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Webinar: ARM Security Solution for IoT

Webinar: ARM Security Solution for IoT
by Daniel Nenni on 12-08-2016 at 4:00 pm

Yossi Weisblum will be presenting ARM’s IoT security solution during the Open Silicon webinar that I am moderating next week. Yossi manages product marketing for ARM’s CryptoCell subsystem. He has an extensive background in product marketing across several platforms, including connectivity, wireless, multimedia and mobile. Prior to joining ARM in 2016, Yossi worked at Intel for over ten years where he was instrumental in the development of the company’s wireless connectivity solutions.


Joining us is Kalpesh Sanghvi, SoC and Solutions Manager for Open Silicon. Kalpesh has over a decade of professional experience in the semiconductor and embedded industry. He has in-depth knowledge of software development and bring-up for SoC/ASIC designs, and domain expertise in IoT, storage solutions, security solutions, networking and multimedia reference designs. Kalpesh is also experienced in ASIC design flows, pre-silicon and post-silicon bring-up and validation as well as prototyping solutions.

We started tracking security related content at the end of 2015 and based on the SemiWiki analytics I can tell you for a fact that EVERYBODY is concerned about security, especially IoT security.

REGISTER HERE

This joint Open-Silicon and ARM® webinar, moderated by Daniel Nenni, CEO and founder of SemiWiki, will address the security issues associated with IoT edge devices and how to make them secure with custom SoCs. The key focus areas for security in IoT edge devices are secure boot, data security, tamper proofing and device authentication. Efficient security features are implemented with a combination of hardware and software. Features like root of trust with secure boot and tamper proofing with physical security are more efficient when implemented in hardware and IP by a turnkey ASIC vendor. Features like data security and device authentication are more efficiently implemented in software by OEMs leveraging purpose-built hardware.

The advantages of hardware-implemented security features with custom SoCs include a significant improvement in acceleration time (ex: boot-up time), mitigation of potential tampering, and enabling a purpose-built device from a system point of view. The ARM TrustZone® CryptoCell family of security IPs provides hardware-based platform security for cost efficient implementation in custom SoCs, as well as a fast path to market. Open-Silicon’s custom SoC IoT platform, based on ARM’s Cortex-M and TrustZone® CryptoCell, enables OEMs to develop secure IoT edge devices with lower risk and shorter development time. This platform supports root of trust with secure boot and a secure over-the-air firmware/application upgrade.

We just did the practice run of the presentations and it will be worth your time if you too are involved with or concerned about IoT security, absolutely. The webinar is on Tue, Dec 13, 2016 from 8:00 AM to 9:00 AM PST. After a brief introduction by me, Yossi and Kalpesh will present leaving plenty of time for Q&A. And to top it off, attend the webinar – ask a question – and if your question is addressed during the webinar I will make sure you get a signed copy of “Mobile Unleashed: The origin and evolution of ARM processors in our devices”. Sound reasonable?

REGISTER HERE


ARM and Mentor talk about Real Time Virtualization, Webinar

ARM and Mentor talk about Real Time Virtualization, Webinar
by Daniel Payne on 12-08-2016 at 12:00 pm

Processor cores come in a wide variety of speeds, performance and capabilities, so it may take you some time to find the proper processor for your system. Let’s say that you are designing a product for the industrial, automotive, military or medical markets that has an inherent requirement for safety, security and reliability – which ARM processor would fit the task? The A-series processors are popular and well-known, however the new Cortex-R52 is specifically designed for safety, security and reliability applications.

You will want to learn more about the Cortex-R52 at a webinar next week that is hosted by experts from both ARM and Mentor Graphics. A few highlights about the Cortex-R52 to whet your appetite:

  • Deterministic microarchitecture
  • Deterministic memory
  • Extensibility
  • Fast interrupt entry
  • Fast context switching
  • Scalability from 1 to 4 core


Expect to learn a few ideas at this webinar:

  • Advantages of using Cortex-R processors
  • Using devices and software with isolated hypervisors to mage safety and security events
  • Cortex-R52 used in ADAS applications

Register for the webinar today, there are two timezones available:

Jon Taylor from ARM and Felix Baum from Mentor are the two presenters, and you’ll have time to type in any questions during the webinar for answering at the end. I look forward to attending the webinar and sharing my thoughts in the next blog.

Jon Taylor
Jon Taylor is a Product Specialist in the CPU product marketing team at ARM with responsibility for the Cortex-R family of processors. His background includes real-time software development for multi-core microcontrollers and safety certified RTOS development.

Felix Baum
Felix Baum is working in the Product Management team of the Mentor Graphics Embedded Software Division, overseeing the virtualization and Multi-OS and Multi-Core technologies. Felix has spent nearly 20 years in the embedded industry, both as an embedded developer and as a manager. During the last few years he led product marketing and product management efforts for various real-time operating system technologies and silicon architectures. Before that, working in business development, he managed the technical needs of strategic alliance partners around the globe, helping them address the challenges of integrating and promoting joint solutions for mutual customers. Prior to that as a field applications engineer in the greater Los Angeles area, he consulted with customers on the development of highly optimized devices for a broad range of industries, including Aerospace, Networking, Industrial, Medical, Automotive and Consumer. Felix started his career at NASA’s Jet Propulsion Laboratory at the California Institute of Technology, designing flight software for various spacecraft and managing a launch campaign for the GRACE mission. Felix holds a master’s degree in Computer Science from the California State University at Northridge and a Master of Business Administration from the University of California at Los Angeles.


Design for Ultra-Low Power LTE: CEVA Webinar

Design for Ultra-Low Power LTE: CEVA Webinar
by Bernard Murphy on 12-08-2016 at 7:00 am

You might have thought that ultra-low power communication for the IoT was limited to standards like BT5 and 802.15.4 (eg in ZigBee and Thread) which depend on gateways to cellular networks and limit reach, especially deep inside buildings. But now there’s a new standard for ultra-low power and ultra-low cost based on LTE, known as Cat-NB1. If you want to understand more about communications options for your IoT devices, you should attend this Webinar.

REGISTER HERE

Summary

The 3GPP recently completed the standardization of a new LTE-based narrowband technology to support the emerging needs of cellular-IOT devices. Known as Cat-NB1 (formerly NB-IoT), this new low data rate category will enable the development of ultra-low power, ultra-low cost solutions that can leverage the existing LTE infrastructure for a new wave of connected devices. However, in order to efficiently leverage the Cat-NB1 standard, a new approach to cellular SoC design is required, where low data rate transfer in very large time intervals is the goal. As such, solution designers might step out of their “comfort zone” and reevaluate existing modem solutions.

Join CEVA experts to hear about:

  • A Cellular IoT market overview
  • Introduction to Cat-NB1
  • Cat-NB1 design considerations and SoC architecture overview
  • CEVA’s solution compared to traditional designs

Target Audience
Communication and system engineers targeting cellular IoT segment as well as similar Low Power Wide Area Network (LPWA) standards; IoT solution designers interested in low-end devices with low throughput requirement

REGISTER HERE


Emmanuel Gresset – Business Development Director, CEVA Wireless BU


Tal Shalev – Senior Communication System Architect, CEVA Wireless BU

Naturally, CEVA already has solutions in this space. As the leading licensor of signal processing IPs for smarter, connected devices, CEVA together with NextG-Com Limited (NextG-Com) has introduced two pre-integrated narrowband LTE solutions designed to simplify the development of Cat-M1 and Cat-NB1 (NB-IoT) modems for cost-sensitive Internet of Things (IoT) applications.

The solutions incorporate the recently introduced CEVA-X1 single-core IoT processor together with NextG-Com’s ALPSLite-M Cat-M1 or ALPSLite-NB Cat-NB1 protocol stacks, in a highly compact and power-efficient manner. Addressing the cost-sensitive nature of cellular IoT devices, the CEVA-X1 is capable of handling the full DSP and CPU processing loads for these modems, eliminating the requirement for a CPU controller in the system. Furthermore, the solutions have been carefully optimized to ensure smallest memory footprint, minimizing the requirements for costly embedded flash and static RAM. Ensuring maximum power efficiency for long life cellular IoT applications such as asset trackers or smart meters, the CEVA-X1 incorporates dedicated NB-IoT instructions, allowing it to operate at a clock speed of less than 100MHz for a complete Cat-NB1 solution.

“Cellular IoT offers huge potential in terms of the breadth of applications it will enable and the massive global scale on which these devices can be deployed,” said Denis Bidinost, Chief Executive Officer of NextG-Com. “Our partnership with CEVA brings together their dedicated IoT processor with fully-optimized implementations of our Cat-M1 and Cat-NB1 protocol stacks to significantly simplify the integration of narrowband LTE connectivity into cost-sensitive, power-optimized IoT product designs.”

CEVA is the leading licensor of signal processing IP for a smarter, connected world. We partner with semiconductor companies and OEMs worldwide to create power-efficient, intelligent and connected devices for a range of end markets, including mobile, consumer, automotive, industrial and IoT. Our ultra-low-power IPs for vision, audio, communications and connectivity include comprehensive DSP-based platforms for LTE/LTE-A/5G baseband processing in handsets, infrastructure and machine-to-machine devices, computer vision and computational photography for any camera-enabled device, audio/voice/speech and ultra-low power always-on/sensing applications for multiple IoT markets. For connectivity, we offer the industry’s most widely adopted IPs for Bluetooth (Smart and Smart Ready),Wi-Fi (802.11 b/g/n/ac up to 4×4) and serial storage (SATA and SAS).


Mentor’s Battle of the Photonic Bulge

Mentor’s Battle of the Photonic Bulge
by Mitch Heins on 12-07-2016 at 4:00 pm

A few weeks back I wrote an article mentioning that Mentor Graphics has been quietly working on solutions for photonic integrated circuits (PICs) for some time now, while one of their competitors has recently established a photonics beachhead. One of the most common challenges for PIC designs is their curvilinear nature, thus the reference to the now infamous battle of the bulge. To continue the parlance, Mentor has, in fact, been attacking PIC design on multiple battle fronts. Don Dingee wrote a nice article about one of those efforts in which Mentor’s Tanner team has been working with Luceda to make photonic design more straightforward (see link below).

I also wrote an article highlighting some of Mentor’s efforts in the area of Electro-Optical Design using their Pyxis and Calibre tool sets. The one point that hasn’t really been made in these articles, though, is that Mentor’s Calibre design rule checking (DRC) and layout-vs-schematic (LVS) technologies hold a strategic articulation point for any design going into a silicon-based foundry. Calibre is the de facto sign-off DRC & LVS tool for all production silicon foundries, and as silicon photonics starts to take hold, it will be essential that those foundries have good photonic DRC & LVS rule decks in place. Turns out this is a bit trickier than one might imagine. The good news is that Mentor has been working on this now for more than five years, and they have built up a wealth of experience.

As mentioned, the challenge when doing DRC for PICs is the curvilinear data, the aforementioned bulge. These curves get digitized into polygons with thousands of points that represent the curves in a piece-wise linear fashion, each of which must be snapped onto a manufacturing grid. The result is that a normal DRC deck will report thousands of false errors from these highly discretized shapes.

The example picture on the left from one of Mentor’s silicon photonics white papers shows concentric circles very typical of a photonics design style used to make spiral delay lines. Note the thousands of colorations along the design shapes denoting error markers from DRC using a normal DRC deck. The picture on the right is the same set of concentric circles, but now they are DRC clean. In this case, the Calibre team used their experience to modify the DRC deck to redefine the rules for width and spacing, given the knowledge that these shapes were indeed digitized curves with a given radius of curvature and spacing.

Two things were needed to make this happen. The first is that information needed to be sent to Calibre tools so that they knew to treat these shapes differently. This was done by a flow that Mentor put together with PhoeniX Software, which is used in Mentor’s Pyxis flow to generate these types of shapes. The second thing that needed to happen was to have a DRC capability that could use the information forwarded from PhoeniX to perform a type of check that was amenable to the identified shapes. Mentor put their equation-based DRC capabilities to work to solve this problem.

A second challenge for PICs is how to best perform LVS. The good news is that PIC designers are now using a PDK approach to building their designs. This means that many of the tricky LVS challenge can be subsumed within the PDK components. This includes things like logical connections between waveguides that transfer data through evanescent coupling where the waveguides don’t actually touch. These connections become components with pins, as opposed to the LVS tool having to discern a coupler vs. two waveguides simply passing each other. This makes the checking of basic connections easier, especially if one has a schematic with which to compare.
Another photonic LVS problem is checking schematic parameters against the layout. In electronic ICs, this would be comparable to measuring transistor widths and lengths in the layout and then comparing them to the W and L parameters in the schematics. With PICs this is much harder, as the parameters are not simple scalar values, but instead mathematical relationships. This has been a research subject of groups like PLAT4M (of which Mentor has been a member), and Mentor has come up with some unique and powerful solutions to these problems.

One solution, as already mentioned, uses forward-annotated data where Calibre compares the layout to a rendering based on the forward-annotated equations. This can be done using a combination of Calibre’s Design for Manufacturing capabilities, including its YieldServer API and DFM database, and geometric operations in the Calibre DESIGNrev finishing tool. Additionally, Mentor has come up with a nifty way to do the equivalent of a geometric checksum on PDK components based on parameters as specified in the schematic. This checksum can be computed for the actual layout shapes found and compared against the logical checksums from the schematics, flagging layouts that don’t match their schematic counterparts.

Rounding out Mentor’s photonic capabilities is the ability to use their Calibre LFD package to simulate a foundry’s lithography and etch processes to view how the actual manufactured layout will look. In this case, the designer can not only do DRC and LVS on these simulated shapes, but they can also generate data that can be back-annotated for re-simulation of both the components and the circuit as a whole. Through its collaboration with Lumerical Solutions, Mentor can back-annotate all measured shapes (lengths, widths, radius of curvatures, etc.) of the simulated manufactured design and send them to both Lumerical’s compact model generation process (to create updated S-matrix component models) and to Lumerical’s INTERCONNECT circuit simulator (for full circuit level simulations).

In cases where the design is known to be going into high volume production runs, these types of simulations can be done across the expected manufacturing process window to identify design areas that may be susceptible to yield fallout.

So, while the competition may have recently secured a photonic beachhead, Mentor Graphics has already pushed well inland and is driving forward on multiple photonic battlefronts, including the strategic articulation point between design and manufacturing.

See also: Electrical-Optical Design-A Bridge to Terabitsia and Making photonic design more straightforward


Qualcomm Brings Us One Step Closer To Gigabit LTE Speed Products

Qualcomm Brings Us One Step Closer To Gigabit LTE Speed Products
by Patrick Moorhead on 12-07-2016 at 12:00 pm

Qualcomm announced at their 4G/5G Summit in Hong Kong specific products their 1 Gigabit Snapdragon X16 LTE modem will ship inside of. In February, the company announced, as we wrote in Forbes last Febraury here, that they had achieved speeds of up to 1 Gbps using this newly-announced Snapdragon X16 modem. Many questioned when we would see real products using a modem of such capabilities, but the doubters now have an answer.

At their 4G/5G Global Summit in Hong Kong which Moor Insights & Strategy associate analyst Anshel Sag is attending, Qualcomm announced two major product developments using the Gigabit-class LTE modem known as the Snapdragon X16 LTE modem. Both announcements involve actual product announcements that utilize the X16 LTE modem and bring us into the “LTE Advanced Pro” era.

1Gbps Netgear hotspot on the Telstra network

Telstra, Netgear, Ericsson, Qualcomm deliver the first 1Gbps hotspot and service (Image: Qualcomm)

The first announcement involves a partnership between Telstra, Netgear, Ericsson and Qualcomm. The establishment of this partnership is a sign of how real this upcoming product is and the heavy hitters behind it. The device being brought to market by Netgear using Telstra’s network, one of the leading LTE networks in the world, is a Wi-Fi hotspot of sorts. However, this hotspot will be supercharged with a maximum theoretical speed of 979 Mbps thanks to the combination of support for 3x CA (carrier aggregation), 256-QAM modulation and 4×4 MIMO antennas. This makes the Netgear MR1100 (Mobile Router) essentially a wireless fiber link, wherever you go. Telstra is saying they will ship the entire solution in the next few months.

Having essentially unlimited bandwidth on-demand is quite the empowering technology that enables use cases that simply weren’t possible before. In fact, Gigabit LTE like that from the X16 is very likely going to be the way that many companies first test out their 5G use cases. One example that just keeps coming up is the idea of 360-degree video for both smartphone and VR consumption. The reality is that you need a pretty high bandwidth and robust stream to enable a high enough quality stream to make 360 video worthwhile outside of a Wi-Fi network. Anshel Sag has tried watching streamed 360-degree video content and its pretty abhorrent quality in many cases due to bandwidth limitations. There are plenty of other applications that are going to be possible thanks to gigabit-class modems, by removing bandwidth limitations we may see a new class of applications arise like we did as speeds increased including instant apps. The reality is that we probably won’t know what they are going to be until they reach smartphones which leads us into Qualcomm’s next announcement.

1Gbps in a smartphone soon

Qualcomm announced 1Gbps LTE capabilities will be in its next 800-class SoC (Credit: Qualcomm)

The second major 4G announcement that Qualcomm made today at their 4G/5G summit involves Qualcomm integrating the same discrete gigabit-class X16 modem into the next generation 800-tier Snapdragon processors. While Qualcomm isn’t saying what processor it is exactly, we are left to assume that it will be included with the Snapdragon “830” or whatever the successor to the 820 is called. This means that Qualcomm has once again upped the modem game against their competitors and laid down the gauntlet while also maintaining their coveted modem leadership.

1Gbps wireless is real and lays 5G foundation

The integration of the gigabit-class Snapdragon X16 into mobile routers and smartphones marks the next phase of LTE’s evolutions and the next generation of LTE. With the ability to reach near 1 Gbit/s speeds on a mobile modem over LTE, we are starting to see what I believe to be the foundation for 5G using a robust and nearly ubiquitous technology in LTE Advanced Pro. As Anshel wrote last week, there’s no mistake that 5G is coming very soon, but as the operators have indicated, 4G is going to play a huge role in the bring up of 5G, possibly even more than 3G did with 4G LTE. We can clearly see that Qualcomm’s X16 Modem is more than just a chip, but now a technology enabling a new phase of mobile computing. With these kinds of speeds, I wonder whether any of the operators will break ranks and market their LTE Advanced Pro solutions as ‘5G’ like we saw with ‘4G’. If you want more info here are links to Qualcomm’s press release and a video:


Dark data to fuel warp speed growth for #IoT

Dark data to fuel warp speed growth for #IoT
by Diya Soubra on 12-07-2016 at 7:00 am

In my world of semiconductors, dark silicon refers to transistors that are present in the chip but that can not be turned on due to thermal constraints. A valid resource that is available but not used. In the case of #IoT we have a lot of data already out there that I would label as dark data, it exists but no one outside the network owner has access to it. Valid data that is not available, hence not used. Dark data is growing on daily basis as system integrators deploy vertical networks of #IoT nodes and collect information.


In my continued search for the inflection point for #IoT, I ran into this interesting bit of information this weekend. The city of Boston is applying #IoT principles and best of all is giving open access to the data. The city has even partnered with other providers of data to improve road conditions. This reminded me that in one of my previous rants, I complained about the lack of a broker that would facilitate connecting the data from #IoT nodes to big data consumers. What if this was too big of a step to take? What if instead, a dark data exchange could be the smaller step that might be easier to take?

It would require a lot less in terms of technology and transactions to exchange data as opposed to giving access to networks of #IoT nodes. Someone who is in the business of deploying #IoT nodes would now collect the data and place it in the exchange for other people to purchase. We still need a broker to make the transaction but we no longer need to setup access to the individual nodes. This would be an alternative method to capture revenue for people in the #IoT node deployment for data capture business. Without that revenue potential, growth in the number of #IoT nodes will remain limited to those deployed by system integrators. Without a dark data exchange the growth in #IoT will remain limited to vertical deployments.

In #IoT, information is the fuel for analytics engines. People are willing to pay a lot for that fuel since the output from the analytics engine is worth 10x more than the input. A global dark data exchange will for sure make many people happy on all sides and would boost the number of companies that want to deploy #IoT nodes. Only the potential of revenue from deploying #IoT nodes will drive deployment and only the subsequent horizontal mashup applications would drive #IoT into exponential growth. No revenue potential, no data. No exchange, no mashups.

Do you know of a dark data exchange already in operation today?


Hack This? Making Software a Moving Target

Hack This? Making Software a Moving Target
by Bernard Murphy on 12-06-2016 at 4:00 pm

It sometimes seems that the black hats are always one step ahead of the white hats in the never-ending security game. One of the especially invidious ways hackers have found to evade detection is through mutation – changing the code in a virus on each copy, defeating classical signature detection methods and potentially requiring new signatures to be built and redistributed for each mutation.

The seriousness of this problem may be compounded by the growing lack of diversity in systems in the IoT at large – in industrial, home, medical and many other applications. ARM through its many customers has made this revolution possible but at the same time present to the hacking world an attractive and focused target of incredibly high value. Find a way to hack into the core of one system and you can potentially attack many systems with the same exploit. I’m sure ARM is very careful in analyzing and removing as many bugs as possible in their core software, but software by its nature is never perfect. Bugs will be found, especially since hackers can experiment at their leisure with their own ARM-based systems.

But there’s way to turn the tables on hackers by reintroducing diversity into systems, in fact even into a single system, so that exploits are always trying to aim at moving targets. The method started with a technique called address-space layout randomization (ASLR) introduced early in the millennium. In conventional computing the memory map of a program has fairly predictable structure. The stack starts in a certain well defined place, as does the heap. The easy “discoverability” of the stack is what enables so many basic hacks; you can easily change return routine return locations through tricks like buffer overflows. Less well-known but equally damaging exploits are known for attacking the heap or even the code.

ASLR in its early incarnation aimed to defeat hacks by randomizing the address map on program startup. In principle it would be much harder for exploits to discover key information because they wouldn’t know where to look. Sadly, as is eventually the case for all defenses, hackers found a way around ASLR by exploiting “memory disclosure bugs”, cases where applications may at least temporarily reveal information from which address map offsets can be reconstructed or code snippets can be extracted or overwritten.

Problems associated with this class of attack are very real. The Linux kernel has known memory discovery vulnerabilities. Some suggested fixes have included execute-only memory where it is not possible to overwrite code, but this becomes very challenging in the presence of Just-In-Time (JIT) programming where code and data can easily intermingle. Since JIT is becoming increasingly common – in Java and in Javascript (used by most browsers) – potential attacks have already been exposed.

But if viruses can constantly mutate, why not the address map also? A team at Columbia have created just such a defense which they call Shuffler. Shuffler randomizes code locations every tens of milliseconds (including for itself), effectively creating a deadline for an attacker – if they can’t figure out and exploit a disclosure in that time, their exploit will fail. Shuffler is software-based and uses various techniques to minimize performance impact but still shows up to a ~15% overhead. You could easily imagine hardware assist removing most of this overhead (but this would also need to be secured).

Another interesting approach to handling code read attacks on JIT code uses a technique called destructive code read. Code can be executed normally but if it is read it is immediately garbled, as a method to undermine the usefulness of memory disclosure. The software based on this approach is called Heisenbyte in tribute to the Heisenberg principle which asserts that observation of a state must change the state.

You can read a lightweight write-up on Shuffler HERE and a more detailed paper HERE. A description of a memory disclosure vulnerability in Adobe Shockwave is HERE and a paper on Heisenbyte can be found HERE.

More articles by Bernard…


It’s Better than SUPREM for 3D TCAD

It’s Better than SUPREM for 3D TCAD
by Daniel Payne on 12-06-2016 at 12:00 pm

Process and device engineers have a tough task to model and simulate an IC process prior to fabricating silicon, however this approach is much better than the alternative choice in the 1970’s of just running multiple lots of wafers and then making measurements to see if your node was meeting specifications. Out of Stanford University came a process simulator tool named SUPREM some 30 years ago, and the industry adopted it along with researchers. Nothing lasts forever, and so is the case for SUPREM because alternative tools for process simulation are available.

An ideal process simulator should have many capabilities, like:

  • 1D/2D/3D process simulation
  • Adding new materials
  • Create new processes
  • Low learning curve
  • A path from SUPREM decks
  • Flexible methods for simulation meshes
  • Supporting layout-driven process simulation

When I think of TCAD tools the company name of Silvaco comes to mind, and they are presenting a webinar on December 8th at 10AM PDT. More info here.


Simulation of a SRAM cell

Silvaco has both a 1D/2D/3D process simulator (Victory Process) and a 2D process simulator (Athena), and the focus of this webinar is on Victory Process. Here’s what you will learn at the webinar:

 

  • Key differences between Athena and Victory Process
  • How to translate legacy SUPREM-based decks to VP2D using DeckBuild utility A2VP
  • How to set, control and refine/unrefine simulation mesh
  • How to use layout driven process simulation
  • How to use basic geometrical and physical etching and deposition models
  • How to export 2D structures for visualization and device simulation

​The presenter for this webinar is Dr. Misha Temkin, and he’s a Senior AE at Silvaco in the TCAD group. Misha started out some 40 years ago in the USSR and has authored papers and books on TCAD topics. Dr. Temkin has been with Silvaco since 1989 and is an expert in using both Athena and Victory Process tools.


The Future of FPGA Prototyping!

The Future of FPGA Prototyping!
by Daniel Nenni on 12-06-2016 at 7:00 am

This interview originally appeared as the foreword to our book “Prototypical: The Emergence of FPGA-based Prototyping for SoC Design” but I thought it would be worth publishing for those of you who have not downloaded it yet. I also wanted to mention that our friends at S2C are currently offering a 50% discount on the Prodigy Kintex UltraScale Prototyping Solution Package to get you started on your prototyping journey.

Remember, the health of the semiconductor industry revolves around design starts which translate to wafer starts and ultimately product shipments. If all goes well the semiconductor industry continues to grow and we live happily ever after, right?

Unfortunately, all does not always go well with design starts and nobody knows that better than Mon-Ren Chene, the CTO of S2C. His 30+ year semiconductor career spans: EDA, FPGA, Emulation, and FPGA prototyping so he is definitely the right person to ask about a successful design start:

Nearly two decades ago during our time at Aptix, my S2C co-founder, Toshio Nakama and I recognized the power of prototyping. At that time, prototyping was only accessible by large design houses with the budget and means to employ a prototyping architecture. We also recognized that FPGAs had become a popular alternative to the much more expensive and rigid ASICs. It was then that we both decided to team up to develop a prototyping board around an FPGA, and S2C was born. Our commitment to our customers has been to push the limits of what FPGA prototyping can do to make designing easy, faster, and more efficient.

Our goal has always been to close the gap between design and verification which meant that we needed to provide a complete prototyping platform to include not only the prototyping hardware but also the sophisticated software technology to deal with all aspects of FPGA prototyping. Fast forward to today and you’ll find that FPGAs and FPGA prototyping technology has advanced so much that designers and verification engineers can no longer ignore the value that they bring, especially when dealing with the very large and complex designs that we see today. These advances have made FPGA prototyping poised to become a dominant part of the design and verification flow.

This book will hopefully give you a sense of how this is achieved.But what’s next for FPGA prototyping? Having dedicated my time to working with our customers in developing the evolution of FPGA prototyping, I have figured out two things: FPGA prototyping needs to be part of the conversation early on in the design process, and FPGA prototyping needs to move to the cloud. What do I mean by these two statements? Well, let’s break it down.

Design for FPGA Prototyping

Making FPGA prototyping part of the design process early means actually thinking about how the design will be prototyped via an FPGA as you design – Design for FPGA Prototyping. Designing for prototyping will significantly speed up the FPGA prototyping process downstream. It will aid in the act of synthesis, partitioning, and debug. I’ve outlined six ways that this is achieved:

(1) Prototyping-friendly Design Hierarchies
Design architects can make the job of prototyping much easier for engineers to implement FPGA prototyping by modifying the design hierarchy to work better in a prototyping environment. The engineers who perform implementation or verification usually have very little ability to improve prototyping performance once the design hierarchy is fixed. The need to do partitioning down to the gate level can be removed if the size of each design block can be kept to one FPGA. Furthermore, modifying the design hierarchies early can help to avoid pin congestion as many times a design becomes very difficult to implement in an FPGA or becomes very slow because there’s a central block that has tens of thousands of signals that need to go to multiple blocks in different FPGAs. Design architects can also ease prototyping by providing guidance to their FPGA implementation team(s).

(2) Block-based Prototyping

Instead of hoping the entire design will magically work when mapped and downloaded to multiple FPGAs, bringing up subsystems of the entire design, block by block, will allow quick identification of both design issues in a sub-block as well as any issues related with mapping the design to the FPGA(s). Blockbased prototyping works well especially with designs that contain many 3rd party IPs that also needs a lot of real time testing and early software development.

And very often, designers don’t even have the RTL source code for the IP blocks from 3rd parties (for example, ARM processors) and therefore cannot map the IP to the FPGAs themselves. This can be solved by requesting the IP provider to supply the encrypted netlist so that you can synthesize and partition the entire design while treating that IP as a black-box. As long as you specify the correct resources (LUT, registers, I/Os), the prototype compile software should take those resources into account when partitioning to multiple FPGAs. You can then integrate the encrypted netlist during the place and route stage.

I’ve come across customers that want to do an FPGA implementation but are reusing some very old blocks with only the ASIC netlist and without RTL. Implementation becomes very difficult since the details of the design are unknown. These legacy designs are usually only accompanied by a testbench. In this case, the best approach is to covert the ASIC gates to an FPGA and to use a co-simulation environment (such as S2C’s ProtoBridge™) to verify if the functionality of the block is correct before integrating it with the entire design. Unfortunately, this is still a painful process so designers should consider either not using those legacy blocks or re-writing them.

Note that a reconfigurable and scalable prototyping system is needed for a block-based prototyping methodology, as well as a robust partitioning and FPGA prototyping software flow.

(3) Clean and Well-defined Clock Network for Prototyping

Many ASIC designs have tens or even hundreds of clocks and most of them are just for power management/saving. Even with the most complex designs there are usually a few real system clocks plus some peripheral clocks such as PCIe and DDR. Peripheral clocks usually reside in a single FPGA which has the actual external interface pins and therefore are easy to implement. System clocks, however, need to go to every FPGA and therefore should be clean for FPGA implementation.

ASICs use a lot of gated clocks to save power. Today’s FPGA synthesis tools have advanced to take care of most of the gated clocks, but there may still be some gated clocks that go undetected and therefore cause design issues. This can easily be avoided by creating two different RTL clock implementations for the ASIC and the FPGA by using IFDEF.

Internally generated clocks can also be a problem for an FPGA prototyping environment as they all need to get on the FPGAs’ global clock lines and synchronize among all the FPGAs. A Multi-FPGA prototyping system will have a limitation on how many of these global clocks can be supported therefore the number of the internally generated clocks should be restricted (or again use two implementations in the RTL: one for ASIC, and one for FPGA).

4) Memory Modeling
ASICs support many different types of memories while FPGAs usually support two types: synchronous dual port memories, or the use of registers and LUTs to build custom memories. The latter one consumes large amounts of logic resources and might cause place and route congestion. Most ASIC memories can be re-modeled to take advantage of the block memories in the FPGA but a manual process may be required to do that. Again, instead of having the engineers who try to implement the ASIC design in a FPGA model the memories, a better approach would be to have the architects plan the designs with two memory implementations both for ASICs and FPGAs. The RTL designers then code using IFDEF to have the two implementations. FPGA prototyping becomes easy by just instantiating the correct memory implementations.

5) Register Placement on the Design Block I/Os

FPGAs usually have a lot of register resources available for the design but most ASIC designs try to use less registers to save area and power. Ideally, all block I/Os should be registered for FPGA implementation to achieve the best results. At a minimal all outputs should be registered so no feed-through nets (which impact system performance by half) will be created after design partitioning. As a result, there will be a noticeably higher FPGA prototyping performance with this approach.

6) Avoid Asynchronous or Latch-based Circuits
Asynchronous circuits and latch-based designs are FPGA unfriendly. It is very hard to fine-tune timing in an FPGA with every FPGA having to be re-place and re-routed multiple times. These issues become even worse when the asynchronous circuits have to travel across multiple FPGAs.

Moving to the Cloud

We are living in an age where design teams no longer reside in one geographic location. No matter how big or small, companies have multiple design teams in multiple locations. A cloud-based FPGA prototyping system is an ideal way for dispersed teams to manage the prototyping process and resources.

Furthermore, as smaller IoT designs proliferate the market, FPGA prototyping must become accessible to these designers. Today’s FPGA prototyping, although effective, can be costly for smaller IoT designers to adopt. The reusability of boards becomes less viable so costs cannot amortized over multiple design starts. By moving to the cloud, FPGA prototyping solutions can become a shared resource and thus can
reduce cost inefficiencies. The future of FPGA prototyping is strong. It has and will continue to demonstrate itself as one of the most effective solutions to realizing the full potential of any design.


It’s Apple TomTom Time Again

It’s Apple TomTom Time Again
by Roger C. Lanctot on 12-05-2016 at 4:00 pm

It’s December and time for the annual Apple-should-buy-TomTom rant. Of course, we know Apple prefers younger, smaller companies with brighter and clearer long-term prospects, but we also know Apple navigation sucks and if there is one thing TomTom does well it’s navigation… and traffic.

To stir the pot, TomTom released a statement two days ago:

“Amsterdam, 02 December 2016 – Responding to questions in Dutch media today, TomTom (TOM2) announces that within the Consumer business unit 170 roles have been reorganized. Of those roles, 110 will move to other areas within the company and 60 roles are made redundant, of which 24 are in The Netherlands.”

The announcement points to nothing in particular other than disappointing results from the consumer group. Regular followers of TomTom’s quarterly earnings will be well acquainted with the painfully slow evolution of the company’s business away from consumer-focused portable navigation devices and toward automotive, fleet and service and software oriented businesses. TomTom has cleverly launched products for golfers along with fitness devices and its Bandit action cams, but all of these categories have yet to fill the crater created by declining PND sales.

A few things are different this year. First of all, on this date, one year ago, TomTom’s stock was at a nine-year high of $12.10. For most of 2016 the stock has traded in a narrow range after falling from that high.

Second of all, TomTom has built its fleet business to a last-reported total of 671,000 subscribers for one of the largest fleets in the world behind LeasePlan, Enterprise Holdings, UPS, FedEx, Verizon and a few others. The achievement ought to command a higher perceived value – especially given the frothy merger and acquisition environment.

The roster of potential acquirers is legion and includes Apple, Alibaba, Baidu, Alphabet or maybe a Tier 1 auto industry supplier (Panasonic, Sony, Continental), a car maker consortium (Toyota, Renault-Nissan, Mazda), or a carrier (Vodafone, AT&T). The list no longer includes Samsung.

The fact that neither Verizon nor Samsung saw fit to grab TomTom suggests that TomTom is either asking too much or is perceived as possessing too much baggage and/or overhead. Somehow, the existing TomTom book of business from Volvo, Ford, Volkswagen, Subaru, Renault-Nissan and others was not enough to catch Samsung’s eye. But, again, TomTom is no doubt looking for an $8B-$10B exit at least.

There is reason to hold out for that kind of pricing given Verizon’s recent Fleetmatics acquisition ($2.4B) or the acquisition of video telematics provider Lytx by GTCR in February 2016 for $500M. A wave of dashcam companies have elbowed their way into the market including Nauto, Navdy, Netradyne, Carvi and others.

Most of these dashcam wannabes are targeting usage-based insurance, automated driving and advanced driver assist technologies along with thinly veiled intentions to build their own map databases to compete with TomTom and HERE. TomTom already has a map. So why isn’t TomTom getting into the dashcam game? Good question. None of the financial analysts on the last earnings call asked it.

There is one ominous reason TomTom’s stock isn’t on the rise in the manner it was 12 months ago. The latest speculation around Apple is that the company is looking into using drones to enhance its map-making capabilities. The rumor seemed a little zany to me, but what isn’t zany is Apple’s courtship of the OpenStreetMap community and increasing preference for using OSM maps over TomTom maps in 100 overseas markets.

The narrative of an eventual or even possible Apple acquisition of TomTom has steadily unraveled during 2016. So this is my last Apple-should-buy-TomTom rant. TomTom is clearly an automated driving and, increasingly, a fleet play and, as such, remains a prime acquisition target.

TomTom, more than any other company, is in the existential throes of trying to determine whether it is, was or will be primarily a business-to-business or business-to-consumer company. The B2B call is strong, but the company’s DNA has long derived from B2C. It may take TomTom another year, but the time is rapidly approaching when the company must pick one or the other.