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Hierarchical RTL Based ATPG for an ARM A75 Based SOC

Hierarchical RTL Based ATPG for an ARM A75 Based SOC
by Tom Simon on 03-27-2019 at 5:00 am

Two central concepts have led to the growth of our ability to manage and implement larger and larger designs: hierarchy and higher levels of abstraction. Without these two approaches the enormous designs we are seeing in SOCs would not be possible. Hierarchy in particular allows the reuse of component blocks, such as CPU cores. This has been a major enabling element to SOC designs. Due to the very real clock rate ceiling for practical CPU implementation, the move to multiple parallel processors has been essential to increasing performance without running into power and bandwidth issues.

Back in the late 1990’s physical chip design was hierarchical, and it was Mentor that lead a revolution in leveraging hierarchy for DRC. Now, Mentor is a leader in the move to make DFT and ATPG hierarchical, taking special advantage of repeated blocks. They have moved test insertion and test operations themselves to the block level, unlocking many efficiencies and reducing overall complexity. Mentor’s Tessent Hierarchical ATPG Flow at the RTL level offers many advantages.

Mentor and ARM have published a reference flow showing how DFT and ATPG can be implemented at RTL in an SOC containing multiple Cortex-A75s. Fully one third of the reference flow introduction is documentation of the steps used in the flow. This provides useful technical information useful for implementation. The first part of the document discusses the approach and advantages of the flow.

For the purposes of the reference flow, which uses 4 instances of the A75, they implemented two levels of DFT: the wrapped A75 core and top-level logic. Once the A75 core is wrapped it can be placed multiple times in the SOC. The finished chip contains MBIST and 1149.1 boundary scan logic. Also included are on-chip clock controllers (OCC), Tessent TestKompress controllers (EDT) and the test access mechanism (TAP).

The flow starts with MBIST insertion in the A75 block, followed by EDT and OCC insertion, all at RTL. After this, block synthesis is performed as usual. Next is scan insertion and retargetable ATPG for the block. Within the A75 the Tessent MBIST can use the shared memory bus. Once the A75 is done with test, the reference flow moves on to the top-level logic.

For the top level, boundary scan and MBIST are added first. A JTAG compatible TAP controller, Tessent boundary scan logic, an IJTAG-based Tesesnt MBIST assembly module for shared bus memories in the chip top level, and also regular Tessent MBIST for individual memories are added next. A second pass adds TestKompress logic and OCCs. The design also gets TAMs that can support multiple ATPG test modes. Each of the already wrapped A75s are included during the second pass.

So, what are the results? At the core level with 6,365 patterns for Stuck-at faults, they reach a coverage of 99.21%. For Transition faults, with 17,791 patterns, the coverage is 98.28%. In each case these numbers are just shy of the ‘ideal’ total for extest and intest coverage. Here are the top level ATPG results.

As I mentioned earlier, this is a detailed step by step description of the flow and includes actual annotated command descriptions for the process. This documentation shows the value of the partnership between ARM and Mentor and provides useful insight into the actual flow and its results. For users wishing to take this to the next level, the full reference flow package available from Mentor includes everything needed to implement this flow, including scripts, interfaces and documentation. To get started I’d suggest reading the overview from the Mentor website.


Menta eFPGA Conquer Eu Processor and 5G in China

Menta eFPGA Conquer Eu Processor and 5G in China
by Eric Esteve on 03-27-2019 at 12:00 am

During 2018, Menta looked quiet if you consider communication as the main indicator of activity. In fact, the eFPGA vendor was hyper-active in developing future business and reports two main design-win. The first is with the European Processor Initiative (EPI) and Menta has announced in December 2018 that it has been selected as the sole provider of embedded FPGA IP for this European project.

This is significant for Menta in driving programmability in a large share of new high-performance computing and automotive applications. Members of the consortium include Atos, BMW, CEA, Infineon and ST Microelectronics.

The second design win officially announced by Menta a few days ago is with a Telecom company in China, as “eFPGA IP from Menta Selected by Beijing Chongxin Communication Company to Enable Programmability in 4G/5G Wireless Baseband SoC”. It’s important to show that eFPGA IP is now considered as mature enough to be integrated into a wireless SoC addressing the very competitive 4G/5G market.

In other words, all design win doesn’t weight the same. Winning a prototype project developed by a research team working in a prestigious university is great, but integrating an eFPGA IP in a SoC expected to go in production is even better and demonstrate that embedded FPGA is moving from lab to industry!

Nevertheless, being selected to serve the EPI is a wise investment to serve the automotive industry in the future. If we must select one industry segment where Europe is competitive, automotive certainly comes in first. The main goals of the EPI project are:

  • European independence in High Performance Computing Processor Technologies.
  • EU Exascale machine based on EU processor by 2023.
  • Based on solid, long-term economic model, Go beyond the HPC market.
  • Address the needs of European Industry (Car manufacturing market).

I love the last two goals, showing the willingness to keep pace with long-term economic model and to address the needs of the automotive industry. It looks obvious today, but such big project may have failed in the past to be economy-compatible. And, because car manufacturing is a competitive market, we know that it can turn into an economic war between USA, China and Europe. In modern wars, you need to consider semiconductor as ammunitions!

We can expect the automotive CPU issued from EPI to integrate eFPGA IP, as it’s the best way to provide efficient flexibility to a SoC. Especially when this SoC will be integrated to a car and must be functional for at least a decade, but also be able to be updated when needed.

If we consider the total European automotive industry, the production volume is in the 20 million vehicles range. To obtain the SoC production volume TAM, you have to multiply the number of cars by the number of CPU per car… It may become a huge number, approaching the billion SoC per year (just look at the next picture). Yes, eFPGA IP design win in EPI can be a very wise investment!


The other (officially announced) design win, the baseband SoC from Beijing Chongxin Communication Company is expected to support both the existing 4G LTE infrastructure while also offering the programmability required to address the emerging 5G NR wireless specification. And Mr Tao Hu, VP of Engineering of Beijing Chongxin Communication Company, seems to be completely convinced by the benefits of integrating eFPGA IP.

“We are pleased to select Menta’s eFPGA IP for our 5G NR SoC. The eFPGA IP surpassed all other available options on the market in terms of flexibility, technology portability and customer support,” said Tao Hu, VP of Engineering of Beijing Chongxin Communication Company. “Menta’s IP supports of the specifications of our next-generation wireless communication products, including re-configurable and software-defined features. The portability of their IP to all process technologies makes them an ideal long-term technology partner.”


As a conclusion, I will share again that I wrote in 2017 in Semiwiki: “As far as I am concerned, I really think that the semiconductor industry will adopt eFPGA when adding flexibility to a SoC is needed. The multiple benefits in term of solution cost and power consumption should be the drivers, and Menta is well positioned to get a good share of this new IP market.”

These two design wins represent a fact-based confirmation of this prediction, isn’t it?

From Eric Esteve from IPnest


Verification 3.0 Holds it First Innovation Summit

Verification 3.0 Holds it First Innovation Summit
by Randy Smith on 03-26-2019 at 5:00 am

Last week I attended the first Verification 3.0 Innovation Summit held at Levi’s Stadium in Santa Clara along with about 90 other interested engineers and former engineers (meaning marketing and sales people, like me). There was a great vibe and feel to the event as it exuded an energy level that I have not felt at an EDA event in years. The attendees included longtime EDA veterans as well as a few newcomers. Perhaps more important, the list of participating companies was quite long including speakers from Avery, Breker, Metrics, TV&S, Imperas, OneSpin, Vayavya, Agnisys, Concept, Methodics. Vtool, and Verifyter. Blue Pearl, Willamette HDL, and XtremeEDA were also supporting the event. Quite a collection of verification experts. All these companies gave presentations, spoke to attendees in a tabletop gathering at the end of the event (with great food!), or did both.

EDA industry luminary, Jim Hogan, who has been a driving force behind the Verification 3.0 effort, kicked off the event. Jim is involved in several of the companies supporting this effort as a consultant, investor, and board member. Unfortunately, due to traffic, I missed Jim’s remarks, but we did get a chance to talk at the reception later in the evening where Jim told me, “There are some major themes that Joe outlined in his talk. It’s time to take a new approach to verification, that’s why we called it verification v3.0. We outlined this in an article last year.” Herding so many start-ups is quite a challenge, but Jim is off to a terrific start.

Next up was Joe Costello, former Cadence CEO and the “Tony Robbins of EDA”. I worked at Cadence during Joe’s tenure and his infectious smile, positive attitude, and fervent enthusiasm were clearly all still in effect. Joe laid out a clear case for the likely path of verification solutions over the next five years. He discussed the macroeconomic factors and the design trends that are driving a new approach to verification solutions and then suggested a target opportunity for the participating companies.

The first macroeconomic factor mentioned by Joe is the move to cloud computing. The cloud computing market is already in the same order of magnitude as the entire semiconductor market, measured in the hundreds of billions of dollars per year. Yet, most EDA companies have been slow to make use of these services. Cloud-based EDA solutions would stop semiconductor designers from also needing to be experts at running their own massive compute farms. This also goes hand-in-hand with the second macroeconomic factor, SaaS (software as a service). Deploying EDA tools as a service is far simpler to do in a cloud environment where both the use of the hardware AND software would be measured. This allows users to only pay for the tool usage they use, rather than pay for (and try to predict) their maximum needed capacity of licenses.

So, you might be thinking that these are just infrastructure issues, it is not the next algorithm or paradigm to solve verification issues. What I can tell you is the biggest hurdle of semiconductor design today is the COST of verification. That cost is in licenses and hardware – but it is especially important in headcount. Having spent some time the last few years helping firms on their recruiting challenges, I know for certain that there are not enough verification engineers available to meet the semiconductor industry’s current needs. So, improving efficiency in verification is critical to improving the results of verification as well as reducing its costs.

Improving the efficiency of verification also can mean building more platforms which are specific to certain types of designs. Joe specifically mentioned the fledgling market for design specific processors. Domain specific processors are coming about due to the end of Moore’s Law and Dennard scaling, as well as the concerns about efficiently scaling solutions. Building processors for specific applications is an approach to improve the efficiency and results of designs build for specific problems. Joe specifically mentioned ‘RISC-V’ as an example of open processors enabling this approach. Now doubt, ARM could also go down this path to some extent as well.

Which leads us to this: If you are going to have domain specific architectures, then can’t you develop specific verification environments to aid in the design and verification of those designs? For example, why not build an environment around a specific processor (that also supports extensions) including the IP and verification best practices specific to that application – an environment supporting ISO 26262 for functional safety? An environment knowledgeable of video/audio codec standards? The list is long. Beyond the changes this can drive in the verification industry, the opportunities in semiconductor IP are enormous.

This event was well worth attending, and if you are interested in verification, it would be well worth your time to attend the next Verification 3.0 event whenever that might next happen. You can check out the website at https://verification30.com/. I heard slides might be online next week.


Self-Certification Insufficient?

Self-Certification Insufficient?
by Roger C. Lanctot on 03-26-2019 at 12:00 am

The crash of Ethiopia Air Flight 961 may have a negative impact on the development of autonomous vehicle technology. The Federal Aviation Administration (FAA) is now forced to reconsider the “self-certification” process used for the Boeing 737 Max 8 airplane involved.

Self-driving car developers have been seeking the same self-certification for their own systems. The FAA’s failure suggests that may not be good enough. The U.S. Department of Transportation’s National Highway Traffic Safety Administration is taking public comments regarding a regulatory framework for autonomous vehicles, which are already cruising U.S. highways. The challenge for air and land travel governed by software is the same: Understanding and regulating the algorithms and code inside black boxes.

Feds move to consider cars with no steering wheels, brakes – Automotive News

Regulating surface transportation is complicated by the role of local regulators in the U.S. – the 50 states. It is complicated by the fact that many of these states view automated driving technology as the killer app capable of easing congestion, reducing vehicle emissions and enhancing mobility for disadvantaged or disabled populations.

But the killer app might become itself a killer. With each new fatality attributed to an autonomous vehicle, come the investigations to determine what sort of algorithmic failure led to the crash. Thus far, from Florida to Arizona, the source of the software shortcoming seems to have been successfully located – but that may not always be the case.

In the case of Ethiopia Air 961 the story appears to be even worse as multiple reports suggest that a software update was either in the works – to correct the failure experienced by Lion Air Flight 610 – or ready to be implemented, but failed to deploy in time. Another layer to the story derives from the self-certification where, according to reports in the Washington Post, Boeing employees were more or less deputized to act as FAA representatives as part of the process.
Further still, reports have emerged that pilots and airline representatives being shown the new system in the Boeing 737 Max 8 identified multiple areas requiring further training and preparation:

For cars it is not a case of training drivers. It is a case of training machines to drive. We go from the forensic “black box” of the airline industry to the emerging A.I. black box of the self-driving car industry. The question is whether we are inclined to put our “faith” in A.I. from self-driving car developers or with regulators. We already know the limitations of the regulators.

Conferring our faith to the A.I. black box in the self-driving car reminded me of the A.I. challenges currently facing the health care industry. In the words of one interviewee, Dr. Eric Topol, cardiologist and the founder and director of the Scripps Research Translational Institute, quoted in the New York Times last week:

“There’s no shortage of deep liabilities for A.I. in health care. The liabilities include breaches of privacy and security, hacking, the lack of explainability of most A.I. algorithms, the potential to worsen inequities, the embedded bias and ethical quandaries.”

Self-certification in the airline industry – necessitated no doubt by expenses and staffing limitations at the FAA – will now come under renewed scrutiny. Will self-certification be good enough for self-driving cars?

The incompetence and failure at Boeing and the FAA raise unavoidable questions regarding the regulation of transportation. The latest fatal Tesla crash (with a semi-trailer), just a few weeks ago, and these two 737 Max 8 crashes are testing the tolerance of transportation users.

U.S. safety agencies to investigate fatal Tesla crash in Florida – CNBC

The debate calls to mind a presentation I gave last week at a security conference put on by the Metropolitan Police in the U.K. I concluded by noting the likelihood that regulators will require the ability to remotely control autonomous vehicles. In other words, regulators will not allow autonomous vehicles unless there is a provision to control them remotely.

Not surprisingly, some of the law enforcement members in the audience wanted to discuss the topic in further detail. The story of vehicle remote control is both old and new.

General Motors and Hyundai Motor America offer remote vehicle slow-down functions as part of the stolen vehicle tracking and recovery solution in their telematics offerings for passenger vehicles. Brazil attempted to mandate vehicle immobilizer technology several years ago, but abandoned the effort over privacy and security concerns. Finland’s regulatory authority requires a driver for a certified autonomous vehicle, but the driver need not be IN the vehicle.

Remote control is the main differentiator between airline and surface transportation, which is far more deadly than flying. For now, the airline industry and its regulatory authorities have determined that the risks of remote control for airplanes are greater than the rewards. For cars, it is increasingly looking like remote control will be essential.

Even with remote control, though, the challenge of certification and regulation remains. In the U.S., states are opting for less regulation, not more. An audience at the Future Networked Car Symposium at the Geneva Motor Show voted by a show of hands slightly in favor of more regulation – perhaps reflecting the presence of executives from multiple European regulatory authorities.

Ten years from now we will somehow arrive at the nirvana of autonomous vehicle technology where we are saving lives and reducing congestion, and emissions, and parking garages are eliminated completely. There are going to be bumps along the way. Fasten your seat belt.

Also read: Surviving in the Age of Digitalization


Update on SystemC for High-Level Synthesis

Update on SystemC for High-Level Synthesis
by Tom Dillinger on 03-26-2019 at 12:00 am

The scope of current system designs continues to present challenges to verification and implementation engineering teams. The algorithmic complexity of image/voice processing applications needs a high-level language description for efficient representation. The development and testing of embedded firmware routines (commonly written in ‘C’) are driving the trend toward SW/HW “virtual prototyping” verification strategies. And, to be sure, the time-to-market (TTM) pressures are extreme – despite the increased scope and diversity, there is little relief in design schedules. To improve design productivity and verification throughput, hardware models must be represented at higher levels of abstraction, while also providing a well-defined synthesis flow to implementation.

The SystemC hardware description language was originally conceived to help address these design modeling and verification pressures. Yet, SystemC adoption has been slow. The overall language semantics were well-defined, but the modeling guidelines for implementation synthesis were unclear. And, significantly, the influence and support of a “standards” organization for SystemC modeling was lacking. At the recent DVCon (Design and Verification Conference) in San Jose, a workshop session focused on SystemC provided a very positive update on the issues above – indeed, I would anticipate an acceleration in adoption by system designers.

First, a standards update…

Mike Meredith from Cadence Design Systems described the initiatives within Accellera to define and document SystemC usage guidelines. The list of active working groups is impressive:

  • SystemC Language
  • SystemC Synthesis
  • SystemC Verification
  • SystemC Datatypes
  • SystemC Analog/Mixed-Signal
  • SystemC Configuration, Control, and Inspection

The other workshop participants added to Mike’s overview, with encouraging comments.

“The Accellera initiatives are expanding beyond the base language definition, with use case examples covering ‘what to model’ and ‘how to model’.”

“The Accellera activities have focused on clarifying the relationship and distinctions between SystemC (v2.3.3) and C++(v11/v14).”

“A draft of the SystemC library integration with the Universal Verification Methodology(UVM)has been prepared – for example, how to adapt a System Verilog constrained random testbench to exercise SystemC models.”

“The unique nature of automotive system designs requires both the productivity of SystemC and AMS simulation integration. The Accellera working group has been updating the SystemC/AMS user guide and regression test suite, describing in detail the synchronization activity between the(continuous domain)analog and(discrete event)digital models.”

“The high-level synthesis semantics of SystemC assertions is a focus area, in support of assertion-based verification(ABV)environments.”

Mike expanded upon the last comment above, to describe the main emphasis of the Accellera SystemC synthesis working group, namely the development of a SystemC modeling standard for high-level synthesis (HLS).

HLS for SystemC involves a sequence of algorithms to realize an implementation-based model:

  • elaboration
  • input synthesis directives and constraints
  • characterization of the hardware resources for all operations
  • scheduling operations to clocks
  • generation of the RTL model

To enable SystemC synthesis, additional “hardware-centric” features were needed – e.g., modules, ports, signal, processes, bit-accurate datatypes, communication channels, and clocks. SystemC synthesis directives are also unique, offering (optional) user guidance on:

  • program loop interpretation (e.g., “UNROLL_LOOP”)
  • resource allocation (i.e., binding operations to resources)
  • cycle scheduling (e.g., pipelining evaluations, latency)
  • allocation and mapping to registers
  • reset behavior
  • creation of finite-state machine states and transitions
  • definition of data channels (e.g., point-to-point interfaces, FIFO’s, etc.)
  • pin-level protocols for data communication (with SystemC function calls through an event on a “SC_port”)

Even with cycle-accurate definitions for protocols and controls, the base algorithm models are still abstract – SystemC for HLS maintains its design and verification productivity.

Mike went into detail on the most significant updates to SystemC modeling for HLS, specifically how the model structure is defined, and how (implicit) clocking is incorporated. His illustrations used the concept of a SystemC “thread” (process).

The figure below illustrates the SystemC module structure for HLS (from Mike’s DVCon presentation). The structure contains elements familiar to RTL designers – e.g., ports for hierarchical connectivity and signal communication.

The definition of a concurrent sequential process is fundamental to RTL modeling, and is reflected in SystemC (for HLS) as an “SC_METHOD” or “SC_THREAD”. The figures below illustrate the features of these processes, and a brief coding example, applicable to both verification and synthesis.

The SC_THREAD and SC_CTHREAD include both a reset preamble and a “wait()” function to represent clocked evaluation. (Briefly, the SC_THREAD process is sensitive to any event, whereas the SC_CTHREAD is suspended by a clock signal – the SC_CTHREAD process is used to define a FSM in the output RTL model.)

The SC_METHOD would not include any wait suspension execution control. Note that the verification flow is directed to execute the reset code by “registering” the thread/process, as opposed to the semantics of a constructor function. (A constructor would only be evaluated once, whereas a model reset may be re-executed as part of verification.)

Mike also described the SystemC standards activity for synthesis of variable datatypes, using 2’s complement evaluation – see the figure below.

“Not all users will need the full datatype width of standard.”, Mike highlighted. “For more efficient hardware implementation through synthesis, other bit width datatypes are available in the Accellera SystemC library. For non-integer numeric datatypes, user-defined behavior for the saturation and rounding of a calculation is provided.”

I left the DVCon SystemC workshop very enthused about the progress of the Accellera working groups, and the standards activity to define SystemC semantics for HLS. Admittedly, only two EDA vendors are currently providing SystemC HLS support. Regardless, I expect the interest in SystemC modeling to grow and the adoption rate to increase.

Design and verification engineers interested in learning more about SystemC (and ideally, participating in the working groups) are encouraged to go to the Accellera web site (link).

For more information on the Cadence Stratus HLS offering, please go to this link.

-chipguy


Device-as-a-Service – a Market for the Future

Device-as-a-Service – a Market for the Future
by Krishna Betai on 03-25-2019 at 5:00 am

There is an emerging market in the world of IoT, and service providers are yet to realize the potential of it. With x-as-a-Service — x taking the shape of either software, platform, or infrastructure — already in play, it is only a matter of time before Device-as-a-Service becomes a cash cow for these providers.

Like its predecessors, DaaS too is based on the pay-per-use model, which has been around for a while and has become popular among consumers, convenience being the selling point. From basic household utilities such as electricity to music and video streaming services like Spotify and Netflix, the PPU model has become a ubiquitous force that has changed the definition of consumption and is likely to end the concept of product ownership.

When the pay-per-use model is applied to smart appliances, the result is a Device-as-a-Service model. A consumer would be able to use a smart washing machine, dryer, refrigerator, or air conditioner without actually paying their heavy price tags, instead, they would pay a monthly fee based on their usage. Imagine paying a monthly bill for using a washing machine, the amount of which would vary should the user wash a handful of clothes, instead of washing an entire load of several pounds. The “units consumed” for a refrigerator would shoot up if its door is kept open longer than required, resulting in a spike in the monthly bill. Furthermore, harnessing the “smart” feature of an air conditioner, consumers could be advised to operate the appliance at a specific temperature or range to keep the monthly bill within a certain amount and avoid unnecessary surcharges. This, of course, would depend on external factors such as changes in seasons and climate.

There are several benefits of the Device-as-a-Service model:

From the viewpoint of service providers, the DaaS model would provide them with steady, predictable business after the initial installation of the appliance. Rather than receiving a lump sum amount for the outright purchase of an appliance, they would generate revenue from the monthly payments made by the consumer, regardless of the number of times the appliance is actually used in the 30-day period. Moreover, service providers can monitor the daily wear and tear of the appliances from the large volumes of data generated, thus enabling predictive maintenance. This would help in optimizing repair costs and inventory management of spare parts.

From the consumer viewpoint, convenience and flexibility are the highlights of the DaaS model. In the event that a consumer moves into a new home, they can do away with the hassle of shifting heavy appliances, and can simply inform their service provider of the change and continue their usage, uninterrupted. This would be possible due to the contractual nature of the model.

Environmentally, DaaS would avoid wasteful consumption of energy, aid in the timely maintenance of the appliance thereby extending its useful life, and optimize its usage in a way that would not harm the environment.

Companies like HP and Amazon already follow a pricing model that resonates with DaaS in some way. HP sells its printers at an economical price, charging more for the ink cartridges that its users purchase almost monthly. The online retail giant launched the Kindle, a revolutionary reading device, at a mouth-watering price, fully aware that the millions of e-book purchases would generate more revenue and turn out to be profitable in the long run. Carriers like Verizon and AT&T also follow a similar pricing model, dishing out subsidized smartphones in exchange for contractual agreements with a typical timespan of 24 months. These examples are a testament to the fact that data-driven consumption and billing is the future.

While IoT sensors are heavily used in automobiles and medical devices, their scope can be expanded to smart appliances as well. Whirlpool, for instance, has already taken the lead; the company can track the usage of its smart washing machines and even order detergents for its users before they run out of it. The only obstacle in the DaaS model is whether or not the current 4G networks would be able to manage so many connected appliances at a given point of time. Thanks to the rapid development of the faster, stable, and more reliable 5G network, this does not seem like much of a hurdle.

As companies put together the pieces of the IoT puzzle and become better equipped to handle vast amounts of data over superfast networks, the market of Device-as-a-Service seems to be a viable and obvious next step towards an IoT-enabled future.


A Smarter Way to Do Multi-Board PCB Systems

A Smarter Way to Do Multi-Board PCB Systems
by Daniel Payne on 03-23-2019 at 2:15 pm

Many electronic product ideas start out as sketches on the back of a napkin, then migrate over to diagrams drawn in Visio or PowerPoint, finally entered into EDA-specific tools. With that methodology there’s a big disconnect between the diagrams drawn with a purely graphical tool and the EDA tools, because there’s no data linkage happening, so there’s no consistency and no automation when a change is made to the specification. Necessity is the mother of all inventions, so I recently spoke with Gary Hindeat Cadence to learn about how this need for system-level capture was turned into a new product, named Allegro System Capture, announced earlier this year.

Q: How new is System Capture?

It’s been in development for a few years now, and it’s a platform for hardware design of systems with multiple boards, packages, cables and harnesses.

Q: Why was System Capture created in the first place?

I’ve had previous roles at Cadence as an AE and AE director, visiting customers across Europe that design PCB systems for automotive, industrial, mil-aero, networking and even formula racing. These teams often started out their designs with PowerPoint or Visio to capture the big-picture, but there was never any linkage to the electrical system and requirements. So we created System Capture as a way to automate the graphical diagrams that also included connectivity, and partitioning a system into multiple boards.


Electronic system definition that drives the detailed implementation

Q: Does System Capture work with any schematic or PCB layout tool?

Our System Capture tool works with the Cadence Allegro and OrCAD tools only at this point.

Q: Can you give me an example of how using your approach is beneficial?

Sure, consider a two board system having RF and Digital. With this approach you can partition your system into two boards, then have design engineers assigned to each board working in parallel, while the interconnect between the two boards is first entered with System Capture, maintaining consistency of the interconnect between the boards.

Q: What types of engineers would be using your new tool?

It really depends on the project, typical users would be: system architects, hardware architects, lead engineers senior engineers, EE, some MCAD users, PCB designers, SI experts, even manufacturing engineers.

Q: What problems does this new approach help mitigate?

Well, it eliminates surprises that happen when bringing together two or more boards. Let’s say that something changed like pin positions or pins names, with this approach you catch these changes so there aren’t surprises. The system-level connectivity is defined from the top-down, and there are consistency checks as you create the PCB layout for each board.


System connectivity mismatches identified and highlighted for users to resolve

Q: How much time can an engineer expect to save with this approach?

With the connectivity already defined in System Capture you can expect that during schematic capture between a 2X to 5X speedup. Placing decoupling capacitor rails is up to 10X faster on schematic pages now.

Q: What types of simulation analysis are supported?

We’ve got two types, signal integrity analysis is done with the Allegro Sigrity SI tool, and power integrity with Allegro Sigrity PI.

Q: Where can I learn more about System Capture?

On the web there’s a product page and data sheet, contact your local Cadence AE, or come visit us at PCB West in Santa Clara.

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Semiconductor Market Downturn in 2019

Semiconductor Market Downturn in 2019
by Bill Jewell on 03-23-2019 at 5:00 am

The global semiconductor market grew 13.7% in 2018, according to World Semiconductor Trade Statistics (WSTS). Each year, we at Semiconductor Intelligence review semiconductor forecasts and compare them to the final WSTS data. We used projections which were publicly released from late 2017 through early 2018, prior to the release of January 2018 WSTS data in March 2018. These forecasts ranged from 5.9% from Mike Cowan to 21.3% from Future Horizons. Most were in the 6% to 8% range. Our Semiconductor Intelligence projection in February 2018 was 12%, the closest to the final number of 13.7%.

We were set to award ourselves the (virtual) trophy for forecast accuracy. However, in researching recent forecasts for 2019, we found Objective Analysis posted a report on its forecast accuracy since 2008. The December 2017 video from VLSI Research shows a chart with the Objective Analysis statement “strong start supports 10%+ growth” for 2018. But in the video Jim Handy of Objective Analysis said their forecast was 14%. Thus, Objective Analysis wins the (virtual) trophy for 2018. The 2017 semiconductor market grew 21.6%. Last year we awarded our (again virtual) trophy to Future Horizons for its 11% projection. However Objective Analysis would have won that year also, with a forecast of ~20%.

What is the outlook for 2019? The year 2018 semiconductor market finished weak with an 8.2% decline in the fourth quarter from the third, according to WSTS. The first quarter of 2019 will be even weaker. Most major semiconductor companies are expecting up to double digit declines in 1Q 2019 from 4Q 2018. The exceptions are Qualcomm which expects a 0.9% increase (with 9.3% at the high end) and Infineon, which sees a flat 1Q 2019. Weak end demand and inventory adjustments are cited as key factors in the declines. Memory companies are the hardest hit, with Samsung down 24.3% in 4Q 2018 and SK Hynix down 13.0%. Micron just reported a 26.3% revenue decline in its fiscal quarter ended February 28, 2019. Micron’s outlook for the quarter ending May 31 is a 17.7% decline.

The global economic outlook for 2019 points to slower growth in 2019. The International Monetary Fund (IMF) January 2019 forecast is for world GDP growth to slow from 3.7% in 2018 to 3.5% in 2019. The decline is led by the advanced economies, with the U.S. slowing from 2.9% in 2018 to 2.5% in 2019 and the Euro area slowing from 1.8% to 1.6%. China is expected to drag down growth in the emerging/developing economies as its GDP growth decelerates from 6.6% in 2018 to 6.2% in 2019. On the positive side, India continues to show of over 7% and accelerating, the ASEAN-5 (Indonesia, Malaysia, the Philippines, Thailand and Vietnam) exhibit steady growth of around 5% and Latin America is recovering. Key factors cited by the IMF for the slowdown are trade tensions (especially between the U.S. and China) and the uncertainty of the U.K.’s exit from the European Union (Brexit). The outlook for 2020 show slight improvement, with acceleration to 3.6% world GDP growth led by emerging/developing economies.

The outlook for key end equipment is also bleak. IDC in March forecast a 0.8% decline in smartphone unit shipments in 2019 and a 3.3% decline in combined PC and tablet unit shipments.

Recent 2019 semiconductor market forecasts are generally negative. Our latest projection from Semiconductor Intelligence is a 10% decline. Several forecasts are in the -5% to -1% range. Objective Analysis has a chance for a three-peat forecast trophy for 2019; but would have to share with Morgan Stanley if -5% is closest to the final number. IC Insights expects a slight 1.6% gain for the IC market while Gartner projects a 2.6% gain for semiconductors. Memory is the weakest link in 2019. IC Insights projects the IC market excluding memory will grow 6.7%. WSTS expects 2.6% growth for semiconductor excluding memory. Our Semiconductor Intelligence forecast is for a 2% decline in semiconductor without memory.

The current outlook for the semiconductor industry for 2019 assumes lower memory prices, slower electronic equipment demand, inventory corrections, and slower growth for the global economy. Despite all the uncertainty, few analysts expect a global recession in 2019. The expectations for the 2020 semiconductor market are mixed. VLSI Research and Gartner forecast a rebound in 2020 of 7.0% and 8.1% respectively. IC Insights projects a 1.9% decline in the 2020 IC market. Our preliminary 2020 forecast from Semiconductor Intelligence is 5% to 10% growth.


SPIE Advanced Lithography Conference – ASML EUV Update

SPIE Advanced Lithography Conference – ASML EUV Update
by Scotten Jones on 03-23-2019 at 12:00 am

At the SPIE Advanced Lithography Conference ASML gave an update on both the current 0.33NA system and the 0.55 high-NA system development. I saw the presentations and got to sit down with Mike Lercel (Director of Strategic Marketing).
Continue reading “SPIE Advanced Lithography Conference – ASML EUV Update”


Attend Parts of DAC For Free, Really

Attend Parts of DAC For Free, Really
by Daniel Payne on 03-22-2019 at 5:00 am

The Design Automation Conference (DAC) is the must-see, annual event for semiconductor professionals that design chips, use EDA software, and buy semiconductor IP. Like all conferences there’s an entrance fee, but for the 11th year now you can get a free pass, courtesy of three sponsors: Avatar Integrated Systems, ClioSoft, Truechip. The free pass is part of the I Love DACpromotion going on now, but you must act before the deadline of May 17th. DAC is located in Las Vegas this year from June 2-6, so make your airline and hotel arrangements early to get the best deals.

Here’s what you’re going to experience with the I Love DAC pass:

  • Four daily Keynote sessions
  • Access to the Exhibition Floor with over 170+ Exhibitors
  • Access to two pavilions with daily presentations
  • DAC Pavilion, sponsored by Cadence

    • SKYTalks (mini-keynotes)
    • Industry leader discussions
    • Hot industry topic panels
    • Tear-downs
  • Design-On-Cloud Pavilion in Design Infrastructure Alley

    • Daily presentations focused on cloud-based and IP Topics
  • Chip Essentials Village

    • Demonstrations from leading companies providing essentials to SoC design.
  • Daily networking receptions Sunday – Wednesday

Design Infrastructure Alley
In 2018 there were IT and specialty vendors galore, with familiar names like:

  • Google Cloud
  • Microsoft
  • Cadence
  • Amazon Web Services
  • Metrics
  • Alibaba Cloud
  • IBM
  • Dell EMC
  • Univa
  • Footprintku
  • PureStorage
  • Rescale
  • Six Nines
  • Altair
  • Suse
  • ICmanage

These companies provide us the hardware, software and services needed while running EDA tools, licensing, storing massive data, security and even support cloud-based flows.

Chip Essentials Village
Let’s say that your company wants to exhibit at DAC on a budget, then check out the Chip Essentials Village because it offers an exhibit kiosk at a value price, presentation time in a theater and more.

DAC Experience
I’ve been attending the DAC conference since 1987 and I always come away filled with new insights learned from the Keynotes, foundries, EDA and IP vendors. You’ll rub elbows with system designers, architects, RTL designers, circuit designers, IC layout designers, CAD engineers, researchers, C-level executives, and of course the team of SemiWiki bloggers. There are about 60 technical sessions to attend, exhibits to peruse, and many networking opportunities.

About DAC
The Design Automation Conference (DAC) is recognized as the premier event for the design of electronic circuits and systems, and for electronic design automation (EDA) and silicon solutions. A diverse worldwide community of more than 1,000 organizations attends each year, represented by system designers and architects, logic and circuit designers, validation engineers, CAD managers, senior managers and executives as well as researchers and academicians from leading universities. Nearly 60 technical sessions selected by a committee of electronic design experts offer information on recent developments and trends, management practices and new products, methodologies and technologies. A highlight of DAC is its exhibition and suite area, with approximately 200 of the leading and emerging EDA, silicon, and intellectual property (IP) companies and design services providers. The conference is sponsored by the Association for Computing Machinery (ACM), and the Institute of Electrical and Electronics Engineers (IEEE), and is supported by ACM’s Special Interest Group on Design.