SemiWiki – Page 682 – The Open Forum for Semiconductor Professionals

January 5, 2016

Preview of International CES 2016

Preview of International CES 2016
by Bill Jewell on 01-05-2016 at 4:00 am
Categories: IoT

Monday, January 4, 2016, Las Vegas, Nevada
Today I attended CES Unveiled, which offers a sneak peak at some of the new products being introduced at International CES 2016. The Internet of Things (IoT) has been hyped as a key driver of electronics market growth over the next few years. There were plenty of examples at CES Unveiled. Numerous “smart” products were on display. Some of these products seemed questionable as to whether they were of any practical use. Others were innovative and solved real problems.

The “smart” products included a toothbrush, shower head, tennis racket, shoe, remote control, steering wheel, piano, ceiling fan and smoke alarm battery. A Fridge Cam allowed you to use your smartphone remotely to see what was in your fridge so you could buy what was missing (unless your spouse moved stuff around). Two separate products promised to stimulate hair growth (below). Some of the booths looked like late night TV infomercials.

The CES Innovation Awards included several products which were not only innovative but practical. Ricoh introduced a camera which captures 360 degree scenes.

Deeper introduced a wireless fish finder which works with your smartphone. My brother-in-law would love this.

HP introduced an all-in-one PC which features a curved, panoramic monitor. This could replace multiple monitors in many applications.

Two products from related companies offer relief of pain and discomfort. Quell’s device for chronic pain claims 86% satisfaction from users. The device is worn on the thigh and works primarily for back, leg and feet pain.

Reliefband is a device worn on the wrist to relieve nausea due to motion sickness, pregnancy, chemotherapy and other causes. The device emits gentle electrical pulses which work with the body’s nervous system to relieve nausea. Both of these products are consumer versions of proven medical technology.

These are but a small sampling of the products which will be introduced at CES 2016. I will provide daily updates through Thursday, January 7 on my website at www.sc-iq.com

January 4, 2016

A System Spin on IoT Security

A lot of progress has been made in infrastructure to secure edge nodes in the IoT and to secure communications between edge nodes and gateways, all of which is good and necessary to block manifest evil, but it’s never enough. Perfect security is and always will be an asymptotic goal, so there should always be room for new ideas. To a large extent our approach to security looks a lot like what we already understand in the traditional Internet; self-defense within nodes plus firewalls in the infrastructure to limit the spread of contagion. One possible approach to augment this base-layer would consider security from a system perspective – how the system as a whole can defend its integrity, while acknowledging that some components may need to be sacrificed in defense of the greater good.

In 2014 I wrote an article in another forum in which I discussed biology-inspired approaches to security. Some of the details may be a little dated but I think the principles are still relevant. The core idea is that the IoT, at least at the scale we eventually envision, is a very large system with a very large attack surface, not unlike biological systems. Therefore, biological defenses may be a productive source of inspiration for added defenses we might consider. Most of this is based on work done by others. What I added (I hope) was to collect together the ideas and view them in the context of the IoT.

Let’s start with diversity. The engineer in each of us says that we should drive to a small number of system types with as much commonality as possible because standards encourage growth and innovation and reduce cost. But lack of diversity also carries risk – a pathogen exploiting a zero-day weakness may be able to spread quickly through the system before effective counter-measures can be found. A famous biological counterpart is the Irish potato famine in which almost all of the crop, based on a single strain, was wiped out. You might argue that a proliferation of vendors and applications will solve this problem, but I’m not so sure. Much of that diversity may be only skin-deep thanks to the dominance of a limited set of core architectures and OSes. And in time, as in most markets, the majority of product volume will be supplied by a couple of dominant players. All is not lost though. There are ways to add diversity even to common platforms, for example by randomizing stack layout.

Another technique is to mimic immunological defenses. The basic idea here is to identify potential pathogens based on behavioral rather than structural signatures (the standard approach in computer virus defenses), since behavioral signature detection is potentially much more economical, especially in edge nodes, than structural-based approaches. The system must be trained to identify “self” or normal behavior from unexpected behavior, mimicking biological immunity inherited through evolutionary adaptation. Simple examples might be (self) allowable paths of IP addresses for communication or (non-self) detecting a fragment of the device encryption key in an I/O channel.

In the example above, there is an important difference from traditional approaches to security. By the time a behavioral trigger is fired, an attack is possibly already underway or may have succeeded. At that point, the best goal may be to sacrifice the node. The parallel in biology is programmed cell death – or equivalently an IoT node shuts itself down (in critical cases an exception might be to fail-over to a default non-programmable behavior). The node also emits an alarm signaling surrounding nodes to disable communication with this node, allowing for the possibility that it may already be too compromised to effect a shut-down..

The last method I mention builds on a common pathogenic strategy – deception – and is well-known today in IT security systems. Pathogens can evade immunological defense through deception by making their behavior appear like “self” behavior. A counter-deception strategy would be to present tempting but fake “honeypot” targets. These may be dummy DNS targets, empty file or directory links, or dummy accounts with temptingly easy passwords. Any attempt to access one of these triggers an alarm, which again may be used to trigger self-sacrifice. Finally you make these hard to evade by having many more honeypots than real targets.

Hopefully you see in these ideas at least a different way to think about security and especially a way to think about whole-system defenses (top-down) as a complement to more traditional defenses (bottom-up). None of these is any more “invincible” than other approaches. But by further raising the bar, they should increase the cost and therefore decrease the likelihood of attack. You can read the complete article HERE.

My Life at Fairchild – 1980-1983

My Life at Fairchild – 1980-1983
by Mark Rioux on 01-04-2016 at 12:00 pm
Categories: Foundries

After spending my first year learning a great deal about Diffusion and completing my orientation at Fairchild, I was moved to the 3″ Photolithography area as a sustaining engineer. As with the Diffusion area, being a sustaining engineer in Photo meant dispositioning lots on hold and making process improvements as needed.
Continue reading “My Life at Fairchild – 1980-1983”

January 4, 2016

Inventor of Netscape Looks at IoT

Inventor of Netscape Looks at IoT
by Daniel Payne on 01-04-2016 at 7:00 am
Categories: IoT

1995 was the year that a co-worker walked into my cubicle and said, “Hey, you have to see this new web browser and Internet thing.” I promptly installed Mosaic, later renamed Netscape, and began surfing the web with all of those interesting hyperlinks bringing me to new articles. Marc Andreessen was the mastermind behind Mosaic and Netscape, so I give him a lot of credibility to spot new trends in our tech-dominated world.

Looking beyond the common Smart Phone that we enjoy today, Andreessen sees a world of ambient or ubiquitous computing where, “You walk up to a wall, sit at a table and talk to an earpiece or eyeglasses to make a call.” That reminds me quite a bit of the weekly cartoon series, The Jetson’s, where in 1962 they portrayed a future of ubiquitous computing and automation.

Marc is asking questions like, why have a smart phone at all?

A California start-up called Samsarareceived a $25 million investment from Andreessen to help them automate industrial processes using IoT. They offer IoT Gateways, Environmental Monitors, Input Modules and Power Monitors. Industries like pharmaceuticals, transportation, power deliver and water are all using Samsara for sensors and data analytics in the cloud.

Industrial or Vehicle IoT Gateways

Wireless Monitor with temperature probe

Self-powered wireless input module with 2X analog inputs, for 4-20mA current loop sensors

Market research company Gardner is projecting that businesses will be spending some $1.4 trillion on IoT in 2016, growing to $3.0 trillion by 2020. IoT startup companies are raking in investments to the tune of $7.4 billion so far, which was a doubling in just the past five years.

Manual measurements just cost too much money and waste manpower, so the industrial IoT is starting to really automate the processes in our hospitals, pharmaceutical supply chains, and warehouses. By installing inexpensive sensors, then uploading and analyzing the data in the cloud, the Samsara approach is about 1/10th the cost of other industrial approaches. An American yogurt company called Chobani, two big pharma companies and city water districts are all in trials with Samsara products. The water districts want to know how much energy they are using for their water pumps and to understand the usage patterns.

Andreessen looks out over the next 20 years and seeing nearly every physical item having a computer chip or sensor embedded. I’m hoping that this product growth for industrial IoT applications will translate into a very healthy semiconductor market with opportunities for broad growth. It will be quite interesting to see if the hardware or software oriented companies will make more revenue for industrial IoT. Companies like Samsara are owning both the hardware and software, so should be in a good position to control the end product and help users gather and manage all of that analytics coming from embedded devices.

Marc Andreessen, source:Reuters

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Who Does Voice Recognition in the Samsung Gear S2?

Who Does Voice Recognition in the Samsung Gear S2?
by Eric Esteve on 01-03-2016 at 4:00 pm
Categories: Ceva, IP

If you have bought a Samsung Gear S2 smartwatch for Christmas, you certainly didn’t open it to do a teardown. Chipworks did it and have shared the results: Qualcomm is the big winner here with five different chips: Snapdragon 400 as the main CPU of the system, the RF transceiver, the audio codec, the power and the baseband processor (MSM8226). Not really a surprise as the Qualcomm wireless port-folio is certainly the strongest in the industry.

Samsung has integrated three of its own chips, DRAM memory, NFC controller and Wi-Fi module, a DC-DC converter for AMOLED, accelerometer and gyroscope and barometer from STMicroelectronics and another DC-DC converter from TI. In fact, the real surprise comes from a chip from DSP Group HDClear family, especially dedicated to manage the audio command capabilities of Samsung Gear S2. At the heart of the DSPG HDClear is CEVA-TeakLite-III DSP core that DSPG has licensed a few years ago.

HDClear DSP includes noise reduction algorithms and filtering ambient noise of any kind to deliver “cleaner” speech to ASR (Automatic Speech Recognition). According with DSP Group website, HDClear technology outperforms other available solutions, with Word Error Rate (WER) under 20% in any ambient noise environment.

CEVA-TeakLite-III DSP core delivers the processing power providing the exceptional voice intelligibility of this DSPG HDClear chip while enabling extremely low power always-on capabilities, making HDClear is the lowest power chip of its kind in the industry, according with DSPG.

Let’s zoom on CEVA-TeakLite-III, a true 32-bit DSP addressing high-end audio processing, voice processing and wireless baseband applications. TeakLite-III is based on a fully synthesizable dual-MAC native 32-bit DSP engine forming the basis of two implementations: the CEVA-TL3210 and CEVA-TL3211 DSP cores. The CEVA-TL3210 offers a wealth of high-end features including a configurable L1 program cache memory and support for industry-standard APB and AHB-Lite system busses. The CEVA-TL3211 offers configurable L1 program and data cache memories, support for high-speed AXI system busses, and an integrated Power Scaling Unit (PSU).

Based on a native 32-bit architecture, the CEVA-TeakLite-lll can perform two 16×16-bit Multiply-Accumulate (MAC) operations or one 32×32-bit MAC in a single cycle. The CEVA-TeakLite-lll also offers:

Strong bit-manipulation capabilities for stream processing
Up to three instructions executed in parallel
Dedicated single-precision and double-precision FFT instructions
Up to 4GW program memory and 4GW data memory (16-bit words)
L1 program memory (cache or TCM)
L1 data memory (CEVA-TL3210 = TCM; CEVA-TL3211 = 2-way, set-associative, hardware-configurable cache)

An integrated Power Scaling Unit (PSU) provides advanced power management including support for clock and voltage scaling, only available with the CEVA-TL3211. This PSU is responsible for the very low-power capability of the CEVA-TeakLite-lll DSP core. This low-power feature has certainly been one of the main reasons for the DSPG HDClear design win into the Gear S2 smartwatch.

Voice recognition algorithms can require very intensive DSP computation, especially in noisy ambient environment. 20% error rate would be dramatic for any networking or storage system, but a Word Error Rate (WER) under 20% is completely acceptable for voice recognition system. If you speak to pilot your Gear S2 smartwatch using a 5 words sentence, in the worst case scenario the HDClear DSP will transmit 4 words to the main CPU. If you make a test, you realize that the recognition of 4 words in a 5 words sentence is probably enough to rebuild the initial message.

Did you know that CEVA-TeakLite family of DSPs has shipped in more than 4.5 billion devices to date, making this DSP IP core the leader in audio/voice for mobile ? Now that audio/voice is making its way into more and more devices as a means to control and activate (think of voice-controlled smart home systems, handsfree automotive systems), no doubt that CEVA-TeakLite family of DSPs are set to power billions of new devices outside in the handset space. The Samsung Gear S2 design win is the first of its kind but is truly only the beginning of a new era of smart and connected CEVA -powered devices.

Eric Esteve from IPNEST

Internet of Things 2015 Year End Review: IoT Business Ecosystem

Internet of Things 2015 Year End Review: IoT Business Ecosystem
by Alex G. Lee on 01-03-2016 at 12:00 pm
Categories: Automotive, IoT
2 Comments

Goldman Sachs defines the Internet of Things (IoT) as the third wave of internet revolution: By connecting billions of devices to the internet, the IoT can open up a host of new business opportunities and challenges. According to McKinsey, the IoT has the potential to create up to $6 trillion economic value annually by 2025. According to Research and Markets, there are more than 2000 companies that are selling the IoT enabled products, playing a vital role in the IoT technology innovation, or act as an enabler to the IoT business development.

A business ecosystem is the community of business entities that is formed by the competitive and collaborative interactions among business entities for new innovations. A business ecosystem evolves to form a new value network, and thus, to create a new market. The IoT has various applications including, smart home, connected car, connected health, and business/industrial applications. Thus, many business players across diverse industries including semiconductor, consumer electronics, IT, telecom, healthcare, medical devices, retail, industrial & manufacturing and transportation are participated in the IoT business ecosystem.

The key IoT business ecosystem players based on their patenting activities are Samsung Electronics, Google, Toyota, Ford, GM, Philips, GE, IBM, Cisco, and Ericsson.

Samsung Electronics is a key IoT business ecosystem player in the smart home applications. In number of patent applications, Samsung Electronics dominates the patent applications (nearly 15% of the more than 400 total patent applications among more than 70 patent owners). Samsung Electronics patent applications are highly focused on the home automation and security to support its current Samsung SmartThings business. Samsung SmartThings is the first fully integrated smart home system for providing the home automation and safety services to make people’s daily lives easier, more comfortable and safe. Recently, Samsung filed several patent applications regarding home energy management and smart lighting for providing other value added services to make Samsung as the smart home market leader in 2016.

For example, US20150330652 illustrates the temperature control method and device of a heating/ventilation/air-conditioning (HVAC) system for efficiently saving energy. The method includes determining occupancy or non-occupancy of a user in a space subject to temperature control. When the user’s non-occupancy is determined, the temperature control device determines whether to start the temperature control based on probability distribution of a non-occupancy period that is predetermined. When it is determined to start the temperature control, the temperature control device determines the user’s target temperature based on previously collected data, calculates a setback temperature based on the target temperature, and performs temperature control according to the calculated setback temperature.

Google (including Nest Labs) is another key IoT business ecosystem player in the smart home applications. In number of patent applications, Google also dominates the patent applications (nearly 15% of the more than 400 total patent applications among more than 70 patent owners). Google patent applications are focused on the energy/utility management. There are also many recent patent applications regarding the safety monitoring (e.g., hazard detecting, elderly care) and home security. For example, US20150120598 illustrates the smart home system for protecting delivered packages from a thief. The system can receive and retain package in a secure location that is trusted by both deliverer and a system user.

Google also has significant number of patent applications regarding the health monitoring biomedical sensing devices. The health monitoring biomedical sensing devices can provide a real time monitoring of person’s health status such as concentration of glucose, heart rate and blood pressure, and thus, enable remote healthcare services.

For example, US20150164321 illustrates an eye-mountable device for measuring an intraocular pressure. The device includes a transparent polymeric material having a concave surface that is mounted over a corneal surface of an eye, an antenna, an expandable member, a sensor and control electronics that is embedded in the transparent polymeric material. The device can expand and apply a force to the corneal surface and the sensor can detect a resistance to deformation of the cornea in response to the applied force. The resistance to deformation of the cornea in response to the force applied by the expandable member is indicative of the intraocular pressure of the eye.

Toyota, Ford, and GM are three key IoT business ecosystem players in the connected car applications. Their patent applications regarding the IoT connected car applications cover the safety/collision avoidance, intelligence navigation, driver assistance for smart driving, infotainment, and vehicle operation automation. The IoT connected car applications exploit the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems.

For example, Toyota patent application US20140005906 illustrates the system for assisting the driver of a host vehicle through predicting the future position and velocity trajectory of a preceding vehicle. The preceding vehicle is a vehicle immediately ahead of the host vehicle, and the dynamic state of the preceding vehicle was predicted based on data received from surrounding vehicles using the V2V communications. The system allows a more comfortable driving experience in dense traffic environment. US9031779 illustrates the navigation system with the hazard avoidance feature. The system navigation allows for vehicles and other entities to collaborate and share information via vehicular networks regarding hazards, defects, obstacles, flaws, and other abnormalities that exist in any environment. The system navigation automatically detects and catalog environmental hazards and/or obstacles for route planning. Routes can be planned that avoid these hazards reducing lost time or frustration.

As another example, Ford patent application US20150149088 illustrates the autonomous vehicle collision avoidance system. The system enables autonomous vehicle predicts objects lie in a planned path of the autonomous vehicle. Accordingly, the system determines when a collision between the vehicle and objects is possible and alters the vehicle path to avoid the potential collision.

Philips is a key IoT business ecosystem player in the connected health applications. Philips announced a partnership with Amazon to provide a new platform for the IoT connected healthcare applications. Philips connected healthcare platform is based on its cloud-based HealthSuite platform and Amazon AWS IoT platform. Philips patent applications regarding the IoT connected health applications cover the healthcare IT System, Tele health/medicine, body sensor network, and preventative and predictive healthcare. For example, US8884754 illustrates the method of monitoring the vital parameters of a patient using the body sensor network. The method improves the data transmission between on-body sensors of the body sensor network with the off-body monitoring device. Philips also has significant number of patent applications regarding the smart lighting system for the smart home/building applications.

GE is another key IoT business ecosystem player in the connected health applications. GE is also a key IoT business ecosystem player in the industrial applications. According to Industrial Internet Insights Research Report from GE and Accenture, the Industrial Internet—the combination of Big Data analytics with the Internet of Things (IoT)—will produce huge opportunities for companies in Aviation, Oil and Gas, Transportation, Power Generation and Distribution (e.g., smart grids), Manufacturing, Healthcare, and Mining industries. For example, US20150040051 illustrates the industrial monitoring system that provides monitoring capabilities for various types of mechanical devices and systems. US20150032464 illustrates the system to analyze patient information obtained from the biosensors and recommend the personalized medicine therapy approach based on the patient information exploiting the predictive analytics. GE also has significant number of patent applications regarding the smart lighting system for the smart home/building applications and the smart home automation.

IBM is a key IoT business ecosystem player in the data analytics for the IoT applications. IBM announced a plan to invest more than $3 billion over the next four years to build the IoT business. Predictive analytics analyzes current and historical data to make predictions about future events and trends. Predictive analytics can apply to many IoT applications such as real-time asset management and predictive maintenance of industrial equipment. For example, US20140236650 illustrates the cost effective end-to-end analytics driven asset management by managing maintenance operations (e.g., scheduling, preventive maintenance, operating parameter control). IoT big data analytics are becoming important to process unimaginably large amounts of information and data that are obtained by the sensor embedded interconnected IoT devices. For example, US20150134704 illustrates the system for processing large scale unstructured data in real time.

Cisco is a key IoT business ecosystem player in the IoT connectivity/networks. Recently Cisco and Ericsson announced a strategic partnership to create the networks of the future. Cisco filed more than 100 patent applications regarding the IoT connectivity/networks. Cisco patent applications cover the intelligent autonomous IoT networks exploiting the machine learning (ML), predictive analytics for the IoT networks, deterministic networking for smart grids, and fog computing. For example, US20150195216 illustrates the use of the ML in order to estimate the behavior of the communication channels based on prediction, and then, to select the appropriate transmission strategy in the multi-hopping networks. US20150333992 illustrates the application of predictive analytics for managing the IoT Networks.

Billions of interconnected devices that are connected to the internet in the IoT will produce astronomical amount of data to process. The amount of data can easily overload the cloud computing resources at the back-end IT systems. With Fog (or Edge) computing, the problem can be eased by allowing smart devices (e.g., smartphones, PCs, set-top boxes) at the edge of the IoT networks. US20150261876 illustrates the network environment includes multiple fog computing devices each connected with a communication network.

Ericsson is another key IoT business ecosystem player in the IoT connectivity/networks. Machine to Machine (M2M) communications involve the communication (using wired or wireless means, or a combination of both) between two machines without human intervention. Ericsson is developing the seamless M2M networks with high mobility and reduced latency. For example, US20150319771 illustrates the M2M networking of the IoT device at low cost that complies with modern cellular communication standards while having low power consumption. US20150078327 illustrates the mobility-based radio resource assignment methods. US20150305054 illustrates the method for power optimized transmission scheduling in an energy harvesting M2M device. US20150249901 illustrates the M2M services enablement architecture using a cellular access networks.

Ericsson is also developing 6LoWPAN. 6LoWPAN is an acronym of IPv6 over Low power Wireless Personal Area Networks. 6LoWPAN is a set of standards defined by the Internet Engineering Task Force (IETF), which enables the efficient use of IPv6 over low-power, low-rate wireless networks on simple embedded devices through an adaptation layer and the optimization of related protocols. Its main goal is to send/receive IPv6 packets over 802.15.4 links. IoT connectivity standard Thread uses 6LoWPAN for connecting smart home devices. 6LoWPAN radio devices are typically constrained with respect to memory/processing resources, power consumption, and radio transmission range. Integration of the network of 6LoWPAN-compliant low-power devices is the challenge and continues to present a significant obstacle to implementing advanced IPv6-based IoT services. Ericsson patent application US20150245332 illustrates the system for providing access with respect to 6LoWPAN format in a number of IoT networking implementations exploiting 6LoWPAN-compliant low-power devices.

Semiconductors Future Hinges on a Single Pillar

Semiconductors Future Hinges on a Single Pillar
by Pawan Fangaria on 01-03-2016 at 7:00 am
Categories: EDA, Foundries, IoT, IP

A unique phenomenon has started manifesting itself under the slew of mergers and acquisitions this year in the semiconductor landscape. This phenomenon is bound to intensify in the near future and would positions itself as a key factor for the future of the semiconductor industry. The winners and losers in the game would be determined on how successfully they are able to execute on this aspect. In fact, this is one of the key aspects responsible for pushing companies towards mergers too.

Mergers and acquisitions are part of usual cycle of consolidation after expansion. Considering the macroeconomic conditions, I have been foreseeing the increase of M&A activities since 2011, of course it is happening since much earlier than that but it intensified in 2015. With the recent announcements of mergers, which are expected to complete in 2016, the total deal size of semiconductor mergers in 2015 has gone much beyond $100 B. Earlier peaks were $70.3 B in 2000 and $75.2 B in 2006.

I have been keeping track of key mergers year after year and reflecting on main themes of some of those in my blogs on semiconductor landscape. This time there are too many mergers, large and small, so it’s pointless talking on particular mergers, but it makes sense analyzing the key themes around which number of mergers have taken place. A common theme around all these is new technology which will act as the main pillar for the semiconductor industry in the near future.

We have seen how macro economy has struggled since 2008 and yet not fully out of woods, although US FED has garnered confidence to start increasing interest rates. Thanks to business leaderships of companies who have been able to consolidate with good technology leaders who needed funds to grow. What’s next after such massive business consolidation this year?

In most of the current mergers, one key aspect was visible: technological expansion. It’s consolidation with a view to expand in emerging technologies; so it’s complementary as against concentration. In my view, macro economy and business in semiconductors will continue on their own pace, IP leadership will continue as usual. What will see a massive change in near future is technology, which will in turn infuse new life to semiconductor business going forward.

The future of semiconductor industry will depend on how new technologies pan out to support emerging businesses. Let’s review some of the common technological themes based on which some of the key mergers have taken place, and more may be seen.

Internet of Things – IoT has emerged as a general theme from which several verticals have originated from a business stand point, e.g. industrial, home, automotive, consumer, medical, wearable, and so on. From a technological stand point all of them converge on a system’s view with hardware and software integration, data analytics, big-data management and control, and real-time communication under different protocols. Clearly, IoT opened up many fronts for mergers of companies in hardware, software, as well as IP.

As an example big-data management initiated revamping of data center (cloud server) technology. Good progress was seen in IoT edge and gateway devices, and now the focus is shifting to cloud which will see a major innovation and development in near future.

Intel’s Altera acquisition is geared towards adding programmability, customer IP and security into the data center, and also increasing performance and decreasing cost and energy consumption. Also there are innovations happening elsewhere to improve performance and power efficiency of data centers. A big merger of Dell and EMC is on the horizon in the cloud computing space.

Considering the gateway solution, there have been many mergers, for example Bluegiga and Telegesis acquisitions by Silicon Labs, Lantiq acquisition by Intel, Wicentric and Sunrise Micro Devices acquisition by ARM, and so on.

Also there have been mergers or business arrangements around providing IoT devices in various segments such as health fitness, wearable, automotive, and so on. Dialogacquired Atmel to strengthen into microcontroller business that is a key to IoT. NXPand Freescale merger is another example of big consolidation.

System Design Automation – With SoCs being infused in many applications, and of course IoT, system’s view in design automation has become the key. In this space, the big EDA and IP companies are doing in-house innovation as well as acquiring key technologies to augment their system automation tools. Emulation and FPGA prototyping technologies are coming to the forefront.

Mentorrecently merged Calypto with itself. Earlier Mentor acquired Flexras Technologies to strengthen into FPGA prototyping and Tanner EDA for AMS and IoT solutions. Mentor’s Veloce interface with ANSYS’ PowerArtist is a big step in real-time and accurate power analysis of any application running on a system. Also Cadenceis betting big on virtual emulation with its Palladium technology. Synopsysis strengthening its IP portfolio and software solution for systems; it acquired Atrenta to strengthen its verification platform.

In IP world, differentiation has become important and that leads to difficulty in modeling non-standard IP. ARM, the IP giant acquired Carbon Design Systems to accelerate modeling and verification of their new cores, and testing of the cores in complex SoC designs.

Another area in focus for systems is big-data and analytics. ANSYSacquired Gear Design Solutions, Microsemiacquired Vitesse.

Security – With IoT, security is getting prime importance in hardware as well as software. There have been several mergers around innovation in providing secure systems. ARM acquired Offspark and Sansa Security. Synopsys acquired several software companies includingProtecode, Codenomicon, Quotium’s Seekerproduct and R&D team and Goanna Software for enhancing software security, integrity and privacy in various software applications. This space is ripe for innovative technologies to be acquired.

Semiconductor Technology – At one time process technology was thought to be ultimate at 28nm and 22 nm, but now 10nm is a reality and we are going to see 5nm. This brings new challenges and hence new areas to innovate. Towards consolidation, GlobalFoundries completed acquisition of IBM’s foundry business, and now China is eyeing to acquire GF. In process equipment space, Lam Research is acquiring KLA-Tencor, Cabot Microelectronics acquired NexPlanar, and there are others.

There are several other mergers in different segments of semiconductor design space as well. Avago acquired Broadcom, Samsung acquired Yesco, Western Digital acquired SanDisk, MediaTek acquired Richtek, Diodes acquired Pericom Semiconductor, ON Semiconductor is buying Fairchild Semiconductor and Microsemi is buying PMC-Sierra which recently saw a few other contenders as well. More mergers are to be seen in near future.

New Innovative Devices – These are new devices to automate work in many areas and bring disruption in services traditionally driven by human workforce. Although this can bring more efficiency in work and reduce cost, there can be several repercussions; let’s park that for a later discussion. For now we can see these technologies in the making – Freescale acquired CogniVue getting into autonomous vehicle segment, PTC acquired Qualcomm’s Vuforia to usher into augmented reality, and Qualcomm acquired KMel Robotics to strengthen its strategy into Drone and Robotics market. Also, Qualcomm invested in 3D Robotics. Even Intel invested in drone maker Yuneec. Earlier Intel invested in Airware, and PrecisionHawk, and also in VR headset maker Avegant.

Autonomous vehicle, Robotics, Drone, and VR are some of the upcoming technologies which can bring major disruptions in different service and logistics sectors.

Another twist in semiconductor mergers is being driven by geographic traction. China is working hard to build large presence in semiconductor business from its soil by in-house development as well as acquisitions in other countries.

A deeper insight into this expansion led consolidation can explain very well that the consolidation – expansion cycle will get elongated now. It’s time to watch how these new technologies bring major changes in our lives in the first quarter of this century.

Pawan Kumar Fangaria
Founder & President at www.fangarias.com

January 2, 2016

2015’s Unfinished Automotive Business

2015’s Unfinished Automotive Business
by Roger C. Lanctot on 01-02-2016 at 4:00 pm
Categories: Automotive

The farther we come, the farther we have to go. While progress in advancing personal transportation was made in 2015, the year closes with glaring elements of unfinished business threatening to impede further progress toward mitigating highway fatalities and reducing emissions and congestion. These areas of unfinished business ought to serve as priorities for regulators, auto makers and their suppliers and service providers.
Continue reading “2015’s Unfinished Automotive Business”

January 2, 2016June 14, 2019

The “Era of the Photon” is here!

The “Era of the Photon” is here!
by Tom Dillinger on 01-02-2016 at 12:00 pm
Categories: Cadence, EDA, Silicon Photonics

The 50 year anniversary of the publication of Moore’s Law was recently celebrated, highlighting the tremendous advances in the Microelectronics Eraof the period in human history known as the Information Age. However, the technical and economic challenges currently faced by the microelectronics industry are bringing into question the pace at which product innovations realized under Moore’s Law can continue. Nevertheless, the sheer data volume and demand for information processing throughput is accelerating.

I recently had the opportunity to meet with Gilles Lamant, Distinguished Engineer at Cadence, and several members of the development teams at Lumerical Solutions, Inc., and PhoeniX Software B.V., who presented a compelling case that the future of the Information Age will be defined in a new manner, namely The Era of the Photon.

The demand for faster signal communication in short-reach applications – e.g., both within and between compute servers in data centers – will rapidly transition from lossy copper to optical fiber connectivity, utilizing photonic integrated circuits (PIC’s).

Photonics is a broad term, which encompasses the use of light (photons) to represent information, spanning photon generation through transmission to detection. Optical signaling technology has been the backbone of the telecommunications industry for decades. Optical image sensors are the heart of numerous consumer and industrial product sectors. The utilization of optical communication for data system applications is relatively new, and is expected to grow rapidly.

Photonic devices for data representation and transmission incorporate familiar functionality as their microelectronic counterparts – e.g., multiplexers, modulators, amplifiers – with the additional requirement for electro-optical conversion and coupling to optical fiber. These PIC functions rely upon the precise dimensionality of waveguides fabricated on the IC, as illustrated in the layout below (from PhoeniX Software).

The design and simulation of the waveguide are extremely intricate steps, as the structure requires an (all-angle) curvature – more on that shortly. An attractive characteristic is that additional modulation can be achieved by changes in the refractive index of the waveguide induced by adjacent electrical or thermal stimulus, adding significantly to the simulation complexity. As a result of these intricacies, the current PIC industry is still very specialized, leveraging the expertise of companies such as Lumerical and PhoeniX to provide tools for design capture, model generation, simulation, and release to fabrication.

The fabrication of (discrete) PIC’s is also current rather specialized, typically leveraging unique III-V materials suitable for laser generation, waveguide implementations, and photon detection.

The growing demand for photonics is also driving unique implementations, such as the integration of separate (Si and III-V) signal processing and electro-optical conversion parts in a multi-die packaging solution. And, there’s extensive research underway to investigate fully-integrated, monolithic silicon photonics fabrication, extending existing CMOS process technology to include generation and detection feature. (The difference in refractive index between Si and SiO2 makes embedded silicon waveguides very feasible.) Indeed, several leading research teams have recently published promising results, in terms of potential aggregate bandwidth and low power dissipation per transmitted bit.

Cadence, Lumerical, and PhoeniX Software recognized that a key enabler to the growth of systems incorporating PIC designs is the availability of a productive and familiar design environment, whether for multi-die or monolithic devices. The three companies recently announced a photonic IC platform design flow, with interfaces between the following market-leading tools:

Cadence Virtuoso
PhoeniX Software’s OptoDesigner
Lumerical’s INTERCONNECT and DEVICE modeling and simulation engines

The figure below highlights the tool integration and inter-operability available in this platform.

Designers will now be able to develop electrical and optical “circuits” in a Virtuoso-based environment, with links to the specialized tools from Lumerical and PhoeniX. This architecture builds upon the platform concept behind Cadence’s Virtuoso Analog Design Environment, with additional design and simulation support for photonic elements. (The availability of this environment will also promote the standardization of a photonics PDK release from foundries.)

As mentioned earlier, there are intricacies to photonic elements that are distinct from the traditional chip design and analysis methodology:

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Photonic layout designs utilize the definition of waveguide contours. This differs from the conventional vector representation in IC design, and requires special shapes processing for model generation and discretization for tapeout. OptoDesigner from PhoeniX incorporates unique layout support for photonic cells.

Lumerical provides model generation and (finite-difference time-domain, or FDTD) simulation support for the electro-optical system. The nonlinear effects of electric charge and thermal input modulation to the optical propagation system are supported. Optical simulations import electrical stimulus from a Spice simulation, generated in the Cadence environment.

The Cadence platform provides a familiar environment for the design capture, physical implementation, analysis, and simulation of the electronic circuity, including system-in-package (SiP) technology options. The cooperative simulation of electronic and photonic circuit elements utilizing Cadence and Lumerical technology offers a vastly improved analysis approach, when compared to using separate tools.

Photonic IC’s will become a much more prevalent part of system design. The investment in R&D of new materials and processes (especially, silicon photonics) is growing. This has necessitated focus on a more productive design environment, with specialized tool interfaces. Cadence, Lumerical, and PhoeniX have released an initial design flow, and are committed to expanding the capabilities (e.g., PDK standards, DFM/DFY, reliability analysis, etc.).

We are truly at the cusp of the Era of the Photon. It will be exciting to see how this next phase of the Information Age evolves.

More information on the recent platform design flow for PIC’s is available here.

-chipguy

January 2, 2016

MediaTek X20 Benchmark Leaks: A Prelude to 2016 Mobile Chipset Wars?

MediaTek X20 Benchmark Leaks: A Prelude to 2016 Mobile Chipset Wars?
by Majeed Ahmad on 01-02-2016 at 7:00 am
Categories: EDA, Mobile

MediaTek is making waves, again. The company’s flagship mobile system-on-chip (SoC)—Helio X20—is up against rivals like Apple, Qualcomm and Samsung, according to leaked Geekbench scores, and is leading in some of the performance benchmarks.
Continue reading “MediaTek X20 Benchmark Leaks: A Prelude to 2016 Mobile Chipset Wars?”