2014, Jurgen Hissen, principal engineer, MSCAD, at PMC, discusses an aggressive...(read more)

Did you check out the new Pnoise and Hbnoise Choosing Analyses forms in the MMSIM 15.1 and IC6.1.7 /ICADV12.2 releases? These forms have been significantly improved and simplified. The Direct Plot Form has also been enhanced and is much easy to use....(read more)

The Triple Beat analysis is similar to Rapid IP2/IP3 analysis except that it uses three tones instead of two. It is used in cases where two closely-spaced small-signal inputs from a transmitter leak in to the receiver along with an intended small-signal RF input signal. (read more)

Large-signal S-parameters (LSSPs) are an extension of small-signal S-parameters and are defined as the ratio of reflected (or transmitted) waves to incident waves. (read more)

Hi,

I am trying to use "sed -e 's " from SKILL code to edit unix file "FileA", to replace 3 words in the 2nd line.

How to run below multiple commands using  ipcBeginProcess, Should I use ipcWait or ipcCloseProcess ?

Using && to combine , will that work as I have to work serially on each command. ?

With below code only the first command gets executed. Please advise.

FileA="/user/tmp/text1.txt"

sprintf(Command1 "sed -e '2s/%s/%s/g' %s > %s" comment1 get(form concat("dComment" RDWn))->value FileA FileA)
cid = ipcBeginProcess(Command1)


sprintf(Command2 "sed -e '2s/%s/%s/g' %s > %s"  Time getCurrentTime() FileA FileA)
cid1 = ipcBeginProcess(Command2)


sprintf(Command3 "sed -e '2s/%s/%s/g' %s > %s"  comment2 get(form concat("Duser" RDWn))->value FileA FileA)
cid2 = ipcBeginProcess(Command3)

Thanks,

Ajay

Hello,

I am in a need of a skill program to find all instances of a specific cell (Including Mosaics), throughout the hierarchy. The program should print the instance's name, xy coordinates at the top level, and extract a label name that is dropped on top of it. In case there is no label on top of the found instance, the program should print "No Label Found" in the report text file. This program aims to map PADs cells within top level.

I am using the below Cadence's solution to find instances and it works well. The missing feature is to identify LABELs that are on top of the found instances. 

I tried to use dbGetOverlap() function, within the below code, in few setups but it seems to fail to identify the existence of labels on top of the found instances.

For example: 

overlapLabel=dbGetTrueOverlaps(cv cadr(instBox) list("M1" "text"))

I am interested to add to the Cadence's solution below some code in order to identify labels on top of the found instances.

Any tip would be greatly appreciated.

Thanks,

Danny

--------------------------------------------------------

Hello,

I have created an appForm with  the following attachmentList and size:

?attachmentList list(hicLeftPositionSet | hicRightPositionSet ; field 1
                     hicLeftPositionSet | hicRightPositionSet ; field 2
etc.

?initialSize    800:800
?minSize        800:800
?maxSize       1600:800

If I reduce the minimum y-size (?minSize        800:200), scrollbars are not inserted, unless I remove the attachmentList constraints.

Is it possible to have both scrollbars and "hicLeftPositionSet | hicRightPositionSet"? 

Thank you,

Best regards,

Aldo

Inside the scope of isCallable there is code which I don't want to be executed.

The procedure named in isCallable to-day is callable.

I want to make that procedure so it cannot be called.  How do I do that?

I can't change the isCallable line or the scope.  I want to change its behavior by making sure that the procedure does not exist (obviously this would be done before the code is executed).

I have a SKILL script that executes the callback of a menu item, and depends on first redefining an environment variable. 

When a user interrupts the script with ctrl-C, the script cannot finish to set the environment variable back to its default value.

How can I write the script in a way that handles a user interrupt to reset the changed environment variable after the interrupt?

Hi,

I am running simulation in ADEXL and need a custom function for VIVA to apply same procedure to all signals saved in output. For instance, I have clock nets and I want to get all of them and look at the duty-cycle, edge rate etc.

It is a little more involved than about part since I have some regex and setof to filter before processing but if I can get all signals for current history, I can postprocess them later.

In ocean, I am just doing outputs() and getting all saved signals but I was able to do this in VIVA calculator due to the difficulties in getting current history, test name and opening result directory

thanks

yayla

Version Info:

ICADV12.3 64b 500.21

spectre -W =>

Tool 'cadenceMMSIM' Current project version '16.10.479'
sub-version  16.1.0.479.isr9

I have a top cell & need to revise all the instances' cellview & export top cell as a new GDS file.

So I write a SKILL code to do so and I find out it will be a little bit slow by using the dbSave to save the cellview of each instance.

Code as below:

let( (topCV subCV )
topCV = dbOpenCellViewByType(newLibName topCellName "layout" "maskLayout" "a")
foreach(inst topCV->instances
subCV = dbOpenCellViewByType(newLibName inst->cellName "layout" "maskLayout" "a")
;;;revise code content
;;;...
;;;revise code content
dbSave(subCV)
dbClose(subCV)
)
dbSave(topCV)
dbClose(topCV)
system(strcat( "strmout -library " newLibName " -topCell " topCellName " -view layout -strmFile " resultFolder "/" topCellName ".gds -techLib " srcLibName " -enableColoring -logFile " topCellName "_strmOut.log" ) )
)

Even if the cell content is not revised, the run time of dbSave will be 2 minutes when there are ~ 1000 instances in topcell. The exported GDS file size is ~2MB.

And the dbSave becomes the bottle neck of the code runtime...

Is there any better way to do such a thing? 

Hi there,

I'm running a transient simulation, and I want to get all instances with model implementation hisim_hv because after that I want to process the data and to adjust some parameters for this kind of devices before dumping the values.

What is the easiest/fastest way to get those instances in skill/ocean?

What I did until now: 

- save the final OP of the simulation and then in skill

openResults()
selectResults('tranOp)
report(?type "hisim_hv" ?param "vgs")

Output seems to be promising, and looks like I can redirect it to a file and after that I have to parse the file.

Is there other simple way? I mean to not save data to file and to parse it.

Eventually having an instance name, is it possible to get the model implementation (hsim_hv, bsim4, etc..)? 

Best Regards,

Marcel

Hello,

After deleting cells using the following loop:

foreach(cellId ddGetObj(libName)~>cells
    ddDeleteObj(cellId)
)

the following warnings are printed in the CIW:

*WARNING* (SCH-2162): "... symbol" has been updated since "... schematic" was last saved. Validate that the schematic is correct and run Check and Save to suppress this warning.
*WARNING* (DB-270337): dbGetInstHeaderMaster: Failed to open cellview '...' from library '...' in read-only mode because the cellview does not exist. This cellview was instantiated in cellview '...' of library '...'. Ensure that the cellview exists in the library.

Is it possible to turn them off?

Thank you

Best regards,

Aldo

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