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December 24, 2016

NetSpeed Leverages Machine Learning for Automotive IC End-to-End QoS Solutions

NetSpeed Leverages Machine Learning for Automotive IC End-to-End QoS Solutions
by Mitch Heins on 12-24-2016 at 4:00 pm
Categories: Automotive, EDA, NetSpeed Systems

A couple of weeks back I wrote an article about the use of machine learning and deep neural networks in self-driving cars. Now I find that machine learning is also being applied to help build advanced end-to-end QoS (quality of service) solutions for the automotive IC market. With the advent of self-driving cars comes requirements to be able to deal with all of the data streams coming into the car. Many automotive system designers are turning to heterogeneous multi-core SoCs (system-on-chip) to meet the requirements of increased performance, reduced power consumption and increased overall system reliability.

These new SoCs are not your typical homogeneous multi-core ICs. Instead, they are heterogeneous SoCs with a variety of different compute engines each with widely varying requirements for QoS. Automotive SoCs may include CPU clusters, GPUs, communications cores (Wi-Fi, Blue-tooth, USB, 4G modem etc.), multimedia cores, GPS, DSPs, cameras, gesture processing, display / video and security modules to name a few.

These advanced heterogeneous architectures bring many challenges. The different cores come with dynamic and differing workloads, a mixture of different QoS requirements and the added complexity of having to share memory and interact with each other. Additionally, on-the-fly configurability is also desired to keep power consumption down as the SoC adapts to the different workloads and QoS requirements.

Many applications in self-driving cars also require high performance computing. At the hardware level this means that the multiple cores and modules require cache coherency. Designing coherent systems is hard enough when the data and the architectures are homogeneous but in these new automotive SoCs it’s even harder as the data and architectures are heterogeneous. Additionally, since these applications are running in a car they must be very robust and engineered to be secure and fault tolerant which means designers must architect their systems (software and hardware) to be deadlock free at the application level.

Traditionally system designers have built their own proprietary buses or on-chip communication fabrics. This however has become more difficult due to the use of multi-vendor IPs all of which have different speeds, latency, I/O and QoS requirements. In some cases, system architects have turned to multiple networks or segregated subnetworks to avoid bottlenecks caused by these differences.

So what does machine learning have to do with QoS solutions you ask? Enter NetSpeed Systems. NetSpeed offers a network-on-chip (NoC) synthesis capability. This tool set uses machine-learning algorithms to synthesize and optimize NoCs that are tuned for a user-defined combination of cores and modules with varying workloads and QoS requirements. One of the key benefits of machine learning is that it becomes possible to model the system as a whole, taking into account system interactions and understanding how they affect QoS. NetSpeed’s machine learning technology is designed to optimize performance and power efficiency broadly across use models. The beauty of this approach is that the software has the freedom to build new hybrid network architectures from among different network topologies such as multi-drop bus, ring, tree, and mesh.

Alternatively, system designers can specify a particular topology, overriding the tool’s choices. While human designers are good, humans augmented with fast automated machine learning algorithms are even better. See the diagram for typical bandwidth performance of synthesized networks over those that were manually tuned without the aid of machine learning algorithms.

NetSpeed’s NocStudio software takes experience from the design of much larger scale networks and applies them to the chip level problem. Like other networks, a network-on-chip must ensure QoS for signals traveling from one point on the chip to another within a specified time and without delaying other signals. Because NetSpeed’s NoCs are intended mainly for ARM-based SoCs, they connect directly to IP blocks that support AMBA and AXI protocols. Currently, NetSpeed supports protocols up to AMBA 5 but NetSpeed can also create gaskets for other protocols. At the network level, NetSpeed converts all traffic into a native format called the NetSpeed Streaming Interface Protocol (NSIP).

NocStudio automatically configures NetSpeed’s Orion (non-coherent) or Gemini (coherent) NoC architectures by allowing designers to integrate cores and modules from multiple vendors. As the design evolves, NocStudio updates system performance statistics, enabling designers to make trade-offs. Statistics include the link cost (the number of wires required for the interconnects) and the buffer cost (the number of flip-flops required to implement the necessary FIFO buffers). NocStudio can also automatically add pipeline stages to long wires to meet latency requirements and guarantee QoS. The QoS specifications may include such factors as the data-path bandwidth, transfer latency, service priority, and rate limits.

The end result is a set of synthesis-ready RTL code that implements a full-scale NoC including all of the logic required to ensure cache coherency between modules sharing memory. Not only does NetSpeed enable the automatic synthesis of the network logic but their solution also allows designers to get a first pass feel for the floorplan of the SoC that can be used as a guide for the IC layout team.

In the next week or so look for part II on this subject where I’ll go into more details about NocStudio and how a NoC works and what it looks like. In the meantime, see also:
Gemi-3 press release
NetSpeed raises $10M to bring Machine Learning to SoC Design and Architecture

December 23, 2016

Renewable Energy is On a Roll

Renewable Energy is On a Roll
by Bernard Murphy on 12-23-2016 at 12:00 pm
Categories: General

Since everything we build in this industry either runs on, stores or produces electricity, we should have a more than passing interest in how we get that power. A couple of organizations, confusingly named the IEA (International Energy Agency) and the EIA (Energy Information Administration – a US agency) provide lots of interesting information in this area.

I’ll start with the EIA who published an analysis of how energy was used in 2014 in the US, by source and by sector. The report covers energy in general, but I’ll just focus on generation of electricity. Electric power accounted for about 38% of all power consumed, of which 22% came from natural gas, 42% from coal, 13% from renewables and 22% from nuclear.

Telling even at that point was that over 90% of the market for coal was in power generation. A primary rule in business is never, ever let your business drift into high concentration with one customer or one market. Because if you do and markets shift, you’ll be in trouble, as coal seems to be now.

Now over to the IEA report, which looks at worldwide use for 2015, but primarily focused on renewables. Total renewable capacity grew by 153 GW thanks in particular to growth in wind power and solar power installations. Renewable installations in 2015 accounted for half of total capacity growth, also cumulative renewables capacity moved ahead of coal for the first time. The cost of new installations is also dropping significantly. Offshore wind power plant install cost is expected to drop ~40-50% within 5 years, onshore wind by ~15% and solar is expected to drop 25% in the same period driving, it would seem, a virtuous cycle for these technologies. Overall, worldwide renewable capacity is expected to grow 42% in the next 5 years.

Earlier in the year I posted a thread on how solar is quickly moving to utility-scale production, running at $50-70 per MWh which compares well with the best natural gas plants at $52-78 per MWh. But still, it’s worth putting this in perspective. In 2015, all renewable sources (including hydroelectric) contributed 13% of total capacity versus 20% for nuclear and 33% each for coal and natural gas (another EIA report).

We’re still a long way from an all-renewables world, if indeed that will ever be possible. The IEA projects that by 2040, 37% of worldwide power will come from renewables, natural gas demand will have grown by 50% (which would put US use at around 50%) and coal demand will essentially remain static, therefore declining quite a bit as a percentage of total demand, a trend already apparent when comparing the 2014 and 2015 stats for coal and natural gas. In other words, it isn’t just renewables that are ringing down the curtain on coal, it’s a combination of natural gas and renewables, and natural gas is the bigger threat to coal producers.

The EIA report is HERE and the IEA report is HERE. The other EIA report is HERE and the IEA 2040 projection is HERE.

Driverless Cars and our Global Economy

Driverless Cars and our Global Economy
by Daniel Payne on 12-23-2016 at 7:00 am
Categories: Automotive, General

While traveling to California this year I had my first Uber trip after a concierge in Santa Clara recommended it as the best way to get to the airport, instead of the usual and expensive taxi ride. Later in the year I had my first Lyft ride after my road bike broke down and I needed a ride back home. Our transportation choices are shifting, and probably one of the most talked about is the driverless car. This new transition is exciting for the electronics industry because of all the semiconductor, sensor and software involved to enable it.

A futurist named Thomas Frey is actually paid to think about the economic consequences of the driverless car, and he is the founding executive director of the DaVinci Institute. Sure, we know that some companies supplying the technology for the driverless car will see an increase in product and service revenue, however is there any downside? Yes, in April Mr. Frey predicted that the rise of autonomous vehicles will start to impact multiple sectors of our economy, and some of these will actually decrease the number of jobs.

One example of job loss is at the airport where many of us typically park our cars en route to taking a flight. With driverless cars there is a reduced need for airport parking, and therefore the revenues decline for the airport along with the need for those shuttle bus drivers, taxi cab drivers, Uber drivers, Lyft drivers and limo drivers. Another trickle down effect is on the auto dealers themselves, because we may not even need to own a vehicle, instead opting for just-in-time rides from a driverless service, so think about losing jobs in auto sales, auto maintenance, and even in the auto insurance and financing industries.

In a typical year I have my car looked at by the oil change store, tire store and local maintenance shop, but with a driverless car future I may not have need for any of these services anymore. Thinking about driving we need to remember those pesky speeding tickets, but with an autonomous vehicle our local police departments will have reductions in speeding tickets which effect their employment. Even the legal system with lawyers and judges would be trimmed a bit because we have fewer court cases involving auto drivers.

Making our cars smart enough to drive themselves is part of a growing AI trend that is slowly replacing customer service jobs around the globe, even factories are adopting more robotic devices to replace repetitive tasks once done by employees. Here’s a list of dozens of jobs that could down-size as autonomous vehicles pick up business (Source: Futurist Speaker):

Our society’s love affair with the automobile is slowly changing, so expect our economy to adjust for better or worse as driverless cars start to catch on.

December 22, 2016

The transport systems of Science Fiction will be here sooner than you think

The transport systems of Science Fiction will be here sooner than you think
by Vivek Wadhwa on 12-22-2016 at 4:00 pm
Categories: Automotive

Picture the commute of the future: You live in Palo Alto, Calif., but work 350 miles away in Los Angeles. After your morning latte, you click on a smartphone app to summon your digital chauffeur. An autonomous car shows up at your front door three minutes later to drive you to a Hyperloop station in downtown Mountain View, where a pod then transports you through a vacuum tube at 760 mph. When you reach the Pasadena station, another self-driving car awaits to take you to your office. You reach your destination in less than an hour.

That is the type of scenario that Hyperloop Transportation Technologies (HTT) chief executive Dirk Ahlborn laid out for me as we were preparing to speak together on a panel at the Knowledge Summit in Dubai on Dec. 5. He was not talking about something that would happen in the next century; he expects the first of these systems to be operational in the United Arab Emirates by 2020. The Abu Dhabi government has just announced that it has been working with his company to connect Abu Dhabi and Al Ain, two UAE cities separated by 105 miles, using the Hyperloop system.

A proposal for this mode of transportation came from Elon Musk in August 2013, in a paper titled “Hyperloop Alpha.” Musk envisaged a mass transit system in which trains travel as fast as 760 mph in pressurized capsule pods. These would ride on an air cushion in steel tubes and be driven by linear induction motors and air compressors. He claimed that the system would be safer, faster and cheaper than trains, cars boats and supersonic planes, for distances of up to at least 900 miles, and said that it would be resistant to earthquakes and generate more energy through its solar panels than it would use.

Straight out of science fiction it may be, but two start-ups took up Musk’s challenge to develop the technology: HTT and Hyperloop One. These companies have raised more than $100 million each and say they will have operational systems in three to four years and that they have governments backing them. Hyperloop One demonstrated elements of the technology in the Las Vegas desert in May 2016. The sheiks I spoke with in Dubai were most excited about HTT’s system.

Even if the Hyperloop technology doesn’t pan out, the digital chauffeurs surely are coming. Self-driving cars such as the Tesla that I drive can already take control of the wheel on highways and are able to monitor traffic around them better than humans can — because their sensors enable them to see in 360 degrees and communicate with each other to negotiate rights of way.

By 2020, self-driving cars will have progressed so far that they can drive safely at speeds as fast as 200 mph in their own partitioned lanes on highways. In these circumstances, the commute to Los Angeles from San Francisco would take only an hour and a half — without the need to catch a connection to a supersonic pod. From Abu Dhabi to Al Ain or Dubai could take the car 30 to 40 minutes, door to door. In other words, Elon Musk’s self-driving cars and HTT’s short-haul Hyperloops may be competing with each other. I’m one of those who would prefer the convenience of having their car come with them so that they can keep extra stuff in the back and be working uninterrupted on the commute. In any case, for longer journeys, say from New York or San Francisco to Miami, catching a Hyperloop will make more sense than riding in the self-driving car.

The point, though, is that we are on the verge of a revolution in transportation. For decades — actually, centuries — we have been dependent on locomotives and, more recently, airplanes to take us long distances. The technologies have hardly advanced. The entire industry is about to be disrupted. Many of us will choose to take the shared cars and Hyperloops; others will own their own cars. But we will take fewer rides in trains and planes.

That is why new rail-based transportation systems, such as the one that California has long been debating, are not sensible investments to make. By the time they are complete, our modes of mass transportation will have changed. The California project aims to move 20 to 24 million passengers a year from downtown L.A. to downtown San Francisco, through California’s Central Valley, in 2 hours 40 minutes. It is projected to cost an estimated $64 billion when completed by about 2030. By then, we will be debating whether human beings should be allowed to drive cars, and public rail systems will be facing bankruptcy because of cheaper and better alternatives.

The wise investment to make will be in accelerating adoption of self-driving cars and in reserving lanes for them, and in building energy-efficient long-distance transportation systems that do not consume even more time, money and arable land than we have lost already. For distances in the hundreds or thousands of miles, we’d do well to explore Hyperloops and other environmentally sensitive modes of mass transportation. They may be far more cost-effective than laying new railways.

For more, follow me on Twitter: @wadhwa and visit my website: www.wadhwa.com

December 22, 2016

7 Trends of IoT in 2017

7 Trends of IoT in 2017
by Ahmed Banafa on 12-22-2016 at 12:00 pm
Categories: AI, IoT

IoT is one of the transformational trends that will shape the future of businesses in 2017 and beyond. Many firms see a big opportunity in #IoT uses and enterprises start to believe that IoT holds the promise to enhance customer relationships and drive business growth by improving quality, productivity, and reliability on one side, and on the other side reducing costs, risk, and theft. By having the right IoT model companies will be rewarded with new customers, better insights, and improved customer satisfaction to mention few benefits.

With all this in mind, let’s explore some of the trends of IoT impacting business and technology in 2017:

1) IoT and Blockchain Will Converge
Blockchain is more than a concept now and has applications in many verticals besides FinTech including IoT. #Blockchain technology is considered by many experts as the missing link to settle scalability, privacy, and reliability concerns in the Internet of Things. Blockchain technology can be used in tracking billions of connected devices, enable the processing of transactions and coordination between devices; allow for significant savings to IoT industry manufacturers. This decentralized approach would eliminate single points of failure, creating a more resilient ecosystem for devices to run on. The cryptographic algorithms used by Blockchain would make consumer data more private. In 2017 IoT will converge with Blockchain for better security and privacy opening the door for a new category in applications, hardware, and talents.

2) IoT Devices and More DDoS Attacks
Forrester thinks that the recent #DDoS attack that hit a whopping 1600 websites in the United States was just the tip of the iceberg when it comes to the threat that the connected device poses to the world. That attack confirmed the fear of vulnerability of IoT devices with a massive distributed denial of service attack that crippled the servers of services like Twitter, NetFlix, NYTimes, and PayPal across the U.S. on October 21st, 2016. It’s the result of an immense assault that involved millions of Internet addresses and malicious software, according to #Dyn, the prime victim of that attack. “One source of the traffic for the attacks was devices infected by the #Mirai botnet”. All indications suggest that countless Internet of Things (IoT) devices that power everyday technology like closed-circuit cameras and smart-home devices were hijacked by the malware, and used against the servers.

3) IoT and Many Mobile Moments
IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. It touches everything—not just the data, but how, when, where and why you collect it. The technologies that have created the Internet of Things aren’t changing the internet only, but rather change the things connected to the internet. More mobile moments (the moments in which a person pulls out a mobile device to get what he or she wants, immediately and in context) will appear on the connected device, right from home appliances to cars to smartwatches and virtual assistants. All these connected devices will have the potential of offering a rich stream of data that will then be used by product and service owners to interact with their consumers.

4) IoT, Artificial Intelligence, and Containers
In an IoT situation, #AI can help companies take the billions of data points they have and boil them down to what’s really meaningful. The general premise is the same as in the retail applications – review and analyzes the data you’ve collected to find patterns or similarities that can be learned from so that better decisions can be made.

The year 2017 would see Internet of Things software being distributed across cloud services, edge devices, and gateways. The year would also witness IoT solutions being built on modern #Microservices (an approach to application development in which a large application is built as a suite of modular services. Each module supports a specific business goal and uses a simple, well-defined interface to communicate with other modules) and #containers (lightweight virtualization) that would work across this distributed architecture. Further, machine-learning cloud services and Artificial Intelligence will be put to use to mine the data that would be coming in from IoT devices.

5) IoT and Connectivity:
Connecting the different parts of IoT to the sensors can be done by different technologies including Wi-Fi, Bluetooth, Low Power Wi-Fi , Wi-Max, Ethernet , Long Term Evolution (LTE) and the recent promising technology of #Li-Fi(using light as a medium of communication between the different parts of a typical network including sensors). In 2017, new forms of wireless connections, such as 3GPP’s narrowband #NB-IoT, #LoRaWAN, or #Sigfox will be tested. Forcing IoT decision-makers to evaluate more than 20 wireless connectivity options and protocols, which is one step in the right direction of having standards for connectivity.

6) IoT and Talent-Shortage
Organizations launching IoT projects including smart cities and industrial facilities face a tougher time in recruiting talent. Complicating matters is that it remains a challenge to find enough workers to secure the Internet of Things. 45 percent of IoT companies struggle to find security professionals, according to a TEKsystems survey. 30 percent report having difficulty finding digital marketers. In 2017, industrial major vendors will invest in IoT training and certifications and make it part of the mainstream training programs in the tech industry.

7) IoT and New Business Models
The bottom line is a big motivation for starting, investing in, and operating any business, without a sound and solid business models for IoT we will have another bubble, this model must satisfy all the requirements for all kinds of e-commerce; vertical markets, horizontal markets, and consumer markets. A new business model including sharing cost of devices with consumers, reducing the cost of ownership and making UX less hassle and more joyful. 2017 will see new categories being added to smart markets. One key element is to bundle service with the product, for example, devices like Amazon’s #Alexa will be considered just another wireless speaker without the services provided like voice recognition, music streaming, and booking Uber service to mention few.

The Road Ahead
The Internet of Things (IoT) is an ecosystem of ever-increasing complexity; it is the next level of automation of every object in our life and convergence of new technologies will make IoT implementation much easier and faster, which in turn will improve many aspects of our life at home and at work and in between. From refrigerators to parking spaces to smart houses, IoT is bringing more and more things into the digital fold every day, which will likely make IoT a multi-trillion dollar industry in the near future. One possible outcome in the near future is the introduction of “IoT as a Service” technology. If that service offered and used the same way we use other flavors of “as a service” technologies today the possibilities of applications in real life will be unlimited. But we have a long way to achieving that dream; we need to overcome many obstacles and barriers at many fronts before we can see the benefits of such technology.

Ahmed BanafaNamed No. 1 Top VoiceTo Follow in Tech by LinkedIn in 2016

References:
http://www.iotworldnews.com/author.asp?section_id=508&doc_id=727678&
http://www.indianweb2.com/2016/11/08/internet-things-iot-2017-predictions-forrester/
http://www.ioti.com/iot-trends-and-analysis/11-iot-predictions-2017
https://www.linkedin.com/pulse/iot-standardization-implementation-challenges-ahmed-banafa?trk=mp-author-card
https://www.linkedin.com/pulse/wake-up-call-iot-ahmed-banafa?trk=mp-author-card
https://www.linkedin.com/pulse/securing-internet-things-iot-blockchain-ahmed-banafa?trk=mp-author-card
https://www.linkedin.com/pulse/last-mile-iot-artificial-intelligence-ai-ahmed-banafa?trk=mp-author-card
https://www.linkedin.com/pulse/iot-implementation-challenges-ahmed-banafa?trk=mp-author-card
http://blockgeeks.com/guides/what-is-blockchain-technology/cry

December 22, 2016

Floki Bot is Becoming an International Sensation with Cybercriminals

Floki Bot is Becoming an International Sensation with Cybercriminals
by Matthew Rosenquist on 12-22-2016 at 7:00 am
Categories: Security

Floki Bot, a new financial oriented malware, is popular with English, Portuguese, and Russian speaking underground criminal markets, winning over cybercriminals with new features and functionality. It is currently being used by a number of different cybercrime groups around the world and is being sold on the dark market for about $1,000 according to Flashpoint and Cisco Talos.

Improvements Abound
Floki Bot is a great example of evolutionary release-reuse tactics of hackers. Based upon the venerable Zeus Trojan 2.0.8.9 source code, which was released many years ago, this new bot variant sports many different technologies to bypass detection and eradication by security tools. It has an updated engine to avoid Deep Packet Inspection (DPI), a method for cybersecurity used to detect malicious software, and extensibility to use The Onion Router (TOR) network for masking network traffic sources. It uses a number of obfuscation techniques to hide its sensitive code. Floki Bot also sports advanced methods to capture data from one of their primary targets, Point-of-Sale (PoS) devices. Overall, it keeps many of the Zeus banking Trojan tricks while adding upgrades to stay current with the latest security controls and tactics.

Alternate Engineering
Based upon communication traffic analysis, it is believed that several different parties, possibly of different languages, might have contributed to the creation of this malware. As hackers do collaborate well, the result brings together a capable new malware to the stage. This is becoming more common. Bits of code and various experts working together to develop the next generation of malware.

In some cases, it is not intentional. There are several examples of when Nation States have conducted cyberattacks and other parties intercepted their well-developed code, only to reverse-engineer it, and use the parts they found interesting in their own projects. This is the way of the next generation malware author. They don’t need to know everything themselves. They can leverage a community for assistance and even reuse the best parts of other groups code for maximum effect.

Protections Must Adapt
If Floki Bot is any indication of the evolution for malware, we should expect faster cycles of release for more virulent code and methods. Teamwork will increase as groups work together to monetize efforts and fleece victims in more efficient and creative ways. The cybersecurity industry is not only fighting the malicious technology, but also the people who are innovating and collaborating to undermine the security, safety, and privacy of us all.

Interested in more? Follow me on Twitter (@Matt_Rosenquist), Steemit, and LinkedIn to hear insights and what is going on in cybersecurity.

December 21, 2016

Predictions for the IOT in 2017

Predictions for the IOT in 2017
by Bill McCabe on 12-21-2016 at 2:00 pm
Categories: IoT, Security

Although we are a far cry from Nostradamus, there are some fairly reliable predictions that can be made about 2017 and beyond.

The first bold prediction is that 2017 will see a bump in security, and a demand for skilled workers. Since there will be a growing demand for AI and the containers that are utilized to transmit information, there will be a need for individuals who can operate these core foundations.

Prototypes for certain financial transactions will be released. These transactions will utilize blockchain technology, and they will help to expedite and simplify several different types of transactions.

At some point, a massive large scale IoT security breach will occur. This will lead to most industries repairing their coding so that it becomes unbreakable in the future. The potential for better security systems will become a bigger part of this.

Further DDos attacks will then continue to happen. As hackers realize that they can do damage with the DDoS attacks by tapping into the internet of things, there will continue to be older devices that are used for these attacks, until they are remove from the internet. As more devices connect, there will be a need for additional security to take place. Fortunately, places like IBM and Cisco will step in and help to create certifications for devices to help ensure that that the security that is in place is of the highest caliber.

These firms will also likely begin to offer training that is either free for those in the industry, or offer it at a low enough cost that it offers value to developers who need professionals with this level of expertise.

All of this may be taken a step further with industry certified devices. Since the need for security protection will vary from one industry to the next, there is a chance that several certification vendors will come into play and help to ensure that each of the different industries will have what it needs for the IoT technology that it is providing.

What we see is that there is a potential for different advancements within the internet of things. While the actual results of what takes place may vary slightly, there is no denying that we are set to experience another year of growth and advancement in the industry. We can only hope that it continues to be as fascinating as 2016 has been and the years that follow continue to build off that momentum also.

Wishing you and your family a Merry Christmas and Happy New Year from the folks at @IoTRecruiting – and www.internetofthingsrecruting

iot, Internet of things, Bill McCabe

December 21, 2016

V2V: Loose Talk about Talking Cars

V2V: Loose Talk about Talking Cars
by Roger C. Lanctot on 12-21-2016 at 12:00 pm
Categories: Automotive

The U.S. Department of Transportation issued a proposed rule this week which may ultimately require the installation of a communications box in every car manufactured or sold as new in the U.S. The U.S. is alone in the world in pursuing such a mandate and the proposal, which requires years of additional evaluation, testing and definition before adoption, is based on 12-year-old technology that is rapidly being superseded by emerging cellular wireless and sensor-based systems.

http://tinyurl.com/h46kl6t – Notice of Proposed Rule Making – NHTSA

Coming at the end of the Obama Administration, the Notice of Proposed Rule Making, which is the official designation of the announcement, is something of a Hail Mary (i.e. last minute or desperate attempt) to find a solution to the rising toll of highway fatalities now approaching 100 lives lost every day. The announcement also reflects the reality that the U.S. DOT and the National Highway Traffic Safety Administration have no other solutions or policy plans in development to stem the tide of death – with the possible exception of the suggested expansion of the use of ignition interlocks for impaired drivers.

The proposed vehicle-to-vehicle technology is based on dedicated short range communication technology (DSRC) which is a form of Wi-Fi and provides for inter-vehicle communications between appropriately equipped vehicles. The concept is compelling and exciting, but the messaging regarding its efficacy and effectiveness is misleading.

Let’s take a look at the statements of the leaders at the USDOT regarding this technology:
From Transportation Secretary Anthony Foxx we have this relatively reasonable statement of fact:

“We are carrying the ball as far as we can to realize the potential of transportation technology to save lives. This long promised V2V rule is the next step in that progression. Once deployed, V2V will provide 360-degree situational awareness on the road and will help us enhance vehicle safety.”

The exaggeration begins with NHTSA Administrator Mark Rosekind:

“Advanced vehicle technologies may well prove to be the silver bullet in saving lives on our roadways. V2V and automated vehicle technologies each hold great potential to make our roads safer, and when combined, their potential is untold.”

Rosekind’s somewhat breathless enthusiasm overlooks the disconnect between the agency’s claimed capacity for V2V to help eliminate or reduce the severity of up to 80% of all crashes (once the technology reaches near full deployment) and the anticipated saving of lives – estimated to be between 955 and 1,321 in the 30th year of deployment or 2051. With an estimated annual cost of deployment of between $2.2B and $5B (based on NHTSA’s own estimates) that is $2.2M per life saved excluding the billions of dollars to be spent on infrastructure.

The agency emphasizes the fact that the V2V mandate is nothing more than an automated vehicle beacon combining GPS and Wi-Fi information to broadcast vehicle location data (location, heading, speed) at 10x/sec. The mandate does not require reception of the vehicle signals nor does it require in-vehicle displays or interfaces and it does not require implementation of the applications that might actually prevent crashes.

V2V informational videos on the NHTSA Website, point out that drivers must remain in control and that the beacon signals are nothing more than warnings which may be conveyed to the driver via tones, displays or seat vibrations – none of which are specified or required by the mandate – nor are they included in the projected cost per vehicle estimated at more than $300 at launch. The NHTSA announcement also glosses over the fact that the mandate is not expected to be finalized until 2019 with initial deployment commencing in 2021.

The significance of the 2019/2021 timeframe is the fact that by that time the first 5G cellular networks will have begun being installed around the world using some of the same wireless spectrum as DSRC and offering the same or superior communication capabilities. The importance of that reality is borne out by the informational videos on the NHTSA.gov Website.

The videos describe four applications: do not pass (DNP), intersection movement assist (IMA), emergency electronic brake light, and blind spot warning. (The videos also show cross-traffic alert technology already available in existing advanced driver assistance systems.) All of these applications can be fulfilled today with sensor-based technologies or, in the near future, with cellular LTE-V2V or 5G technology.

The key difference between DSRC and cellular-based technologies is the fact that car companies are already building cellular connections into cars. And those cellular connections have commercially motivated and business model justifying applications.

The USDOT is essentially proposing that an entirely new wireless network be built from scratch without any commercial purposes other than safety, though the agency is quick to note in its press release:

Separately, the Department’s Federal Highway Administration plans to soon issue guidance for Vehicle-to-Infrastructure (V2I) communications, which will help transportation planners integrate the technologies to allow vehicles to “talk” to roadway infrastructure such as traffic lights, stop signs and work zones to improve mobility, reduce congestion and improve safety.

Here, too, cellular communications are already being employed to communicate traffic light information to cars – as shown recently by Audi and introduced two years ago by BMW. BMW, Daimler and Volvo are already deploying inter-vehicle road hazard communications using cellular.

Again, the key differentiator is that the cellular infrastructure is already in place, the investments have already been made. At a time when the U.S. is wrestling with crumbling bridges and tunnels, there is precious little money left to stand-up a new wireless network to potentially enhance driving safety in the interest of saving 1,000 lives out of 35,000 annually. Bigger life-saving gains can be made sooner with existing technology.

In the Notice of Proposed Rule Making the agency notes that it considered two regulatory alternatives:

An “if-equipped” standard with performance requirements. The agency says it felt that “anything short of a mandate for universal V2V capability on all new vehicles would not lead a sufficient fraction of the vehicle fleet to be equipped with V2V to enable full realization of the technology’s potential safety benefits.”
Requiring that V2V-capable vehicles also be equipped with the two safety applications analyzed in this proposed rule – Intersection Movement Assist (IMA) and Left Turn Assist (LTA) – in addition to V2V capability. But the agency felt these two applications were not ready for deployment

What is obviously missing from the USDOT’s deliberations is the potential for cellular technology to be used as an alternative to DSRC. The determined myopia of the USDOT after more than 12 years of work on DSRC is stunning and suggests that the time is indeed ripe for new leadership.

Yet unresolved is the definition and creation of the Secure Credential Management System (SCMS) required to support the inter-vehicle and vehicle-to-infrastructure communications. In the words of one anonymous V2V skeptic: “Someone needs to ante up the funds to build and operate the SCMS and while the (USDOT) guidance addressed the needs and some technical issues, there are still some significant unknowns regarding the SCMS (who operates, how they operate, governance, funding, etc.) and it’s a big complex system so it won’t be easy to build. And nothing works without the SCMS.”

The USDOT and its supporters have also suggested that V2V will be an essential element of automated driving. But in none of the official USDOT materials is there any suggestion that V2V technology is intended to enable self-driving cars. The USDOT is quite clear on this point: the driver remains in control. V2V is intended solely to provide driver alerts.

Finally, General Motors is still the only car company with announced plans to deploy V2V technology in 2017 which will be in advance of a completed standard or mandate. No other car company has followed GM, suggesting lingering skepticism throughout the OEM community in spite of the official stated support of the Alliance of Automobile Manufacturers.

V2V is not the answer to the car-inflicted carnage on U.S. highways. No other government anywhere else in the world has come to the conclusion that V2V is the solution. V2V a clever protocol that is most likely to see adoption within the existing cellular network. But the Notice of Proposed Rule Making ensures ongoing funding ($700M-$800M already spent by the government alone) and Federal support into the incoming Trump Administration. It is highly unlikely that Trump will pump the brakes on DSRC. See you at the inauguration.

Roger C. Lanctot is Associate Director in the Global Automotive Practice at Strategy Analytics. More details about Strategy Analytics can be found here: https://www.strategyanalytics.com/access-services/automotive#.VuGdXfkrKUk

December 21, 2016January 27, 2022

IEDM 2016 – Marie Semeria LETI Interview

IEDM 2016 – Marie Semeria LETI Interview
by Scotten Jones on 12-21-2016 at 7:00 am
Categories: CEO Interviews, FD-SOI

Marie Semeria is the CEO of Leti, one of the world’s premier research organization for semiconductor technology and the key development center for FDSOI. I first interviewed Marie at SEMICON West and at IEDM I had a chance to sit down with her and get an update on Leti’s efforts over the last several months.

My interview with Marie at SEMICON West is available here.

FDSOI
When I spoke to Marie at SEMICON West we discussed the long-term roadmap for FDSOI with extendibility down to 10nm and even 7nm. At the time GLOBALFOUNDRIES had announced their 22FDX technology and that there would be a follow on FDSO technology but had not announced what it would be. At that time Marie noted that Leti was working with GLOBALFOUNDRIES, since then GLOBALFOUNDRIES has announced 12FDX as their next generation technology. Marie noted that Leti continues to work with GLOBALFOUNDRIES to make 22FDX happen, design 12FDX and implement the required ecosystems.

In September it was announced that Sony has developed a smart watch GPS chip with ST Micro on FDSOI. The chip provides 10x the battery life of a bulk chip and the watch utilizing the chip will be announced in the USA and Europe next month. In September GLOBALFOUNDRIES also announced 60 tape outs and Samsung has 16 tape outs on FDSOI. Approximately one half of the tape outs should be products 18 months later, several products should appear at the end of next year.

One of the key attributes of FDSOI is the revolutionary ability to tune the wafers after they come out of the fab using biasing. Designers need to be trained to use back biasing and Leti has designed specific IP for this application. GLOBALFOUDNRIES has an initiative to have a complete design and IP ecosystem and Leti is involved in making this happen.

ST Micro is capitalizing on 28nm FDSOI for MCU and automotive applications. FDSOI inherent radiation hardness makes it ideal for automotive applications.

Another strength of FDSOI is in the RF space where FDSOI has >2x the performance of FinFETs. LETI has already reported FT/Fmax=390/385GHz at 28nm, good analog performance and reduced noise and good RF efficiency of the back gate yielding good RF designs. FinFETs low Ft is mainly impacted by strong parasites capacitances and Fmax mainly impacted by Gate resistance (Gate last process)

One of the biggest collaborations for Leti in FDSOI is with Soitec to optimize the substrates. It is very important to be able to give Soitec the device feedback and understand the impact of the substrate on the device and to be able to understand the contribution of the device and the substrate.

Leti is also working on new ways to leverage FDSOI and at IEDM presented a paper on integrating a photodiode under the Box layer to generate bias under the Box.

Horizontal Nanowires
Horizontal Nanowires (HNW) is an area of intense research in the industry. Both FinFETs and FDSOI devices are facing fundamental scaling issues around the 7nm node and are reaching thickness and electrostatic control limits. HNWs have a process very similar to FinFET formation and represent an evolutionary path with superior electrostatics. Leti has been working on HNW for 10 years whereas IMEC started with vertical nanowires before switching to HNW more recently.

Similar to the FDSOI work described in my SEMICON article (see above), Leti develops models of HNW, then they build test devices and calibrate and confirm the model to give confidence to model based projections. Leti has a long history of stressors in the substrate and S/D and they can carry that over to HNW. They have the full model that has been confirmed and characterized to use for HNW.

Leti has two HNW efforts, one with ST Micro and relaxed geometries and one with IBM at scale. Leti has presented a compact model of HNW stress they developed with IBM. The model integrates quantum effects and stress and is confirmed by experimental data. Their experience in stressors is very useful for tuning very advanced devices

At IEDM Leti presented a paper on a stacked HNW technology with raised source/drains including for the first time a silicon germanium (SiGe) raised S/D to strain the pFET channel. The pFET had a SiGe:B (boron doped SiGe) raised S/D and the nFET had a Si:P (phosphorus doped silicon) raised S/D. They used an inner spacer and wet etch to etch out the SiGe layers releasing the Si nanowire while protecting the SiGe:B raised S/D.

The basic process flow is:

Super lattice deposition (alternating SiGe and Si layers)
Fin patterning – similar to FinFET process except that two different materials are etched
Dummy gate formation – similar to FinFET
Spacer formation – similar to FinFET
Inner spacer formation – CD recess with wet etch, second deposition and etch back to form a spacer in the recess
Source/drain epi – similar to FinFET
ILD and CMP – similar to FinFET
Dummy gate removal – similar to FinFET
Nanowire release etch – wet etch
Gate stack formation – similar to FinFET
Contact and back end of line – similar to FinFET

As can be seen from the process flow above, only a few steps are different from FinFET processing although the difficulty of the integration issues should not be underestimated.

Non-Volatile Memory
Leti has developed a test vehicle for comparing nonvolatile memory: MRAM, OXRAM, PCRAM, CBRAM on the same test vehicle. They are working to benchmark and optimize the nonvolatile memory for each design. RRAM is interesting for computing application. With Spintech they are working on MRAM. They have set up a roadmap to very low power MRAM using a new type of spin. They are working with GLOBALFOUNDRIES and Samsung on MRAM and ST Micro on PCRAM.

Conclusion
In conclusion Leti is working with GLOBALFOUNDRIES, Samsung, Soitec and ST Micro to commercialize FDSOI while also pursing next generation HNW and nonvolatile memory technologies for future generations.

Also Read:

CEO Interview: Dündar Dumlugöl of Magwel

CEO Interview: Jack Harding of eSilicon

CEO Interview: Randy Caplan of Silicon Creations

December 20, 2016

Semiconductors flat for second straight year

Semiconductors flat for second straight year
by Bill Jewell on 12-20-2016 at 4:00 pm
Categories: Semiconductor Intelligence, Semiconductor Services

The global semiconductor market posted strong 11.6% growth in 3[SUP]rd[/SUP] quarter 2016 from 2[SUP]nd[/SUP] quarter, according to WSTS. This strength is reflected in the 3[SUP]rd[/SUP] quarter revenue growth reported by the major semiconductor suppliers. Of the 12 companies, half (Intel, Samsung, Broadcom, TI, Micron and Toshiba) reported growth of over 9%. The other six companies reported revenue growth in range of 2.3% to 8.1%.

The 4[SUP]th[/SUP] quarter of 2016 looks weak based on the available guidance from the above companies. Six companies projected declines in 4[SUP]th[/SUP] quarter revenue from 3[SUP]rd[/SUP] quarter based on the midpoint of their guidance. But the upper end of guidance from four of these companies (Intel, Qualcomm, Broadcom and NXP) is for 4[SUP]th[/SUP] quarter growth. Only Micron Technology (for its fiscal quarter ended in early December) and STMicroelectronics are guiding for increases based on midpoint guidance. Samsung and SK Hynix did not provide revenue guidance, but both stated demand for their memory products will be strong in the 4[SUP]th[/SUP] quarter.

2016 will be another basically flat year for the semiconductor market following a 0.2% decline in 2015. Recent forecasts call for a range of a 0.9% decline (Gartner) to a 1% increase (IC Insights). Our Semiconductor Intelligence projection in August was a 2% decline. However with the strong 11.6% 3[SUP]rd[/SUP] quarter growth, a modest 1.3% gain in 4[SUP]th[/SUP] quarter would drive a slight 0.1% annual growth in 2016. We are confident overall 4[SUP]th[/SUP] quarter market growth will be sufficient to drive a slight positive gain for the semiconductor market in 2016. We are revising our 2016 forecast to 0.1% growth.

The projections for 2017 are generally for moderate growth in the semiconductor market, with most in the 3% to 5% range. Our latest forecast at Semiconductor Intelligence is 8% growth in 2017, the same as in our August forecast. The scenario is based a moderate improvement in end demand for electronics, the quarterly trend driven by 2016 and a modest inventory recovery. In October, Gartner projected the total units of PCs plus tablets would decline 0.7% in 2017 after an 8.7% decline in 2016. Total mobile phones should move from a 1.6% decline in 2016 to a 1.2% increase in 2016. IC Insights in November called for a slight acceleration in smartphone unit growth from 4% in 2016 to 5% in 2017. Thus no strong growth in key electronics devices in 2017, but an improvement from 2016.

The world economy should show modest improvement in 2017, with GDP growing 3.4% compared to 3.1% in 2016 according to the International Monetary Fund (IMF). Among advanced economies, improved GDP growth from the U.S., Canada and Japan will more than offset weaker growth in the UK and Euro Area countries. In emerging and developing economies, steady growth in India and southeast Asia and recoveries in Russia and Latin America should more than compensate for slowing China growth.

Downside risks to the forecast are significant. The impact of Brexit, the UK’s vote to withdraw from the European Union, is difficult to estimate. U.S. President-elect Donald Trump has threatened high tariffs against China. A trade war between China, the largest electronics producer, and the U.S., the second largest electronics consumer after China, would negatively impact the electronics and semiconductor markets in the near term. The continuing conflicts in the Middle East and global terrorism threats could also disrupt the economy. Despite these risks, the overall global economy is healthy and should show modest improvement in 2017.