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Is there anything in VLSI layout other than “pushing polygons”? (6)

Is there anything in VLSI layout other than “pushing polygons”? (6)
by Dan Clein on 02-05-2018 at 12:00 pm

I am very sorry but I have to break the flow of sharing initiatives, to reiterate the reason for these articles and maybe amplify the message these articles should promote.

I got a few inquiries from LinkedIn connections, who read the previous articles, with a very interesting point of view. This proves that after 5 articles some people did not get “yet” the message. They say that people like the stories, the explanations, the details, but I had a better chance to “invent” things as the world of VLSI automation was very “crude” and “primitive”. Today with all the automation going on, there is little to improve, improvise, innovate or invent. Most of what is needed is already here, so I should write about what should they invent next!!! If everybody will think this way we will stop growing, the gate size technology will stop “shrinking”, and the number of people in our industry will diminish.

To prove my point, I have to go back to history, my initial start in this profession. The year is 1984, the day is January 24, I was one of the 4 people selected to get trained in this “fancy” profession called IC Layout Designer. We were very excited recruits as the number of people with this profession was 6 in MSIL and in all Israel maybe 30 at that time. We were had a trainer from US to teach us Calma computer and software and for layout basics, flows and procedures our trainer was the Layout Manager, Miriam Zvuloni Gaziel. She had a challenging task: to get us from “know nothing” to people she can trust in 3 months. I can never forget the most shocking sentence she used at the end of the first training day:

As you will see, this is a very “fascinating” profession that you cannot learn anywhere else but in big companies like Intel, National, Motorola today. It will pay very well compare to other professions however, based on how the software automation is going, this profession has the potential to disappear in the next 5 years. This was in 1984.

I don’t want to invoke statistics but with all the automation the industry developed in in the last 30 years the number of IC Layout designers not only grew but exploded. Today there are many schools around the world teaching layout, Sankalp alone trained more than 1,000 new grads in the last 10 years. Universities are training Master and PhD student’s in layout so they can implement their projects in silicon. Only in India, that in 1983 probably had no VLSI development industry, there are more than 10,000 people doing VLSI today. We progressed from Calma mainframe to Linux machines, from 5 microns to 5 nano-meters. If somebody says that there is nothing else to invent because all is already there, they should move into the back seats and let the “inspired” and “creative” people take the driver and navigator seats. They will move forward, supporting new ideas, investing time and “Gray power” in new initiatives for automation and technology. Hopefully this clarification is understood and you can use my “historical stories” as stepping stones for your personal development without expecting others to tell you what to do.

A specific issue we had at MOSAID was that each project had to be developed in a totally new process so all tools setup had to be redone every time. We invented the Process Independent Setup (PIS) but people still needed to learn new design rules for each new project. In some cases, the rules changed while we were in the middle of the development. Luckily for us compaction engines showed up around 1996-1997. Rubicad from Germany and Sagantec originally from Holland, with later development moving to Israel. We did our homework by comparing the 2 company’s software features. I saw demos of both at DAC, some official some beyond that. I spoke with all the possible reference users they provided. The final decision was to invite Sagantec for an onsite demo.

We got a very strong AE to visit, Simon Klaver from Holland. The intention was that we can generate fast “dirty” cells and using compaction will get DRC clean results. We also wanted to see if we can use this technology to “migrate layout from process to process” a very new concept at that time. We gave Simon 2 cells for DREAM, the software name at that time, and ask him to clean all the design rules errors. We gave him 5 days with the hope that we can see some “good results” towards our target, but in 2 days he provided DRC and LVS clean cells. Case closed, we needed this tool, so we bought it. MOSAID bought the first DREAM license in North America at a good price with good maintenance service agreement.

After all, this was a huge risk for such a small company to buy a new “bleeding edge” technology from an unknown EDA vendor. We worked directly with the development team and their AEs so Malcolm MacIntosh, one of my team members became our expert. For the next 3 years I spoke with all new potential customers, being the reference customer for Sagantec. This helped their sales and me making new friends around the globe… The following 5 years I was close to Sagantec and help them develop the roadmap for new tools, at the same time being one of the first users for some. One year, after DAC, I went for dinner at the house of Hein van der Wildt, the CEO at that time. After dinner I started to talk with him and Coby Zelnik, a developer at that time, about what can we do next with DREAM. I wanted a tool that can run inside my layout editor, and we started to explore what is needed to make this happen. Like in all cool stories we actually wrote ideas on the napkins we used from the dinner, full of pasta sauce and red wine…

That night Companion, the idea of compaction inside Virtuoso was born.


From compaction flat we wanted hierarchical, from compaction we planned migration, so the life was exiting every time I met their team. I had, and still have, many “interesting” conversations on the roadmaps with Maarten Berkens, who was their CTO at that time, and now is in Sage software. SiClone, SiFix, Anaconda each had a lot of fun to be part of their initiation and development. Being so involved in Sagantec payed back many years later. While in PMC Sierra we needed a tool for DRC fixing so we looked at VLM from Cadence and SiFix from Sagantec. Coby Zelnik, now the CEO of Sagantec, came to Vancouver with Christen Decoin to show the tool and talk about the corporation new capabilities.

Unfortunately, he had to leave in the middle of the night having a family situation. Christen was a new AE with good technical knowledge of the tools but did not know how to answer all customers questions. He did the demo and I became the presenter of Sagantec corporate and technical presentation to PMC Mixed Signal Design & Layout. I had fun convincing PMC team that the tool I present (as Sagantec marketing) is the tool I want (as PMC Sierra Layout Manager) and it’s doing what we needed. The crowd had a lot of fun punishing me with questions, but I survived and we bought the tool.

More MOSAID “non-layout” initiatives next month…

Dan

Read the full blog series HERE.


AI-Leader Horizon Robotics Selects NetSpeed AI-based NoC IP For Next Generation Designs

AI-Leader Horizon Robotics Selects NetSpeed AI-based NoC IP For Next Generation Designs
by Mitch Heins on 02-05-2018 at 7:00 am

If you haven’t noticed, there has been a BIG influx of money into Artificial Intelligence (AI) technologies. Most recently, the Chinese government announced that AI is one of their top initiatives with a goal to catch up with the United States within 3 years and to be the world leader in AI by the year 2030. Horizon Robotics, founded in 2015, is one of China’s AI startups. It just closed a $100M A-round funding led by Intel Capital in October 2017 with the intent to build AI-based hardware and software targeted for use in autonomous vehicles, smart homes and smart cities. They plan to differentiate themselves by building low power, low cost intelligent processors that will enable devices to perceive, interact, understand and make decisions locally in the fog instead of having to transmit data to the cloud.

To accomplish their goal, Horizon’s team led by founder Kai Yu, former head of Baidu’s Institute of Deep Learning, has created a unique architecture they call their Brain Processing Unit (BPU). The architecture is open and allows for it to be targeted to multiple different compute platforms and end-markets applications. One of Horizon’s main goals is to be able to make any device an intelligent entity that can “think” locally without having to communicate to the cloud. That implies a lot of on-chip compute power, while also being cost effective enough to be sold in high volumes.

Because Horizon’s AI solutions are dealing with the real world, their chips have complex heterogeneous architectures that utilize multiple different processing engines, embedded memories and a variety of different sensor interfaces. Streaming data from sensors is fused into a homogeneous semantic environment upon which various hardware-accelerated AI-engines work to perceive objects, identify them and then predict their behavior. This implies an architecture that must deal with real-time cache coherency between different processors running at different speeds and workloads.

This clearly is not a one size fits all problem that can be tackled by one architecture. However, being a leader in AI is helping Horizon to attack the problem in a scalable way. Their understanding of AI’s benefits led them to license NetSpeed’s Orion and Gemini Interconnect IP for use in their AI chips. For those not familiar with NetSpeed, they use machine learning and AI techniques to help system architects synthesize System-on-Chip (SoC) interconnect fabrics known as networks-on-chip (NoCs). To be clear, Orion and Gemini NoCs are not static IP blocks, but instead are sophisticated interconnect fabrics that are synthesized by machine learning algorithms that analyze the anticipated workloads and traffic patterns between various processor engines, memories and external sensors interfaces.

While Orion and Gemini are incredible technology on their own, the thing that really makes them appealing to Horizon is the fact that the same NetSpeed IP can be easily scaled up or down to meet the needs of many different end-market applications using NetSpeed’s machine-learning Turing technology. And when Horizon says scaling they really mean scaling. They are ambitiously looking to put intelligence into as many as 1000 unique types of applications. You can imagine that the architecture for autonomous vehicles will be greatly different than an autonomous kitchen appliance. Yet both applications will use similar BPU building blocks from Horizon along with NetSpeed NoCs.

China by itself represents a huge AI market for Horizon. In the automotive market alone China now sells 30 million new cars each year. Advanced Driver Assisted Systems (ADAS) are well known for helping drivers park their cars or identifying objects in drivers’ blind spots. However, according to Yu from Horizon, ADAS used in Europe or the U.S. won’t cut it for China. ADAS in China must go to a whole new level as Yu says that in China the driving conditions are much more challenging. As examples, Yu says that in China drivers change lanes much more frequently than in most other countries and there are way more pedestrians everywhere, even on the highways!


Automobiles are just the tip of the iceberg however as China predicts it will need hundreds if not thousands of new AI applications to help it with city management, traffic, and a host of Internet-of-things (IoT) devices that will be running on 5G networks within its large populous cities. Here again Horizon plans to make those edge devices intelligent with their Brain technology.

In summary, there is a big push for AI at the edge of the cloud and it appears that NetSpeed’s NoCs are well positioned to leverage this upcoming market. As Horizon Robotics has figured out, the ability to integrate heterogeneous architectures with smart interconnect fabrics is an enabling technology for next generation AI systems.

See Also:
Press Release: Horizon Robotics Licenses NetSpeed Interconnect IP for AI SoCs
NetSpeed Turing Technology
NetSpeed web site
Horizon Robotics web site

About Horizon Robotics
Horizon Robotics aims for becoming the global leader of embedded AI. By jointly optimizing algorithm and processor design, Horizon Robotics is delivering software and hardware integrated solutions with high performance and low power to equip devices, such as autonomous vehicles and smart cameras, to make human life more safe, convenient and fun. The company has a strong R&D team with rich industrial experience support the development of the smart world. Horizon Robotics has received funding from venture investors including Morningside Venture Capital, Hillhouse Capital, Sequoia Capital, GSR Ventures, Linear Venture, Innovation Works, ZhenFund, Wu Capital, Tsing Capital and Vertex Ventures, as well as from Yuri Milner, a legendary venture capitalist from Silicon Valley. http://en.horizon.ai/

About NetSpeed Systems

NetSpeed Systems provides scalable, coherent on-chip network IPs to SoC designers for a wide range of markets from mobile to high-performance computing and networking. NetSpeed’s on-chip network platform delivers significant time-to-market advantages through a system-level approach, a high level of user-driven automation and state-of-the-art algorithms. NetSpeed Systems was founded in 2011 and is led by seasoned executives from the semiconductor and networking industries. The company is funded by top-tier investors from Silicon Valley. It is based in San Jose, California and has additional research and development facilities in Asia. For more information, visit www.netspeedsystems.com.


DSP SoC a la Française

DSP SoC a la Française
by Lauro Rizzatti on 02-04-2018 at 11:00 am

I enjoyed reading Eric Esteve’s article “ French Tech at CES, 2nd country after USA with 274 Start-Up at Eureka Park!” It brought back happy memories of my time at EVE until Synopsys purchased it in 2012.Here is another intriguing story by a French startup named VSORA and founded by Khaled Maalej with a team of scientists and engineers. Not new to the French high-tech landscape, Khaled and team already reached success in a previous enterprise named DiBcom when it was acquired by Parrot, a dronecompany, in 2011. DiBcom was the leading providing of integrated circuits for mobile digital TV receivers incorporated into cell-phones, cars and PCs.

This time the team came up with a rather interesting idea.Digital Signal Processors (DSP) have been around for about four decades and by now they are ubiquitous in the semiconductor industry, used for image and audio processing, in communication and mobile applications, lately in automotive designs, essentially everywhere there is a need to elaborate digital signals. Today DSP designs are by far more complex and advanced than the pioneering implementations introduced by TI, AMD, NEC, and others in the late 1970’s. Still, all current offerings meet the need for ever growing processing power via one or more DSP co-processors: the higher the processing power requirement, the more th eco-processors. All well and good, but co-processors are essentially hard-wired algorithms. Any change to an algorithm, no matter how small, forces the DSP engineers to re-spin the hardware. A costly proposition with a very lengthy design-iteration-time (DIT) in the ballpark of one month or longer.

Based on their previous experience at DiBcom, the team conceiveda DSP architecture that eliminates the co-processors. Instead, they devised a flexible fabric built on a matrix of multiple DSP cores they call Multi-Core Signal Processors (MSP). Each core can be configured and optimized to perform a specific task. You can size the memory assigned to each core, tune the processing power, that is, select the number of arithmetic-logic-units (ALU),or adjust the floating point accuracy. For example, a DSP performing MiMo combinations requires different computation accuracy and rather higher processing power than one performing signal synchronization.

But this is not all there is to it. Vsora went a step,actually two steps further.

In an SoC design that includes an embedded DSP, for example a base station for a wireless application, the traditional development process involves four different design teams. First, the signal processing team, comprised of highly specialized engineers, defines an algorithm at high level of abstraction, commonly using Matlab-like coding. Once pleased with the results,they pass their creation on to the DSP design team to implement it either on the DSP or, when not feasible, in one or more co-processors. The two teams come from different backgrounds, possess different skills, use different development tools and methods, and habitually mis-communicate blaming each other. The scenario leads to multiple iterations between them until they agree on a result. The real problem is, each iteration may take weeks.

Once the DSP design is satisfactory, it is dispatched to the SOC hardware team that incorporates it into the SoC, and to the embedded software team that develops the supporting software stack.

Vsora envisioned a development environment that unifies the two DSP teams into the algorithmic team, giving them the tools to fine tune the algorithms until ready to be deployed in the SoC. They can perform “what-if”analysis, try different configurations, size each core for performance, power, orarea, generate multiple version of the DSP and compare them without implementing the actual hardware. Once pleased with the results, they forward the MSP to the SOC hardware and software development teams. The approach eliminates the detrimental iterations and accelerates the development schedule by few months.

As a cheery-on-the-cake, the team is also setting up the VSORA MSP development environment on the Amazon Web Services FPGA (AWS-F1) cloud. Engineers will be able to access the VSORA development environment and fine tune their algorithms while mapping it directly to the DSP. They will be able to reduce the simulation time of the implemented DSP by factor of 10s compared to simulation of the algorithmic model running on a PC, and eliminate the risk that abstract and implemented models may differ. Signal processing engineers will be able to define and implement their algorithms and verify them on a “prototyping-like”platform within minutes. This leads to better system/cost optimization at the early stage of the project and avoid significant upfront investments to setup a traditional development environment.

The upcoming 5G standard, heavily reliant on DSP technology, is posing new and steep challenges to the engineering community,stressing the traditional DSP development flow. The adoption of millimeter waves, MIMO, and other advanced technologies requires lots of processing power,creating a golden opportunity for the VSORA approach.

Recently VSORA closed their first round of funding from Omnes Capital, Partech Ventures, and few Angel Investors.Definitely, there must be something unique in the DNA of the French engineering community.


The future of education is virtual

The future of education is virtual
by Vivek Wadhwa on 02-04-2018 at 7:00 am

Massive open online courses (MOOCs) were supposed to bring a revolution in education. But they haven’t lived up to expectations. We have been putting educators in front of cameras and shooting video — just as the first TV shows did with radio stars, microphone in hand. This is not to say the millions of hours of online content are not valuable; the limits lie in the ability of the underlying technology to customize the material to the individual and to coach.

That is about to change, though, through the use of virtual reality, artificial intelligence and sensors. Let me illustrate this with an imaginary school of the future in which Clifford is an artificial intelligence, a digital tutor, and Rachael is the human educational coach.

Clifford has been with the children for years and understands their strengths and weaknesses. He customizes each class for them. To a child who likes reading books, he teaches mathematics and science in a traditional way, on their tablets. If they struggle with this because they are more visual learners, he asks them to put on their virtual-reality headsets for an excursion, say, to ancient Egypt.

Watching the design and construction of the pyramids, children learn the geometry of different types of triangles and the mathematics behind these massive timeless monuments. They also gain an understanding of Egyptian history and culture by following the minds of the geniuses who planned and constructed them.

Clifford also teaches art, music and biology through holographic simulations.

By using advanced sensors to observe the children’s pupillary size, their eye movements and subtle changes in the tone of their voice, Clifford registers their emotional state and level of understanding of the subject matter. There is no time pressure to complete a lesson, and there are no grades or exams. Yet Clifford can tell the parents how the child is doing whenever they want to know and can advise the human, Rachael, on what to teach.

Rachael does not lecture or scrawl facts or equations on a blackboard. She is there to listen and help. She asks questions to help develop the children’s values and thinking and teaches them how to work with one other. She has the responsibility of ensuring that students learn what they need to, and she guides them in ways Clifford cannot. She also helps with the physical side of projects, things made out of real materials rather than in mind and machine.

With Clifford as teacher and Rachel as coach, children do not even realize that what they are undertaking is study. It feels like building cool stuff, playing video games, and living through history. Clifford, being software and having come into being in the same way that the free applications on our smartphones have, comes without financial charge. Rachael’s coaching is part of our public education package, funded in the same way today’s teachers are.

We already have wonderful teachers who are supportive and can teach teamwork and values. Believe it or not, we have the ability to build Clifford today. The artificial intelligence tools and sensors to observe human emotion are commonly available via smartphones and digital assistants, and the virtual-reality headsets will soon be powerful enough and affordable enough for holographic learning.

Take Facebook’s Oculus Rift virtual reality headset. When Facebook released Oculus Rift in March 2016, it cost $599 and required a $199 controller and a $1,000 gaming PC. The headset and controller now cost $399 together and do the work of the gaming PC. Facebook says a new version, Oculus Go, will ship later this year and cost $199. At the recent Consumer Electronics Show in Las Vegas, HTC announced Vive Pro, a headset with much higher resolution and better features than Oculus Rift; and its price will surely be lower, because dozens of other companies, including Google, Lenovo and Magic Leap, are in also the race.

We can expect that within two or three years, VR headsets will cost less than $100 and have built-in artificial intelligence chips, enabling billions of people to benefit from the education revolution finally at hand.

For more, you can read my book, Driver in the Driverless Car. It details the advances that are making this amazing–and scary–future possible.


Cloud Provider Leverages FPGA Prototyping

Cloud Provider Leverages FPGA Prototyping
by Daniel Nenni on 02-02-2018 at 7:00 am

Talking to customers is one of the best parts of being a semiconductor professional. It keeps you grounded and offers you the collective experience of some of the smartest people around the world, absolutely.

Webinar: The Emergence of FPGA Prototyping for ASIC/SoC Design

Customer success stories are a close second and interestingly much harder to come by than a face to face meeting. The semiconductor industry is very competitive (secretive) so when you do get a customer willing to speak up it is definitely worth your time. This success story is from my favorite FPGA Prototyping provider S2C:

Inspur is a leading cloud provider in China offering high-end servers, mass storage, cloud operating system, and information security technology. As a chip and systems developer Inspur was faced with the challenges of establishing an executable platform for hardware validation and integration, building a high bandwidth transmission channel to transfer mass packet to DUT for verification, and supporting fast and stable system startup then quickly and accurately locating problems.

Inspur’s routing control design consumed 96% BRAM of VU440 FPGA which allowed no extra memory resources for ChipScope debugging. The S2C delivered MDM does not consume design FPGA memories which perfectly solved this debugging issue.

The complexity of Inspur’s SoC increased both cost and schedule risks due to the need to verify real-world scenarios. Generally no one knows when a bug will hit or when it actually occurs, especially if there isn’t enough sampling depth to analyze. MDM mitigated those challenges as a cost-effective solution. After the initial 1~2 MDM and Single VU systems bring up, Inspur used 10 sets of systems running 24 hours a day without interruption. This enabled Inspur to detect and fix many bugs in the real network testing environment which cut six months off their development schedule.

Inspur used the Single VU440 Prodigy Logic Module for prototyping verification on a routing control chip and selected the MDM to run the deep trace debugging which allows Inspur to grab as many packets as possible to then be analyzed for correctness.

“The performance capabilities of the Prodigy Logic Module, deep trace debugging of MDM software, professional daughter card customization services, and fast support helped us efficiently verify our SoC designs. This allowed us to focus on the innovation and validation of the SoC.” Said Huang Jiaming, General Manager of High-end Server Department at Inspur.

“The biggest advantage S2C MDM gives us is the ability to detect bugs deeply embedded in the design that can be detected only by processing the real word packets. This significantly speeds up the debug process and gets our design to the market quickly with greater confidence.”

Overview

  • S2C’s single VU440 Prodigy Logic Module providing multi-million ASIC gate capacity
  • The Prodigy Multi-Debug Module (MDM) enables greater sampling depth which makes debugging easier
  • The customized QSFP Interface Module is well designed and higher performance
  • The quick response of S2C’s support team helped Inspur to bring up the FPGA validation environment successfully

With S2C’s rapid SoC prototyping solutions Inspur saved about six months in developing and debugging their SoC design. Features like scalability, reuse, flexibility, and deep trace debugging let Inspur quickly port the design into FPGA prototyping, transfer mass packet to the DUT, and speed up the debugging progress.

S2C Solution

  • S2C’s Single VU440 Prodigy Logic Module providing multi-million ASIC gate capacity allows Inspur to quickly port their routing control chip for verification
  • Customized two QSFP cage interface modules to provide the high-speed transmission channel for the DUT
  • Specialized Prodigy Multi-Debug Module hardware enables deep trace debugging with the ability to store up to 16GB of waveforms
  • Prodigy Player Pro is used to setup trigger conditions and capture related packets for chip-level debugging

 


Figure 1: Inspur routing controller validation platform using S2C Single VU440 + MDM

 

About S2C
Founded and headquartered in San Jose, California, S2C has been successfully delivering rapid SoC prototyping solutions since 2003. S2C provides:

With over 200 customers and more than 800 systems installed, S2C’s focus is on SoC/ASIC development to reduce the SoC design cycle. Our highly qualified engineering team and customer-centric sales force understand our users’ SoC development needs. S2C systems have been deployed by leaders in consumer electronics, communications, computing, image processing, data storage, research, defense, education, automotive, medical, design services, and silicon IP. S2C is headquartered in San Jose, CA with offices and distributors around the globe including the UK, Israel, China, Taiwan, Korea, and Japan. For more information, visit www.s2cinc.com.


In-System Automotive Test

In-System Automotive Test
by Daniel Payne on 02-01-2018 at 12:00 pm

I’ve been driving cars since 1975 and in the early days we had simplistic gauges for feedback like: Speed, Fuel level, Oil level, RPM. Back then when you popped the hood of a car you could see through the engine compartment onto the ground below, however with today’s cars the engine compartments are crammed with tubes, wires and assemblies packed so tightly that you cannot see the ground and electronic content abounds. Dashboards of modern cars even report when a turn signal or other light bulb is burnt out or if the tire pressure is out of spec and needs to be checked. A report from IDCpredicts a 19% growth rate for infotainment systems in our cars. McKinsey sees automotive semiconductor trends in several areas:

  • Vehicle electrification
  • Increased connectivity
  • Autonomous driving
  • Shared mobility services

One established vendor to the automotive industry over the years has been Renesas, offering products in eleven distinct areas:

So a big challenge in automotive electronics is safety, we want to know that our cars are operating safely and furthermore we want to know when something has gone wrong so that we can take action like schedule maintenance or repairs. To accomplish these goals our semiconductor suppliers do extensive testing of electronic parts before they are shipped to automotive vendors, but what about after the parts are installed in the vehicle? Is there a way to test some or all of the electronic components in our cars throughout the lifetime of use?

The short answer is yes, there are techniques that chip designers can employ to allow testing of electronics that are installed, or in-system testing. We love our acronyms in high tech so I’ll give you another one that fits our topic and it’s called BIST, which stand for Built In Self Test. With BIST the chip designer adds some extra logic inside their IC that will:

  • Check itself at power-up for faults
  • Check for conditions that cause failures
  • Report the issue(s)

An ideal BIST approach would be one that provides high fault coverage of all gates inside the IC, and does so in a short amount of time like milliseconds. EDA tools have come to automate adding the BIST logic to a chip so that a designer doesn’t have to manually figure out the best implementation, and engineers at Renesas have just publicly talked about how they used the DFTMAX LogicBISTtool from Synopsys in their automotive group. From a design engineer perspective you add LogicBIST when your RTL code is stable and before physical implementation as shown in the following BIST flow:

During the process of adding LogicBIST the Renesas engineers also used a tool to increase fault coverage levels called SpyGlass DFT ADV that accepts RTL code, ensures the design is scan compliant, diagnoses DFT issues early, does lint checking and DFT analysis and estimates stuck-at and transition faults:

Renesas and Synopsys were able to certify DFTMAX LogicBIST was meeting Part 8 of the ISO 26262 functional safety standard, something that the automotive industry regulates.

Benefits that Akira Omichi from Renesas sees from this LogicBIST approach include:

  • Useful on mixed-signal automotive designs
  • Power-on Self Test (POST) improves safety
  • Consumes minimal chip area
  • Gives high fault coverage on the digital logic
  • Easy to use

Talking with Robert Ruiz of Synopsys by phone I learned that the ISO 26262 standard for functional safety presumes that there is a human driver in the car, so it doesn’t directly pertain to fully autonomous vehicles. With POST and LogicBIST the goal is to find and report any latent faults, typically showing up as a message on the dashboard.

Over time you can expect to see more and more automotive semiconductor suppliers to add LogicBIST to their IC designs as a means to improve functional safety and differentiate their product offerings. With EDA vendors like Synopsys it’s an easier process for chip designers to add LogicBIST because of the automation in their DFTMAX LogicBIST tool.

Related blogs:


Crystal Bulb: Sharing Design Intelligence

Crystal Bulb: Sharing Design Intelligence
by Bernard Murphy on 02-01-2018 at 7:00 am

There is a trend among design companies to want to extract more intelligence, from designs in-process and designs past, in support of optimizing total enterprise efficiency. Design automation companies see opportunity in leveraging this interest since they, in various ways, have a handle on at least part of the underlying data. The question of course is what constitutes a sufficient base of design information to support extracting information that will be widely useful to the enterprise. That depends on what sort of information you want to extract.

Design data management companies are making a play in this space because they have a good handle on the chip design bill-of-materials (BOM) view (and perhaps aspects of the software), if not packaging, reference board and documentation. Some even go deeper into some IP, reading OpenAccess (OA) physical databases and netlists. This unquestionably extends their ability to mine more information for those types of design object, though it is unclear how deep an understanding they have of higher-level design semantics.

But how extensively does that level of understanding help the enterprise? If I’m an applications engineer, or a packaging engineer, or I’m developing documentation or software drivers, or planning a reference board, or even program-managing the technical interface with key accounts, understanding the current state of the BOM is certainly important but it’s less clear how useful low-level design details will be beyond the needs of hands-on chip design and implementation teams.

But if you buy into IP-XACT-centric design flows, the picture changes quite significantly. Now you have a much more structured view of a design from the IP level on up with quite a lot of design semantics already built in. Configured IP have their configuration parameters stored in a well-defined way, so you know not only BOM info but also in what way each IP was configured. You can extract clock and reset trees to document / validate how these are structured. You have complete information on memory mapping, essential to documenting the hardware/software interface, auto-generating the low-level hardware abstraction layer and building sequence tests for verification. IO pin-muxing mapping provides test, documentation and reference board teams early insight into the package interface.

Access to this information is what Magillem leverages through their CrystalBulb product. Pascal Chauvet (Strategic Account Manager) told me they have extended the scope of what can be understood, beyond the IP-XACT schema, through a Magillem schema cover to the chipset and board level (he expects these features may eventually be suggested as extensions to the standard).

CrystalBulb runs on a server, accessing data from distributed teams and providing that data either though web-based dashboard or through standard file format (Excel, text, PDF). At this stage Magillem doesn’t emphasize need for an API and scripting to aid gathering data, (though they do provide a RESTful API), instead stressing a simpler (non-programming) approach through filters, which seem appropriate for the wide user-base they are targeting. Pascal also mentioned that they currently work with customers on any extensions they might require.

As an example of usage, Pascal pointed to the needs of an application engineer doing software bring-up on first product samples. This engineer will need to understand the correlation between IP versions, IP configuration, chip-level functional modes, IO muxing, die pads/IC package pin-bonding and board. Old way: dig through all the documentation, talk to the design team, learn “oh yeah, we changed that configuration at the last minute and it didn’t yet get to documentation”. New way: all the latest data is available real time.

The product is designed for viewing data rather than editing (as it should be as an analytics system) and provides all the standard infrastructure for access control, following areas of interest and supporting review with annotations by stakeholders across the enterprise. Again, a more dynamic and real-time way to support enterprise-wide alignment and signoff.

Overall CrystalBulb looks like an interesting step towards widely-accessible analytics based on structured design. You can learn more about CrystalBulb HERE.


Open Silicon Year in Review 2017

Open Silicon Year in Review 2017
by Daniel Nenni on 01-31-2018 at 7:00 am

If you are interested in what types of chips we will see in the coming years always ask an ASIC provider because they know. Companies of all sizes (small-medium-large) use ASIC companies to get their chips out in the least amount of time and at a minimum cost because that is what ASIC companies do.

IP is an important ingredient to the ASIC business model of course and it is easy to see the types of IP that are attracting the big ASIC customers, all you have to do is look at the ASIC company press releases and webinars:

Open-Silicon Expands Networking IP Portfolio to Address High-Bandwidth Ethernet Endpoint and Ethernet Transport Applications

Comprehensive IP subsystem includes Interlaken, Ethernet PCS, Flex Ethernet and Forward Error Correction IPs

“More and more enterprises and small/medium businesses are shifting their IT investments from in-house IT infrastructure to cloud-based IT services—spending on cloud services is on track to rise by over 30% in 2017,” said Matthias Machowinski, Senior Research Director at IHS Markit. “In response, cloud service providers (CSPs) are heavily investing in their infrastructure, and are currently upgrading their networks to 25/100G. In anticipation of continuing growth, CSPs are already looking towards the future, and once 400G becomes available in 2018/2019, we expect them to rapidly adopt this new technology.”

Open-Silicon Unveils Industry’s Highest Performance Interlaken Chip-to-Chip Interface IP

Supports up to 1.2 Tbps and up to 56Gbps SerDes rates

“The 3rd-party IP ecosystem has always played a key role in the industry. And now, with the unstoppable growth of high-bandwidth networking applications together with the desire to further technological advancements on a much quicker cadence, the demand for industry consortium standards that ensure interoperability grows sharply,” stated Michael Howard, senior research director and advisor, carrier networks at IHS Markit. “It is for these reasons that solutions such as this chip-to-chip Interlaken IP core, will likely have high adoption into next-generation routers and switches, packet processors, and high-end networking and data processing applications.”

Open-Silicon Completes Successful Silicon Validation of High Bandwidth Memory (HBM2) IP Subsystem Solution

Silicon validation in TSMC’s 16nm FinFET technology and interoperability with HBM2 memory; Silicon-proven SoC solution enables next generation high bandwidth applications

“Open-Silicon’s successful silicon validation of an HBM2 IP subsystem in 16nm means that volume production of HBM2 ASIC SiPs are now a reality,” said Herb Reiter, President, eda2asic Consulting, Inc. and author of the most recent Multi-Die IC User Guide, co-sponsored by the Electronic System Design Alliance (ESD Alliance). “The benefit to the industry is significant, in that system developers of high bandwidth applications can minimize risk and time-to-market by having access to a complete silicon-proven HBM IP subsystem, and design/manufacturing of HBM2 ASIC SiPs from a single vendor.”

Open-Silicon Receives TSMC OIP Ecosystem Forum Customers’ Choice Award for Best Paper

High Bandwidth Memory (HBM2) IP Subsystem Solution Va
lidation and Interoperability with HBM2 Memory Die Stack

“TSMC has a very selective process for accepting papers, and those that are chosen represent the highest quality and highest value to our customers,” said Suk Lee, TSMC Senior Director, Design Infrastructure Marketing Division. “Receiving the Customers’ Choice Award for the best paper clearly demonstrates the high level of interest in Open-Silicon’s HBM2 IP subsystem solution and the benefits it offers to our mutual customers using TSMC FinFET and CoWoS® technologies.”

One of the trends I have been tracking on SemiWiki is systems companies using ASIC services rather than investing millions of dollars in hiring or acquiring a team and tools. From the SemiWiki analytics you can see an increasing amount of non-traditional chip companies researching IP, EDA tools, foundry and ASIC services. It really is encouraging to see the systems companies investing in the fabless semiconductor ecosystem making the ASIC business great again, absolutely.


Adapting an embedded FPGA for Aerospace Applications

Adapting an embedded FPGA for Aerospace Applications
by Tom Dillinger on 01-30-2018 at 4:00 pm

The IC industry is commonly divided into different market segments – consumer, mobile, industrial, commercial, medical, automotive, and aerospace. A key differentiation among these segments is the characterization and reliability qualification strategy for the fabrication process and design circuitry. For each segment, specific voltage and temperature environment ranges are input to electrical characterization and analysis flows to confirm functional operation. Reliability analysis expands upon these circuit characterization parameters to evaluate various failure mechanisms, which can lead to either “hard error” lifetime fails or “soft error” transient fails. The primary lifetime failure mechanisms are related to device and interconnect parameter drift due to “aging”, associated with: the number of power-on hours; the on/off (thermal) cycles; interconnect current density; and, circuit switching activity. The primary source of soft errors is due to exposure to external radiation.

I was curious to learn more about the aerospace segment – but first, I needed to study up on radiation-hardened (“rad hard”) soft error concerns and circuit design.

Rad Hard Design

Over the evolution of VLSI process technologies, failure diagnosis and experimental research has identified two principal sources of radiation-induced soft errors:

  • alpha particles incident on sensitive circuit nodes
  • cosmic ray-generated high-energy neutrons

IC industry veterans will remember the crucial time in the 1970’s when DRAM “soft error upsets” (SEU) were a dominant failure mechanism. Groundbreaking research identified the root cause as the introduction of free electron-hole pairs generated by an incident radiated alpha particle, which creates an “ionization track” as it traverses the silicon, as illustrated in the figure below.


Figure 1. An illustration of the “ionization track” due to an incident alpha particle at an nFET device node. The principal charge collection mechanism is the drift due to the depletion region electric field. (From Autran, et al, “Soft-Error Rate of Advanced SRAM Memories: Modeling and Monte Carlo Simulation”.)

If these free carriers are generated in the critical “collection volume” associated with a depletion region electric field, the charges would drift to a circuit node, significantly disrupting the node voltage. (The electric field drift mechanism would be stronger than the diffusion of the free charge distribution.)

Fast forwarding several decades, many technical advances have been made to reduce the SEU rate:

  • packaging and die-package attach materials improvements reduce the flux of alpha particles from radioactive decay
  • with process/voltage scaling, the collection volume has decreased (although so has the critical charge, Qcrit, on dynamic storage nodes)
  • DRAM architectures have added ECC functionality to correct single-bit errors
  • systems have implemented memory scrubbing operations

Today, the principal cause of SEU is due to the incident flux of cosmic radiation – the figure below illustrates the constituent high-energy particles.


Figure 2. Cosmic rays generate high-energy neutrons, which have an extremely long range. (From NTT Systems Laboratories, “The action against soft-errors to prevent service outages”.)

The key contribution to SEU is from the neutron flux incident on a die. A neutron collision with the silicon lattice may result is a permanent displacement which is a hard fail lifetime consideration, especially for bipolar devices (due to increased recombination rates in the base junction). Of principal concern for CMOS devices, a neutron collision may generate (high-energy) secondary particles, which can then create free electron-hole pairs resulting in an SEU, in a manner similar to alpha particles.


Figure 3. Illustration of an inelastic neutron collision with the silicon lattice, and (charged) secondary particles creating free electron-hole pairs. (From Yuanfu, et al., “Single event soft error in advanced integrated circuit”.)

A specific consideration is that the high-energy neutron flux is much greater at high altitude, where aerospace equipment will be operating.


Figure 4. Neutron flux (1-10MeV momentum) versus altitude. (From KVA Engineering)


Figure 5. Neutron momentum versus flux rate, measured at sea level. (From Autran, et al.)

Radiation-hardened circuit development is focused on reducing the susceptibility to the impact of an ionizing event. SRAM bit cell and flip-flop circuits are designed to increase the Qcrit over their equivalent commercial library offerings. The circuit layouts are developed to minimize the collection volume, specifically the sensitive node area, and the magnitude of the depletion region electric field to the node.

The Aerospace Market and eFPGA’s

I knew the aerospace market was a big user of FPGA technology, so I reached out to the team at Flex Logix, developers of embedded FPGA IP, for their insights. I recently had the opportunity to chat with Geoff Tate, CEO, and Andy Jaros, VP of Sales, and learned a great deal.

Geoff had some very interesting financial data, indicating, “10% of the FPGA market revenue is from the aerospace segment. And, FPGA’s represent 35% of the electronics cost in aerospace products. FPGA’s are especially appealing due to the reconfigurability, as these products have a long deployment lifetime. Currently, there are very few commercial FPGA products qualified for the aerospace market.”


Andy added, “Aerospace companies have unique requirements for electronics, with regards to performance, power, and product volume.” (We are all aware that mobile product applications are extremely sensitive to cubic volume – I hadn’t thought much about aerospace-related designs, but they certainly are, as well.)


Andy continued, “For these reasons, there is a need to pursue technology integration, but the individual unit volume is relatively low. That’s why we are seeing strong interest from aerospace developers in leveraging embedded FPGA technology – providing for both integration and reconfigurability.”


“What about the rad hard requirements?”
I asked.

Geoff said, “Our eFPGA architecture is extremely modular, allowing us to readily embed rad hard library cells into the LUT design, and rad hard bit cells into the SRAM. We recently completed a collaborative project with an aerospace Licensee, where we took their library and re-implemented the EFLX core into a rad hard implementation, with a preferred metallization stack. All the eFPGA synthesis and compiler support remains the same. We re-extracted and re-characterized the power/performance to the aerospace environment. All within a matter of a few months.”

Given a rad hard circuit library, the recent Flex Logix Technologies collaboration demonstrates that developing an eFPGA for aerospace products is achievable quickly and with low cost.

Considering the traditional appeal of FPGA’s for this segment, and the benefits of technology integration, I anticipate there will be more announcements in the near future. For additional information on aerospace applications for eFPGA’s, please follow this link.

PS. The DAC and ICCAD conferences are the premier places to learn about the latest in EDA tools research. Advanced process technology presentations are the highlight of the IEDM conference. For aerospace product developers, I learned from Geoff and Andy that the GOMACTech conference is the place to be: https://www.gomactech.net/2018/index.html . If you happen to be attending GOMACTech 2018, be sure to stop by the Flex Logix booth and say “Hi!”.

-chipguy


Automotive Mega-trends, Safety and Requirements Management

Automotive Mega-trends, Safety and Requirements Management
by Daniel Payne on 01-30-2018 at 12:00 pm

I come from a car-centric family where my father actually bought and sold over 300 vehicles in his lifetime, so automotive mega-trends pique my interest. A new conference called Semiconductors ISO 26262 held it’s first annual event last month, meeting in Munich with guest speakers from some impressive companies like: Intel, NVIDIA, STMicroelectronics, Renesas, Melexis, Texas Instruments, Toshiba, Robert Bosch, Jama Software and NetSpeed Systems. There was a panel discussion all about ISO 26262, the functional safety standard for automotive, and Adrian Rolufs of Jama Software presented on: Staying Competitive in Safety-Critical Applications with Requirements Management. I’ve read his 18 slide presentation and learned some important details. Adrian’s background includes working for 10 years in mixed-signal IC development and 5 years with requirements management for multiple industries: Semiconductor, Automotive, Medical Device, Aerospace & Defense.

So the big three automotive mega-trends are:

We’ve been blogging on SemiWiki for several years now on the Electrification trend of increased semiconductor content for automotive, and most analysts see something like a 10% growth rate here. Tesla, GM, Ford, Toyota, Waymo, Mercedes Benz, Google, Intel, NVIDIA, Audi and many other technology companies have joined the quest to make autonomous vehicles a reality for us to enjoy. Travel as a Service (TaaS) has been wildly popular around our globe with big brands like Uber and Lyft being in dominant positions today. So there’s a whole lot of change going on in our auto-centric society.

Electric Vehicles (EV) are now at a point where some 30 models are available worldwide and we can expect that number to grow rapidly, the sales of EV around the world went up 41% in 2016. In the USA for 2017 the EV sales were up 86%, now that’s growth worth noting. Even established car brands like Volvo have made a public commitment for 100% electric vehicles instead of gradually tapering away from combustion engines.

One big push for autonomous vehicles is safety, because at present we see some 1,300,000 people die annually in car crashes, an average of 3,287 deaths each day. The early adopters for autonomous driving are Tesla, Google and Waymo, but we will probably have to wait until 2025 to see widespread use of autonomous vehicles because of the technical, financial, government and legal challenges.

I’ve used both Uber and Lyft services in California and Oregon, so they’ve really provided excellent apps for my smart phone when GPS and a cell tower are available. The other big trend is car sharing apps like Car2Go and ReachNow to get higher utilization out of our beloved cars that mostly sit idle. I expect that traditional Taxi, Limo and Rental Car services will decline and suffer as TaaS gains momentum.

If all of these mega-trends comes to a full realization then visionaries at Google expect that we could experience some astounding benefits:

  • 90% reduction in auto accidents

    • 4.95 million fewer accidents in the US
    • 30,000 fewer deaths
    • 2,000,000 fewer injuries
    • $400B cost savings to our economy
  • 90% reduction in wasted commuting

    • 4.8 billion fewer commuting hours
    • 1.9 billion gallons in fuel savings
    • $101B saved in lost productivity and fuel cost
  • 90% reduction in cars

    • 80% reduction in cost per trip-mile
    • Car utilization climbing from 5-10% up to 75%
    • Better land use

The combination of these three automotive mega-trends and their efficiency benefits bode quite well for the semiconductor industry and will continue to drive the healthy 10% growth rate for several years. Semiconductor vendors need to navigate the new complexities of regulation and complexity in the automotive industry in order to stay competitive and relevant. With the ISO 26262 functional safety standard the vendors must now trace their requirements throughout the entire design process, and at first many companies will use standard office applications like Word and Excel to cobble together something quickly..

The company Jama Software was founded to automate the traceability of requirements throughout many complex product design flows, so you don’t have to kludge together something less efficiently with office tools. This automated approach provides new benefits like live traceability during product development to quickly provide the program manager with a view of how every user requirement impacts the technical requirements, design and even test cases.

This approach from Jama isn’t a one-size fits all, in fact you can even adjust the tools to fit the way that your company does automotive design, with each step of your process captured along with dependencies.

During the automotive design process you have many stakeholders, and when something comes up that will impact other stakeholders then the change needs to be reviewed. The Jama tools support this kind of stakeholder review by automating and capturing all review items in a convenient GUI format.

As the electronics in your automotive system are being design there’s need for verification and validation of all requirements, so for example there’s a requirement for supply current on a pin to be 2mA maximum, while the verification limit is set at 1.7mA, but then there’s a validation where the value is outside of the specification at 2.05mA, then the Jama system quickly pinpoints this validation error by using a red color to catch your attention.

What makes the Jama tools so intuitive and easy to use are the web-based GUI, liberal licensing model so that all the engineers can use it, and a low learning curve. Automotive companies may start out using Jama tools to meet ISO 26262 traceability requirements, enjoy the benefits, then start to use the same tools for every product design. If a tool can reduce multiple silicon tape-outs, then its value becomes quite important. The consultants at Jama know about the semiconductor and automotive industries and will help you get setup quickly to fit your specific design process using best practices.

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