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Heads Up! Photonics West is Just Around the Corner

Heads Up! Photonics West is Just Around the Corner
by Mitch Heins on 12-04-2016 at 4:00 pm

As I write about integrated photonics I continue to hear from long-time experts in the field who lament that integrated photonics has been around for decades and other than telecom/datacom, it seems to never be a mainstream technology. It’s hard to argue that this time around it will be different as those people have lived through some very lean times for photonics and are rightfully pessimistic. They had high hopes ten or fifteen years ago and those hopes didn’t come to fruition. It takes a brave soul to take the risk of getting re-energized and passionate about something knowing full well those hopes could be dashed yet again. Then there is another set of people who are newly curious about integrated photonics and these people inevitably run into those industry experts and suddenly we have self-fulling prophesy. We convince ourselves that photonics didn’t take off before so it won’t take off now.

I am however nothing if not an optimist and a dreamer. I’m an inventor looking for ways to make the world better and I am forever intrigued by the wonders of nature and its physics and thus I forge on. It’s with that mind set that I am excitedly looking forward to attending the upcoming SPIE Photonics West show to be held at the Moscone Center in San Francisco January 28[SUP]th[/SUP] – February 2[SUP]nd[/SUP]. If you have never been to the Photonics West show and if you are the least bit curious about photonics, integrated or otherwise, you should take the time to visit scenic San Francisco and check out this show. The full program can be found here www.spie.org/pwprogram. The show boast two free expositions and three for-pay conferences in one venue and if you are a gadget person, you will simply be amazed at the array things on display at these exhibitions. The two free expositions are BIOS (the world’s largest biomedical optics and biophotonics exhibition) and Photonics West (the premier photonics and laser event of the year).

The BIOSexposition and conference runs Saturday and Sunday, January 28[SUP]th[/SUP] and 29[SUP]th.[/SUP], and focuses on topics like biomedical optics, photonic therapeutics and diagnostics, neurophotonics, tissue engineering, translational research, tissue optics, clinical technologies and systems, biomedical spectroscopy, microscopy, imaging, and nano/biophotonics. Free exhibitions are included from 200 companies in this space.

The Photonics Westexpositions run Tuesday through Thursday, January 31st – February 2nd. There are two conferences coincident with the exhibitions, LASE and OPTO, that concurrently for the entire week from January 28th through February 2nd. LASE focuses on topics like laser source engineering, nonlinear optics, laser manufacturing, laser micro-/nano-engineering, and 3D fabrication. OPTO focuses on topics like optoelectronic materials and devices, photonic integration, displays and holography, nanotechnologies in photonics, advanced quantum and optoelectronic applications, semiconductor lasers and LEDs, MOEMS-MEMS, and optical communications from devices to systems. Free exhibitions are available during Photonics West from over 1,300 companies

The show is expected to draw over 20,000 attendees with over 4,800 papers and 72 courses and workshops available for those who want to tune up their technical skills. As part of the free exhibitions there are also a couple of forums that you might want to attend to better understand the market opportunities that lay ahead. The first is these is the Biophotonics Executive Forum which is a half-day session that includes discussion on global optics and biophotonics markets and emerging technologies. The second is the SPIE Photonics Industry Analysis: 2017 Update which will cover sizes of markets, geographic distribution, components and applications. Lastly there are a number of panel sessions that are available as part of the free exhibitions. These cover a wide range of topics from virtual reality, 3D printing, silicon photonics and ICs, solid-state lighting and advice for photonic startups. Check out the SPIE website here for more details on how to register and attend.

If this conference doesn’t light your fire for photonics, your wood is wet. I hope to see you there!


The post election Semicap bubble just burst in one day

The post election Semicap bubble just burst in one day
by Robert Maire on 12-04-2016 at 12:00 pm

Back to a more normal reality… Market gets”De-Fanged”… Where to from here? The “Icarus” Effect… Much of the market, and especially Tech & “FANG” (Facebook, Amazon, Netflix & Google) stocks gave back most all of their post election day gains in one session. The faster the stocks rose, the faster they gave it all back with some of the higher fliers such as Lam , Ultratech and FORM off 7% on Decemebr 1st.

In general SEMICAP stocks seemed to be off by an average of roughly 5%. The reality is that the stocks went up for no real reason (as nothing substantial had changed over the last month) and came back down for no real reason- no downgrades or major announcements in the space. Nothing much changed either way, up or down.

Nothing new to drive the stocks…
Over the last month the stocks have been rising for no good reason other than a post election rally. There was no significant news in the semiconductor space and no discernible change in momentum. We were well past earnings and no surprises or pre-announcements to speak of. Nothing to move the stocks other than the stock market itself…..

Business remains good….but we knew that already….
3D NAND, 10NM and 7NM spending remains on track and DRAM has been spending much better so all has been good, in fact better than expected, but this has not been new news as we have known for a while that the second half would be better than expected and even overflowing into Q1 of 2017. Expectations and estimates haven’t changed, and most companies still are seeing record or near record business.

Life in a fourth order derivative market and stocks…
As it has always been, Semicap stocks and Semicap companies remain at the end of the whip and most levered, both up and downward to variations in the economy and markets. The Global market, drives the US market, drives tech stocks that drive semiconductor companies that ultimately drives semiconductor capital equipment spending and companies. The global market has the sniffles, the US sneezes, tech stocks catch a cold, semis get pneumonia, and semicaps drop dead…… thats why semicap stocks were off 5% in one day, while tech was off about 1.5% but also why its fun and exciting to invest in them.

Will there be a “dead cat bounce”?
We didn’t see much of a bounce during the trading session as the stocks fell hard in the morning and continued to drift downward for the remainder of the day. We think that the selling was driven by a bit of an element of fear and greed as some investors wanted to sell to try to lock in recent gains coupled with fears of a bigger correction. Investors we spoke to did not seem to be willing to fight the tape and may stand on the sidelines tomorrow hoping that not much happens on a Friday.

Falling through some support levels…
Some stock broke below some important psychological barriers that may be a bit more concerning. LRCX fell hard through the $100 mark , dropping 7%. ASML broke just below $100, closing at $99.99, down 3%. AMAT just managed to hold onto a “3” handle. Even though AEIS was off 5.6% it still was up overall over the past month so there could be more of a correction coming for some stocks like this that haven’t given back all their gains yet.

Industry Cyclicality and cheesy horror movies….
Fear of the cyclicality “boogey-man” remains a significant overhang in the stocks. Although company management claims the industry is no longer cyclical or that at the very least , cyclicality has been greatly reduced, most investors don’y buy it…..Its like telling a child having a nightmare that there’s no such thing as the “boogey-man”.

Cyclicality is much like Jason in the Friday the 13th series of movies. He gets run over, shot, drowned, burned and dies a hundred deaths yet always seems to rise again to terrorize investors……you just can’t seem to keep him buried…..

So whats an investor to do???….
We don’t think we want to be in the way of potentially falling spears or be a hero trying to swim against what was a very strong tide of selling. It feels a lot like the stocks should settle back in to where they were before things got stupid, meaning somewhere around pre-election levels.

There is no significant catalyst to believe otherwise. We don’t think Trump’s election is really going to spur 3D NAND consumption or speed the pace of 10NM and 7NM investments. If anything, Trump may be less of a friend to the Semicap industry that has many technical workers under a visa program he wants to get rid of. He continues to threaten a trade war with China. Also, we live in an industry where much of the actual manufacture of products has been moved overseas over the last ten to twenty years.

This leads us to believe that the stock bubble we experienced was more of an empty, knee jerk reaction rather than calculated analysis of the potential benefits of a new administration to the industry. Investors who realize that the stocks went up for no reason will not likely bid them up again in the near term.

If there were an overreaction on the negative side to below pre-election levels, we might be tempted to step in and selectively buy stocks with good fundamentals or those that got overly beat up for no good reason.


Scalability of Industrial IoT applications

Scalability of Industrial IoT applications
by Akeel Attar on 12-04-2016 at 7:00 am

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Industrial IoT applications typically start with a small scale pilot application to demonstrate how some items of equipment and their related sensors can be connected to the cloud and to understand what algorithms are required to automatically extract value from the arriving streams of measurement data. Following on from a successful pilot application the next step will usually be scaling up the solution to automatically monitor many more items of equipment which is likely to require a solution capable of processing data from thousands of devices and hundreds of thousands of measurements.

The XpertRule Rules, Decision & Analytics engine supports large scale IoT deployments through its unique ability to deploy distributed decision making to any part of the IoT ecosystem; IoT edge/fog, Cloud and Mobile devices all from the web / cloud based Decision authoring environment.


Cloud based deployment
The cloud based Decision Engine deployment supports large scale applications through its modular software structure and ability to automatically deploy mirrored instances of the same application across multiple servers. The modular software structure allows separate definition of libraries of data processing and predictive algorithms and rules based templates for monitoring different types of equipment and devices. This makes adding new equipment straightforward and changes to monitoring algorithms and templates are automatically propagated across all equipment types using these libraries. As more devices and equipment are monitored further servers and instances of the XpertRule engine are used to provide increased processing capacity.


IoT edge hub deployment
Deploying Rules, Decision and analytics engine at the IoT edge reduces the reliance on a connection to the cloud and can provide real time response to local problems and minimise the amount and frequency of data sent to the cloud. In addition data remains local where there are restrictions on sharing with the cloud due to confidentiality / security requirements. Reduction in data traffic between edge devices and the cloud can be substantial as there is only a need to report significant events or aggregated data to the cloud. This in turn greatly reduces the requirements for cloud based monitoring algorithms and minimises the need for increased processing capacity as more devices and equipment are added.

Mobile device deployment
Deployment of the XpertRule Decision and Analytics engine on mobile devices supports local troubleshooting of equipment and device problems by field personnel. Guided workflows can guide non expert users through diagnosing and resolving problems so that the requirement for visits from centralised specialist resources are minimised. This has the advantage of the faster resolution of problems as well as preventing the availability of specialist resources becoming a bottleneck to large scale solution deployment.


Nvidia Drives into New Market with Deep Learning and the Drive PX 2

Nvidia Drives into New Market with Deep Learning and the Drive PX 2
by Tom Simon on 12-03-2016 at 7:00 am

Nvidia has found that video games are the perfect metaphor for autonomous driving. To understand why this is so relevant you have to realize that the way self-driving cars see the world is through a virtual world created in real time inside the processors used for autonomous driving – very much like a video game. It’s a little bit like the Matrix, only it is real. Perhaps this was the realization that caused Nvidia to enter the autonomous driving (ADAS) market. Regardless it certainly also has a lot to do with the truly massive computing power they are putting into their latest products.

Nevertheless, the Occupancy Grid which is the virtual world that the ADAS system creates to model the real world around the vehicle is very much like a video game. I learned more about how it works at a recent event hosted by Synopsys and SAE. Shri Sundaram a Product Manager from Nvidia spoke about their offerings for ADAS. He framed his discussion by reviewing where our current era of computing fits into the big picture.

In 1995 there were probably one billion PC users, by 2005 there were two and a half billion mobile users. Today we are looking at a world with hundreds of billions of devices – this is the age of AI and intelligent devices. It is fueled by deep learning and GPU’s. This has set the stage for self-driving vehicles. They promise to be safer, will allow us to redesign our transportation infrastructure, and offer a wider range of mobility services.

It will be great for people – driving is not always fun and can be difficult. It is this difficulty that makes automating it a challenge. Not just a technical challenge either. There is consumer acceptance and the regulatory environment to deal with. Yet, just focusing just on the technical side there are many challenges.

Shri lists the technical challenges as: sensors and fusion, massive compute requirements, algorithm development, and assuring functional safety. He spoke first about sensors. Sensors are used for navigation, detection and classification, and avoidance. We see GPS, inertial motion unit (IMU), multiple cameras, LiDar, radar, sonar and ultrasonic sensors. These create huge bandwidth requirements. Cameras are each over 2MP and running at 30fps. Lidar can provide over 500K samples per second. All of this needs to be fused in real time to create the occupancy grid.

Localization is the first task – using sensors and map data, the ADAS system needs to determine the location of the vehicle. At the same time, more information is needed to successfully navigate through the environment. The ADAS system will combine all the map data, location data, and perceived environment to plan actions and execute them. As Shri pointed out, there are many exceptions – snow or leaf covered roads, pedestrians, people directing traffic, construction zones, emergency vehicles, etc.

Nvidia has developed an SDK for self-driving cars called Driveworks. It uses deep learning to help perform path planning for self-driving vehicles. Driveworks runs on Nvidia’s Drive PX 2 ADAS hardware. It uses multiple layers of deep learning to separately perform operations like road surface identification, object detection, lane detection, and others and then combine those into a composite model.

Drive PX 2 sports 2 Parker Tegra Cores, 2 Pascal GPU’s and consumes about 80W when in normal operation. Shri said that it has the equivalent compute power of about 150 Mac Book Pro’s. Their next generation will have even more processing power and will require only about 20W.

We have all heard about the recent announcement of the partnership between Tesla – the auto company, not the namesake Nvidia GPU. In addition, Shri spoke about several other self driving cars that are in development and using Nvidia AI. These include Baidi, nuTonomy, Volvo, TomTom, and WEpods.

It’s clear that Nvidia is taking a lead role in the rapidly developing ADAS market. It’s no surprise that they accepted the invitation to present during the SAE and Synopsys Seminar. Nvidia uses a number of Synopsys tools in the development of systems like Drive PX 2. The range of Synopsys products that address ADAS systems is wide. Starting at system design and modeling and moving all the way down to IP and physical implementation. For a better understanding of these offerings be sure to look more closely at the Synopsys Automotive web page.

Read More Articles by Tom Simon


These 2 Markets to Drive IC Market Growth through 2020

These 2 Markets to Drive IC Market Growth through 2020
by Daniel Payne on 12-02-2016 at 8:00 pm

Spotting trends is an essential insight for marketing folks, general managers and C-level executives in our semiconductor industry. You could read hundreds of press releases, attend dozens of conferences, and interview all of the major thought leaders to help spot an emerging trend, or you could subscribe to a service like IC Insights to answer your questions. I just read their latest research bulletin and they conclude that the top two semiconductor market segments are:

  • IoT
  • Automotive

The highest growth rate comes from IoT (Internet of Things) which could be at a 13.3% CAGR to $12.8B by 2020.

The number 2 segment is automotive, growing some 12% to $22.9B by 2020. Other growth rates in declining order include:

  • Medical
  • Digital TVs
  • Servers
  • Cellphones
  • Standard PCs
  • Set-top boxes

The two markets projected to decline through 2020 are:

  • Tablets
  • Game Consoles

Our family uses three tablet devices and two game consoles, so it makes me feel a bit sad to see declines in these markets. Readers of SemiWiki see that IoT and Automotive are quite popular topics, and that there are menu links at the top of each page for these two market categories so you can get all the latest news. EDA and semiconductor IP companies are also aligning their product and service offerings in these two growth areas: IoT and Automotive.

Looking at just pure market size, we see the two stalwart segments of Cellphones and Standard PCs, totaling $128.8B in estimated sales. There was an estimated 5% decline in Standard PC integrated circuit sales in 2016, while game console IC revenues dipped 4%, and tablets fell at 10%.

The actual report is a heavyweight tome at 492 pages, so the level of detail should satisfy the most curious marketer. Pricing for the report is $3,690 for individuals and $6,790 for a corporate license.

Read the complete research bulletin here as a PDF document.


ISO 9001:2015 – Not Just for the Big Guys

ISO 9001:2015 – Not Just for the Big Guys
by Tom Simon on 12-02-2016 at 7:00 am

If you are like me, you remember the banners that large companies put up years ago when they achieved ISO 9001 compliance. It seemed at the time that this was something only for large companies. Since its introduction in 1987 ISO 9001 has both evolved as a standard and has become an achievement that not just large manufacturing companies can attain. There have been updates to the standard in 1994, 2000, 2008 and the most recently in 2015. The latest version of the standard is approximately 30 pages long. However, it differs from the previous version in several important ways.
First off – some of the basics. W. Edwards Deming is famous for saying that if something is not measured, it cannot be improved. The ancillary observation is that once something is measured, it will improve. ISO 9001 aims to allow an organization of any size determine what efforts are necessary to improve quality and then undertake and improve those efforts over time to continuously increase quality. Another of Deming’s ideas is Plan-Do-Check-Act (PDCA), which is a circular way to carry out processes. By embracing PDCA, a mechanism for continuous improvement is built into ISO 9001.
Companies need to define and perform processes to meet this objective. It worth noting that a process is not a procedure. A procedure is a step by step way of doing something. As such it tends to be a static list of steps for a given task. A process is established by defining in the inputs and desired results. The actual method is left open, with the assumption that there is expertise possessed by those performing the process. ISO 9001 relies on processes not procedures for the very reason that there can be evolution and improvement.

ISO 9001 starts with “context of the organization”, which essentially is a thorough way of identifying all the things that affect quality and that are affected by quality. The categories that these are drawn from is extensive. There is an external context and an internal context. These include suppliers, contractors, regulatory agencies, customers, competitors, management, employees, etc. Context can include social, technological, environmental, ethical, political, legal, and economic factors. The ISO 9001 process entails documenting these and then exploring the relationships with all of them. This can lead to open ended thinking about how to improve customer satisfaction, increase business, improve products, improve marketplace goodwill, or positively affect other tangible or intangible success metrics.

One of the biggest changes in ISO 9001:2015 is the shift to “risk based thinking” instead of the narrower “preventative action” from earlier revisions. One counterintuitive notion in ISO 9001:2015 is that “risk” can include the possibility of a positive or beneficial outcome. Risk is defined broadly as an effect of uncertainty. Any source of uncertainty, internal or external, can affect the quality of a result. Companies adopting ISO 9001:2015 need to thoroughly think through and document all sources of risk. To manage risk various actions can be taken. With the broader net that risk based thinking encourages, organization may identify risks proactively, instead of waiting for problems to manifest before taking preventative action.

ISO 9001:2015 puts increased emphasis on engagement with the highest levels of management. If a quality management system (QMS) is an afterthought carried out with no high-level sponsorship, it will not have the aegis or resources to be effective. ISO 9001:2015 requires up front involvement with the organization’s leadership. If this is baked in at the outset, the likelihood of success is dramatically improved.

Companies have wide latitude in how they initially document their quality management system and how they use it in practice. However, certification is becoming increasingly important. The ISO organization does not do the certification themselves. ISO published the standard which is drafted by a technical committee known at TC 176. There are accredited third parties that perform certification. An organization seeking certification would use one of them.


As I began this article – it’s not just the big car makers or telecom companies that are taking advantage of ISO 9001:2015; rather a number of smaller companies are seeing the advantages for themselves and their customers in adopting the standard. In EDA and IP there is an increasing number of these. Nowhere is this more important than for IP that relates to security and storage of vital information. One such company that has adopted ISO 9001:2015 is Sidense – supplier of IP for one time programmable non-volatile memory.

It’s easy to see why IP consumers would want to have assurance that the IP they are using in their designs is designed, test and supported with processes that focus on continuous improvement. To see more about how an ISO certified supplier operates, take a look at the Sidense website.

More articles by Tom Simon


IoT Security – Part 1 of 3: IoT Security Architecture on the Device and Communication Layers

IoT Security – Part 1 of 3: IoT Security Architecture on the Device and Communication Layers
by Padraig Scully on 12-01-2016 at 4:00 pm

The massive scale of recent DDoS attacks on DYN’s servers that brought down many popular online services in the US, gives us just a glimpse of what is possible when attackers are able to leverage up to 150,000 unsecure IoT devices as malicious endpoints.

To address the growing fear and uncertainty out there surrounding the IoT security architecture, our IoT security research practice teamed up with the IoT Security company Ardexato help companies implementing IoT double-check that their solutions are built secure.

Part 1 of this 3-part security-focused blog series presents anintroduction into the overall IoT security architecture and highlights six key principles as explained by George Cora, CEO of Ardexa.


Developing secure end-to-end IoT solutions involves multiple levels that fuse together important IoT security architecture features across four different layers: Device, Communications, Cloud, and Lifecycle Management.

A. Secure Device Layer
The device layer refers to the hardware level of the IoT solution i.e., the physical “thing” or product. ODMs and OEMs (who design and produce devices) are increasingly integrating more security features in both their hardware and software (that is running on the device) to enhance the level of security on the device layer.
Important IoT security architecture features:

  • Some manufacturers are introducing chip security in the form of TPMs (Trusted Platform Modules) that act as a root of trust by protecting sensitive information and credentials (i.e., not releasing encryption keys outside the chip).
  • Secure booting can be used to ensure only verified software will run on the device.
  • Even physical security protection (e.g., full metal shield covering all internal circuitry) can be employed to guard against tampering if an intruder gains physical access to the device.

While these “hard identities” or “physical protection barriers” may be valuable in specific situations, it is the proposed data movements and ability of the device to handle complex security tasks that will determine the level of risk. Edge processing and complex security functions within a device are important principles to get right from the start.

IoT Security Architecture Principles on the Device Layer:

1. Device “intelligence” is required for complex, security tasks

  • Many devices, appliances, tools, toys or gadgets available today have the ability to ‘talk’ to a service, cloud or server via Ethernet or wi-fi. But many of these ‘devices’ are powered by nothing more than a microprocessor. These devices are ill-equipped to handle the complexities of Internet connectivity, and should not be used for the front-line duty in IoT applications.
  • Effective and secure connectivity must be powered by a “smart” device able to handle security, encryption, authentication, timestamps, caching, proxies, firewalls, connection loss, etc. Devices must be robust and able to operate in the field with limited support.”

2. The security advantage of processing at the edge

  • Having smart devices is about giving your device the power to evolve, making it more powerful/useful/helpful over time. For example, machine learning algorithms can now enable these small devices to process video streams in ways which were not foreseeable (or computationally possible) a few years ago. Edge processing means that these smart devices can process data locally before it is sent to the cloud, eliminating the need to forward huge volumes of video to the cloud.
  • Can this be used for enhanced security? Absolutely. It means that sensitive information (usually in bulk) need not be sent to the cloud. Furthermore, it means processed data, packaged into discrete messages, sent securely to various entities is now possible. Thoughtful execution of the processing power at the device layer helps strengthen the overall network.

Insights from George Cora, CEO at Ardexa

B. Secure Communications Layer
The communication layer refers to the connectivity networks of the IoT solution i.e., mediums over which the data is securely transmitted/received. Whether sensitive data is in transit over the physical layer (e.g., WiFi, 802.15.4 or Ethernet), networking layer (e.g, IPv6, Modbus or OPC-UA), or application layer (e.g., MQTT, CoAP or web-sockets) unsecure communication channels can be susceptible to intrusions such as man-in-the-middle attacks.
Important IoT security architecture features:

  • Data-centric security solutions ensure data is safely encrypted while in transit (and at rest) so that even if intercepted, it is meaningless except to users (i.e., a person, device, system, or application) who have the right encryption key to unlock the code.
  • Firewalls and intrusion prevention systems, designed to examine specific traffic flows (e.g., non-IT protocols) terminating at the device, are also increasingly being used to detect unwanted intrusions and prevent malicious activities on the communication layer.

IoT Security Architecture Principles on the Communication Layer:

3. Initiate a connection to the cloud, and not in the reverse

  • The moment a firewall port is opened to a network, you literally and metaphorically open your network up to significant security risks. Opening a firewall port is only really required to allow someone or something to connect to a service. Yet, field devices are not likely to be supported to the same degree as hosted applications such as web/email or voice/video servers. They will not have an administrator patching, reconfiguring, testing and monitoring software that normally applies to a cloud service.
  • For this reason, it is usually a bad idea to allow a connection from the Internet to the device. The device must initiate the connection to the cloud. It must not allow incoming connections. A connection to the cloud can also facilitate a bi-directional channel, thereby allowing the IoT device to be remotely controlled. In most cases, this is required.
  • Closely related to this principle is the use of Virtual Private Networks (VPNs), to access an IoT device. However, VPNs can be just as dangerous as allowing incoming services, since they allow an individual, or a network, access to resources inside one’s own network. The scale of the security task has now grown significantly, and often beyond reasonable control. Again, VPNs have a role to play but in very specific circumstances.

4. The inherent security of a message

  • Communications to the IoT device (regardless of whether they are to or from the device) should be treated with care. Lightweight message-based protocols have a number of distinct advantages that make them a good choice for IoT devices including options for double encryption, queuing, filtering and even sharing with third parties.
  • With correct labeling, each message can be handled according to the appropriate security policy. For example, one may restrict access to messages that allow ‘remote control’ functions, or allow ‘file transfers’ in only one direction or (say) double encrypt all messages carrying client data to protect it when it traverses a message switch. It becomes possible, with such an infrastructure, to control message flow to the desired destination(s). Messaging, and its related access control and security benefits is a very, very powerful tool on the communication layer of the IoT.”

Insights from George Cora, CEO at Ardexa
To combat the inherent challenges of securing the IoT, sticking to these key principles at both the Device and Communications layer will help reduce future headaches, particularly in trying to compensate for poor underlying design fundamentals and inadequate IoT security architectures.
Stay tuned for Part 2 of our IoT security blog series in December where we take a closer look at Secure Cloud and Secure Lifecycle Management.

Find out more details about the 4 levels of IoT security architecture and how the overall IoT security market is shaping up in our upcoming IoT Security Market Report (to be released in the coming months) – contact us now to gain exclusive access.


Car Connectivity Lost

Car Connectivity Lost
by Roger C. Lanctot on 12-01-2016 at 12:00 pm

The frustration in the room was palpable yesterday at the annual Vehicle Connectivity Workshop gathering of the Telecommunications Industry Association (TIA). The prospect of dedicated short range communication (DSRC) technology achieving its long-sought mandate to connect cars and infrastructure hung tantalizingly over the crowd like mistletoe. Meanwhile speakers touted the merits of competing and complementary wireless connections – with an emphasis on 5G cellular.

Unspoken for much of the meeting, though, was the major disconnect between the wireless, intelligent transportation (ITS), information technology and automotive industries – to say nothing of disconnected insurance and regulatory interests. All of these parties were well represented at the gathering but, as always, they talked past one another and a chance to achieve true alignment was missed once again.

I’ll state the underlying conflict in simple terms. Wireless carriers don’t understand car companies and car companies can’t stand wireless carriers.

It comes down to motivations. Everyone is motivated by profit. Car companies are primarily interested in extracting revenue from wireless connections in cars. Wireless carriers are primarily interested in extracting revenue from car companies and their customers. These objectives are in conflict, though they do not have to be.

Meanwhile, the ITS community is interested in using wireless technology to improve vehicle throughput at toll plazas and high-occupancy-vehicle lanes. Regulators and insurance companies are interested in reducing rising highway fatality levels. Startups and Silicon Valley types are interested in disruption.
The prospect of enabling connections between cars, regardless of the technology to be used, means car companies will have to cooperate with one another on application development for the first time. It is not at all clear how that will work with DSRC technology. Using cellular technology will introduce wireless carriers as a unifying force – a role carriers will increasingly play as the world of interconnected things continues to emerge.

This new post-IoT world will also elevate the role of IT companies – Oracle, IBM, HP, Microsoft and Amazon. Not all of these voices were represented at the TIA gathering.

I don’t hold TIA responsible for the failure to calm the waters and part the clouds hanging over vehicle connectivity. I blame the car makers.

The onset of 5G connectivity in cars and the reality of LTE connectivity already in cars has shifted connectivity responsibility into a cross carlines responsibility. Some car companies treat connectivity as a crash response priority, others treat it as a source of monetize-able Wi-Fi connections, still others want to use vehicle connectivity for promotional and marketing opportunities.

At the forefront of the conversation yesterday was the prospect of 5G connections enabling enhanced security, over-the-air software updates and automated driving. All of these use cases will transform the industry and they suggest that the wireless connection in the car will soon be touching all departments from powertrain to safety to infotainment, marketing, customer relationship management, finance and dealer relations.

But even sorting all of that out leaves vehicle-to-infrastructure and vehicle-to-pedestrian connections unaddressed. The companies building the roads and bridges are at a loss in trying to gain traction with the correct auto industry execs. This holds true for smart city initiatives and mobility as a service strategies. No one knows who to talk to and there does not appear to be a single executive at any car maker with comprehensive responsibility for defining the connectivity vision.

European car makers have made the greatest strides here by nominating executives with such titles as “chief digitalization officer” or the like. Talk with one of these executives and he or she will run down a Trump-sized list of teams and initiatives over which they are responsible. It’s too much for a single man or woman – and profit motives still sadly take precedent over safety.

It all comes down to infrastructure. I participated in the event on a panel with Chrisopher Bluemle of Crown Castle. Chris’ selection to participate in the event was a clever one not only because his company is responsible for tower and fiber optic infrastructure enabling the connections we are so keen to create, but also because his background is finance. Unfortunately, the financing of the backbone of vehicle connectivity is likely to come from all of our wireless bills – which will probably be less than if it came out of our taxes.

There was no consensus in the room regarding DSRC vs. 5G yesterday. This debate will rage on. But the bigger question is whether wireless carriers, car companies, ITS infrastructure companies and IT providers can find sufficient common ground to craft an effective strategy for guiding automated vehicle development.

This is not about taking sides. It’s about assigning responsibility appropriately with the goal of saving lives. The next move is up to the car makers. This was the one constituency insufficiently represented in the presentations and panel discussions. The one dominant auto-maker voice came from Dr. Gary Smyth, executive director Global R&D Laboratories of General Motors.

Smyth is a fierce but friendly advocate of DSRC. He firmly planted the DSRC flag as the focal point of the TIA gathering. The event concluded with word of President-elect Trump’s appointment of a new Department of Transportation Secretary, Elaine Chao, but no word regarding DSRC rule making.

Rule making and regulators won’t solve the various connected vehicle disconnections. Only inter-industry and intra-industry cooperation can solve this problem. Perhaps the best news emerging from the TIA event was the creation of the 5GAA (5G Automotive Association) which is bringing together car makers, carriers, and infrastructure partners. AT&T, Verizon, Ford, Denso and others are expected to soon join Audi, Daimler, BMW, Qualcomm, Ericsson, Huawei, and Vodafone already involved. Perhaps the clouds will yet part for the world of connected cars. Watch this space.


The Failure of IoT Platforms

The Failure of IoT Platforms
by Glen Allmendinger on 12-01-2016 at 7:00 am

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Creative Evolution and the Post Platform Era
When telephones first came into existence, all calls were routed through switchboards and had to be connected by a live operator. It was long ago forecast that if telephone traffic continued to grow in this way, soon everybody in the world would have to be a switchboard operator. Of course that did not happen because automation was built into the systems to handle common tasks like connecting calls.

We are quickly approaching analogous circumstances in the IoT arena with the proliferation of connected devices. The tools we are working with today to make products “smart” were not designed to handle the diversity of devices, the scope of interactions and the massive volume of data-points generated from devices. Each new device requires too much customization and maintenance just to perform the same basic tasks. These challenges are diluting the ability of organizations to efficiently and effectively manage development.

Today, platforms for the Internet of Things are still a kludgy collection of yesterday’s technology and architectures that do not address the most basic development challenges. Even though many companies are telling fantastic IoT marketing stories about what their solutions can do, you wouldn’t know it from today’s fragmented collection of incomplete platforms, narrow point-solutions, and software incompatibility.


We need better software to empower users and developers to exploit the vast potential of the Internet of Things.

Download Our Storyboard on IoT Frameworks

We’re Having a Crisis of Perception About “Future Computing”
In times of radical change, crises of perception are often the cause of significant failures, particularly in large established companies. Such failures result from the inability to see emergent discontinuities. We believe this is the case with most large developers and suppliers of technology attempting to address the emerging Internet of Things opportunity. Many players’ assumptions about future architecture for Smart Systems are being shaped by the past and are being extrapolated into the future in a linear fashion. Most of the large established IT equipment, software and network players appear to be stuck in this tyranny of replication.

Today the world of smart communicating devices is mostly organized in hierarchies with smart user interface devices at the top and the dumb devices [often analog or serial sensors and actuators] at the bottom. Within this structure, there are typically various types of “middle box” supervisory and gateway devices forming a point of connectivity and control for the sensors and actuators as well as the infrastructure for the network. From our perspective, this description of today’s IoT systems architecture looks very familiar and is largely organized like client-server based computer systems….. no surprise given they were designed in the 1990′s.

As the Internet of Things opportunity matures, the sensor and actuator devices will all become smart themselves and the connectivity between them (devices, for the most part, that have never been connected) will become more intelligent and the interactions more complex. As the number of smart devices grow, the existing client-server hierarchy and the related “middle boxes” acting as hubs, gateways, controllers and interfaces will quickly start to blur. In this future-state, the need for any kind of traditional client-server architecture will become superfluous. In a future Smart Systems world, the days of hierarchical models are numbered.

We can now begin to imagine an application environment where there will be widely diverse operational technology (OT) computing devices running applications dispersed across sensors, actuators and other intelligent devices sharing and leveraging the compute power of a whole ‘herd’ – a smart building application, for example, where the processor in an occupancy sensor is used to turn the lights on, change the heating or cooling profile or alert security.

In this evolving architecture, the network essentially flattens until the end-point devices are merely peers and a variety of applications reside on one or more [OT] computing devices. In a smart systems application designed to capture, log and analyze large volumes of data from sensors, such as we are describing here, peer computing devices will carry out the process of taking raw data and distilling it into information “locally.” Local processing is required to reduce the otherwise untenable Internet traffic challenges that arise from connecting billions of devices.

This is the move we’ve been waiting for…….. to a truly distributed architecture because today’s systems will not be able to scale and interact effectively where there are billions of nodes involved. The notion that all these “things” and devices will produce streaming data that has to be processed in some cloud will simply not work. It makes more sense structurally and economically to execute these interactions in a more distributed architecture near the sensors and actuators where the application-context prevails.
Dispersed computing devices will become unified application platforms from which to provide services to devices and users where the applications run, where the data is turned into information, where storage takes place, and where the browsing of information ultimately takes place too – not in some server farm in a cloud data center. Even the mobile handsets we admire so much today are but a tiny class of user interface and communications devices in an Internet of Things world where there will be 100 times more “things” than humans.

From our view the movement towards peer-to-peer, and the view that many people hold that this is somehow novel, is ironic given that the Internet was originally designed for peer-to-peer interactions. We seem to be heading “back to the future.”

Today’s IoT Platforms Don’t Liberate Data; They Trap It
In the course of the last two decades, the world has become so dependent upon the existing ways computing is organized that most people, inside IT and out, cannot bring themselves to think about it with any critical detachment. Even in sophisticated discussions, today’s key enabling information technologies are usually viewed as utterly inevitable and unquestionable.

The client-server model underlying today’s computing systems greatly compounds the problem. Regardless of data-structure, information in today’s computing systems is machine-centric because its life is tied to the life of a physical machine and can easily become extinct. With today’s IoT platforms information is not free (and that’s free as in “freedom,” not free as in “free of charge”). In fact, thanks to today’s platforms and information architectures, it’s not free to easily merge with other information and enable any kind of systemic intelligence.

All of this adds up to a huge collection of information-islands whether on your servers, your service provider’s servers or anywhere else. Assuming the islands remain in existence reliably, they are still fundamentally incapable of truly interoperating with other information-islands. This is the issue with all of the so-called IoT platforms that have flooded the market – they are really “data traps” and information islands. We can create bridges between them, but islands they remain, because that’s what they were designed to be.

What would truly liberated information be like? It might help to think of the atoms and molecules of the physical world. They have distinct identities, of course, but they are also capable of bonding with other atoms and molecules to create entirely different kinds of matter. Often this bonding requires special circumstances, such as extreme heat or pressure, but not always. In the world of information technology, such bonding is not all that easy.

Smart Systems requires we fundamentally change this paradigm, treating data from things, people, systems and the physical world as “neutral” representations. In other words, treating diverse data types equally. But even this makes too many assumptions about what the Smart Systems phenomenon will be. Encoded information in physical objects is also smart computing—even without intrinsic computing ability, or, for that matter, without being electronic at all. Seen in this way, a printed bar code, a DVD, a tag, a disc, a house key, or even the pages of a book can have the status of an “information device” on a network.

Today’s holdover client server architectures are just making matters worse. With each additional layer of engineering and administration, computing systems come closer and closer to resembling a fantastically jury-rigged Rube Goldberg contraption.

The reason for all of this is simple. Today’s computing systems were not really designed for a world driven by pervasive information flow and are falling far short of enabling adaptable real-time intelligence.

Creative Evolution Will Force a “Post-Platform” World
Machine learning, artificial intelligence and the Internet of Things are all in some way trying to break from today’s computing paradigms to enable intelligent real-world [physical] systems. As these devices and systems become more and more intelligent, the data they produce will become like neurons of the brain, or ants in an anthill, or human beings in a society, as well as information devices connected to each other. The many “nodes” of a network may not be very “smart” in themselves, but if they are networked in a way that allows them to connect effortlessly and interoperate seamlessly, they begin to give rise to complex, system-wide behavior that usually goes by the name “emergence.” That is, an entirely new order of intelligence “emerges” from the system as a whole—an intelligence that could not have been predicted by looking at any of the nodes individually. There’s a distinct magic to emergence, but it happens only if the network’s nodes are free to share information and processing power.
Today’s platforms for Smart Systems and the IoT should be taking on the toughest challenges of interoperability, information architecture and user complexity. But they’re not.

We need to creatively evolve to an entirely new approach that avoids the confinements and limitations of the today’s differing platforms. We need to quickly move to a “post platform” world where there is a truly open data and information architecture that can easily integrate diverse machines, data, information systems and people – a world where smarter systems will smoothly interact to create systemic intelligence – a world where there are no artificial barriers between different types of information.

In our years of experience, we have all too often seen the unfortunate scenarios that managers create when uncertainty and complexity force them to rely on selective attention. Unfortunately, when this happens, selective attention naturally gravitates toward what’s readily available: past experience, existing tools and uncertain assumptions. Today’s IT and telco infrastructure players are doing just this. By ignoring important trends simply because it’s difficult to perceive an alternative future, these managers are certainly leaving the door open for competition that will lead to their eventual obsolescence…which will make for a very interesting world to live in…

For more information on how to overcome these obstacles in the market email us


OpenCL hits FPGA-based prototyping modules

OpenCL hits FPGA-based prototyping modules
by Don Dingee on 11-30-2016 at 4:00 pm

OpenCL brings algorithm development into a unified programming model regardless of the core, working across CPUs, GPUs, DSPs, and even FPGAs. Intel has been pushing OpenCL programming for some time, particularly at the high end with “Knights Landing” processors. Where other vendors are focused on straight-up C high-level synthesis for FPGAs, Intel is taking Altera technology deeper into OpenCL.

Using OpenCL, a developer can write an algorithm once, emulate it on a PC, then choose what hardware to run it on – or partition it across several different types of hardware depending on cost and packaging. Intel’s FPGA SDK for OpenCL helps abstract out FPGA complexity for hardware acceleration. Their compiler can perform over 300 optimizations, then synthesize the FPGA in a single step.

Several different hosts are supported, including ARM Cortex-A9 cores typical of SoCs, IBM POWER Series processors, and X86 CPUs. The solution can be scaled across multiple FPGAs, which makes it ideal for the FPGA-based prototyping scenario. Instead of taking overt partitioning steps and spreading out RTL across several FPGAs, OpenCL code distributes seamlessly across FPGA devices. This is a huge advantage for HPC teams who want to concentrate on software, not hardware, and especially not the nuances of FPGA programming.


Screenshot from video: https://www.altera.com/content/dam/altera-www/global/en_US/video/opencl-overview-tutorial.mp4

In fact, OpenCL could be one of the key differentiators between the Intel/Altera combination and the ARM/Xilinx ecosystem. There are OpenCL ports on lots of platforms since it is an open standard, but Intel has gone all in on optimization for OpenCL across the board including its FPGA offering. Combining the benefits of an OpenCL development flow with the power of an Altera Arria 10 FPGA brings a bunch of algorithm acceleration possibilities.

S2C has solved the problem of how to get many FPGAs interconnected in a single prototyping platform. With their new Arria 10 Prodigy FPGA Prototyping Logic Module, users can have anywhere from a single Arria 10 1150GX FPGA to a scaled-up system with 16 FPGAs in the Cloud Cube chassis. As the name implies, a single Arria 10 logic module has 1150K logic elements along with a full suite of programmable I/O including 48 transceivers running at up to 16Gbps, and 576 high performance I/Os. It’s an incredible leap, not only for those interested in working in the Intel/Altera environment, but for those working on OpenCL.

You can read more about the Intel FPGA SDK for OpenCL, and download a copy, here:
Intel FPGA SDK for OpenCL

For more information on the S2C Arria 10 Prodigy FPGA Prototyping Logic Module, here’s the full S2C press release:

S2C Expands Its FPGA Prototyping Library with Arria 10 Solution and Delivers Its Powerful Technology to the High Performance Computing Market

The thing about FPGA-based prototyping is it is becoming less about the FPGA and more about the software running on the platform. While the entire S2C prototyping portfolio including expansion daughter cards, configuration, and debug capability comes to bear, the real news here is how OpenCL speeds up the software development process. The shape of HPC is changing from big, expensive iron to reconfigurable, accelerated computing with FPGAs underneath the hood.