Bronco Webinar 800x100 1

IoT Devices Can Kill and What Chip Makers Need to Do Now

IoT Devices Can Kill and What Chip Makers Need to Do Now
by Daniel Nenni on 01-07-2019 at 12:00 pm

After the onslaught of IoT devices Christmas brought to the masses we really need to talk about security or lack thereof. Do me a favor and count how many IoT devices you have now? Our house IoT count is probably a bit higher than average due to my technology addiction but we are firmly in the double digits and the security breach stories just keep on coming.

Ransomware attacks are increasing, I actually know people who have been attacked and had to pay to get their information back with no guarantee that copies were not made or it won’t happen again. Doorbell cams, baby monitors, smart thermostats, fitness trackers, and even alarm systems can all be used to get into your home. Home WiFi routers, once the most vulnerable devices, are now considered quite secure compared to the others, absolutely.

If you really like scary bedtime stories read the 2018 Internet Health Report: Our compilation of research explains what’s helping and what’s hurting the Internet across five issues, from personal experience to global concerns.

Politicians are even concerned. California is now the first state to pass an IoT specific cybersecurity law with more to follow:

This bill, beginning on January 1, 2020, would require a manufacturer of a connected device, as those terms are defined, to equip the device with a reasonable security feature or features that are appropriate to the nature and function of the device, appropriate to the information it may collect, contain, or transmit, and designed to protect the device and any information contained therein from unauthorized access, destruction, use, modification, or disclosure, as specified.

Not a lot of teeth here but a decent start, my opinion. We track both IoT and Security traffic on SemiWiki and it really is startling to see how much more traffic one gets over the other, which brings us to the topic at hand, an IoT security webinar that you will not want to miss:

IoT Devices Can Kill and What Chip Makers Need to Do Now
IoT devices are at growing risk – smart home appliances, vehicles and medical devices are hacked every day. Connected products are vulnerable to physical probing, network interception, reverse engineering and other attack vectors. As hackers become more clever, security solutions must be a few steps ahead. Robust remediation starts with unclonable identities for the MCU and connectivity chip at the core of an IoT product. Traditional security implementations are burdened with additional components, increased complexity, greater costs and longer time to market. By contrast, Intrinsic ID’s SRAM PUF solutions deliver a hardware root of trust with stronger security at a more attractive ROI. During our webinar we will cover: – Why a Root of Trust is critical for securing connected devices – How Intrinsic ID’s patented SRAM PUF powers vital use cases such as key management and device authentication – How SRAM PUF protects against cloning, counterfeiting and IP theft Register today to discover how SRAM PUF delivers the security that today’s IoT demands.

Presenters: Roel Maes: Senior Security Architect, Intrinsic ID Alpesh Saraiya: Senior Director Product Management, Intrinsic ID

About Intrinsic ID
Intrinsic ID is the world’s leading digital authentication company, providing the Internet of Things with hardware-based root-of-trust security via unclonable identities for any IoT-connected device. Based on Intrinsic ID’s patentedSRAM PUF technology, the company’s security solutions can be implemented in hardware or software. Intrinsic ID security, which can be deployed at any stage of a product’s lifecycle, is used to validate payment systems, secure connectivity, authenticate sensors, and protect sensitive government and military systems. Intrinsic ID technology has been deployed in more than 100 million devices. Award recognition includes the Frost & Sullivan Technology Leadership Award and the EU Innovation Radar Prize. Intrinsic ID security has been proven in millions of devices certified by Common Criteria, EMVCo, Visa and multiple governments. Intrinsic ID’s mission: “Authenticate Everything.” Visit Intrinsic ID online atwww.Intrinsic-ID.com.

I hope to see you there.

Also read:

Intrinsic ID’s BroadKey Named ‘IoT Security Product of the Year’ in 2019 IoT Breakthrough Awards


Rapid Prototyping ARM Based Designs Webinar

Rapid Prototyping ARM Based Designs Webinar
by Daniel Nenni on 01-07-2019 at 7:00 am

While writing the definitive book on ARM history we could not have imagined a more different exit than the SoftBank acquisition, not even close. It is now very clear why SoftBank acquired ARM for $31B. It is also very clear why alternatives like RISC-V are trending on SemiWiki and will continue to do so, absolutely. No matter what IP you choose you will have to prototype your design and that brings us to the topic at hand:

Prototyping ARM-based SoCs with S2C’s Prodigy Logic Systems

ARM is the world’s leading technology provider of silicon IP for custom SoCs, for the widest range of devices and applications. Using ARM’s technology to design an SoC is usually the first choice. Quickly building an FPGA prototyping target will significantly accelerate your hardware verification and software development for optimum time-to-market. In this webinar, we will focus on how to quickly prototype ARM-based designs using ARM for SoCs or Juno ARM Development Platform together with S2C’s FPGA prototyping solutions.

Agenda:

  • S2C Company Overview
  • How to quickly prototype ARM-based designs
  • Demonstration – Revised Full-fledged Base TRD
  • Q & A

Presenters:
Daniel Nenni Founder of SemiWiki.com
Richard Chang Vice President of Engineering, S2C.
Another interesting note, S2C was recently acquired by SMIT Holdings, a Hong Kong based security devices provider. This was my fourth acquisition in four years but was quite different from the rest since it involved a foreign acquirer. Seriously, it is a whole new world in EDA M&A, absolutely. Hit me up in the comments section if you want the details or better yet buy me lunch.

Mr Shuai Hongyu, President of SMIT, said, “S2C is a well-established company principally engaged in rapid hardware-based verification systems and software for over 15 years. It has strong presence in China, Japan, Korea and Taiwan. The acquisition added a new and strategically important component to our ongoing business development and helps us to quickly tap into this new industry. It is also in line with our overall investment strategy in the high-technology sector, representing a good opportunity for us to broaden our revenue stream. Through SMIT’s new investments, S2C will be able to accelerate new product developments and provide superior customer support.”

About S2C
S2C Inc. is a worldwide leader of FPGA prototyping solutions for today’s innovative designs. S2C has been successfully delivering rapid SoC prototyping solutions since 2003. S2C provides: * Rapid FPGA-based prototyping hardware and automation software * Prototype Ready™ IP, interfaces and platforms * System-level design verification and acceleration tools. With over 400 customers and more than 2,000 systems installed, S2C’s focus is on SoC/ASIC development to reduce the SoC design cycle. Our highly qualified engineering team and customer-centric sales force understand our users’ SoC development needs. S2C systems have been deployed by leaders in consumer electronics, communications, computing, image processing, data storage, research, defense, education, automotive, medical, design services, and silicon IP. S2C has offices and distributors in US, UK, Israel, China, Taiwan, Korea, and Japan. For more information, visit http://www.s2cinc.com.


CES 2019 Audi and Samsung

CES 2019 Audi and Samsung
by Roger C. Lanctot on 01-06-2019 at 9:00 am

When Nvidia changed its automotive market messaging from an infotainment-centered theme to autonomous driving two years ago – pronouncing the coming tidal wave of robotaxi development – it matched the almost identical epiphany reached by Intel years prior. Automotive infotainment is a low volume, low revenue opportunity for a large semiconductor company – even if it produces headlines.

Intel pivoted to safety after chasing high-end infotainment business at BMW for half a decade or more – ultimately acquiring Mobileye for $15.3B. Nvidia then slotted itself in on many of the same platforms Intel had been targeting at BMW and Audi before concluding that infotainment would be a tough slog competing with Texas Instruments, Renesas, NXP, ST Micro and other suppliers that controlled the vast volume of mass market system sockets.

Qualcomm took a stab with Snapdragon – and has certainly not given up hope of an automotive breakthrough in spite of the failed merger with NXP. But all of these companies – Intel, Nvidia, and Qualcomm – have come to accept that safety and automated driving represent higher volume and higher revenue opportunities for the long haul.

Enter Samsung. Samsung is the newest wannabe player in the automotive space and has announced its first infotainment win – not surprisingly with a luxury German auto maker. Samsung has announced that Audi will use Samsung’s Exynos Auto V9 in an infotainment system to arrive in a car in the market by 2021.

As the largest maker of mobile phones – a business now facing a global decline – Samsung has been looking for new sources of growth and has had its sights set on the automotive industry for years finally acquiring Harman International two years ago for $8B. Samsung is also thought to be the preferred partner, at some future time, for Tesla Motors.

No doubt, Samsung knows that infotainment systems may win headlines, but safety systems deliver dollars. Alas, these days it is difficult to separate infotainment from safety in the latest cars as domains and functionality converge. Presumably CES 2019, next week in Las Vegas, will provide some glimpses of Samsung’s automotive ambitions.

Roger C. Lanctot is Director, Automotive Connected Mobility in the Global Automotive Practice at Strategy Analytics. Roger will keynote the Consumer Telematics Show on January 7 at Planet Hollywood. More details about Strategy Analytics can be found here:

Roger C. Lanctot is Director, Automotive Connected Mobility in the Global Automotive Practice at Strategy Analytics. Roger will keynote the Consumer Telematics Show on January 7 at Planet Hollywood. More details about Strategy Analytics can be found here:

https://www.strategyanalytics.com/ac…e#.VuGdXfkrKUk


CES 2019: Dashboard Dreams

CES 2019: Dashboard Dreams
by Roger C. Lanctot on 01-06-2019 at 8:00 am

The annual trek to Las Vegas arrives this year with visions of sinusitis, chapped lips, flat feet and new concepts for automotive cockpit systems. It is no coincidence that the plaza in front of the Las Vegas Convention Center is dominated by automotive exhibits – along with multiple automated driving demonstrations across the street and a dozen auto makers exhibiting in the North Hall.

What was once a TV, car stereo and home computer show has become a car show. As such, it is as good a place as any to see what it will be like driving cars in the future.

Looking back at CES 2018 we find two head unit concepts that had outsize impact on the market over the past year. One system – a digital dashboard from Harman International – helped to define what has come to be known as a cockpit domain controller; the other, a large display center stack system concept from SiriusXM was actually delivered to market in certain Dodge Ram trucks from FCA.


Samsung/Harman Digital Cockpit: https://tinyurl.com/y9vv3ghm


SiriusXM with 360 L: https://tinyurl.com/yb6d7hte

These two systems represent game-changing designs with implications that resonate today including:
Samsung/Harman system:

  • Integration of safety and infotainment content
  • Availability and integration of multiple digital assistants
  • Smart home tech integration
  • SiriusXM 360 L:
  • Audio content searchable by artist, genre, category (talk, sports, news, etc.), location
  • Digital assistant control
  • Satellite-cellular integration – first of its kind
  • Up to five profiles with recommendations
  • Cross platform content management – smartphone, radio, satellite
  • In-dash account/subscription management

CES 2019 will see further explorations of digital dashboards from companies including Visteon, Continental, Panasonic and Aptiv. The abiding theme will be putting customer and vehicle data to work to enhance the driving experience with content and safety with sensor integration.

Expect in-dash account and privacy management capabilities and advanced digital assistants enabling hands-free interactions with vehicle resources. With the growing variety of vehicle connections including satellite, cellular and connected mobile devices the goal will be to integrate these connections into a holistic information and entertainment management and driving experience.

The core message of the Samsung/Harman digital cockpit is comprehensive integration of one’s home, car and mobile life. The thrust from SiriusXM is an attempt to deliver something similar, but only for content delivery purposes.
MasterCard, Visa and other payment players will be vying at CES 2019 to dominate the emerging eco-system of vehicle-centric purchases from tolls and parking to fuel and movie tickets. The wallet on wheels phenomenon will come to life in Las Vegas next week in a variety of manifestations from multiple suppliers.

The monetization of vehicle data will also be a massive theme with companies lining up to meet the challenge including Otonomo, Wejo, The Floow, High Mobility, SmartCar, Harman (Ignite) and many others. OEMs will support these efforts with open APIs enabling data access and SDKs for application development.

It will be interesting to see what new dashboard experiences have a lingering impact beyond the Las Vegas Convention Center this year. One hint: Don’t miss Honda’s updated DreamDrive demo in North Hall. 😉

Roger C. Lanctot is Director, Automotive Connected Mobility in the Global Automotive Practice at Strategy Analytics. Roger will keynote the Consumer Telematics Show on January 7 at Planet Hollywood. More details about Strategy Analytics can be found here:https://www.strategyanalytics.com/access-services/automotive#.VuGdXfkrKUk


CES 2019 Robotaxis vs. Micro Transit

CES 2019 Robotaxis vs. Micro Transit
by Roger C. Lanctot on 01-06-2019 at 7:00 am

Attendees of CES 2019 arriving at Las Vegas McCarran International Airport next week will have four options for getting to their hotels: a shuttle offering two rides for the price of one (out and back for about $15); a taxi offering one ride for the price of two (about $30), a Lyft or Uber offering one ride for the price of one ride (about $15), or a rental car.

Las Vegas is a microcosm of the transportation challenges facing cities all over the world with the addition of tourists and inebriated pedestrians and minus rail-based public transit. As such it is no stranger to traffic jams – especially during major events. So the local authorities are doing their best to test new innovative solutions to optimize travel on the available roads.

Micro transit is a popular option in the area, with airport shuttles representing a prominent example. Most cities are vying to pry drivers out of individual vehicles and into shared ride, multi-passenger minibuses and shuttles.

Las Vegas has a wide variety of large and small buses plying the strip and downtown. The CES show will bring its own subset of inter-venue busses supplied by the organizers along with various limousines, vans and shuttles operated by attendees and exhibitors.

Las Vegas even has driverless shuttles from Navya operating downtown, albeit at very low speeds. Most recently added to the mix have been 35 driverless Lyft vehicles enabled by technology provided by Aptiv. (The picture – above – was taken from the backseat of a Lyft-Aptiv “driverless” car.)

The Lyft-Aptiv effort is an example of the impending arrival of “robotaxis,” an expression popularized by Nvidia at its GTC event in Munich two years ago. At the time, Nvidia was touting its dominance of the world of robotaxis noting that of the then 225 partners developing autonomous driving technology on the Nvidia Drive PX platform, 25 were robotaxis.

Notably, Uber was and is one of those Drive PX partners. In 2018, an inattentive Uber safety driver and a flawed Uber autonomous set-up resulted in a fatal crash in Phoenix. So 2018 ended with Uber sputtering to restart its robotaxi efforts – while headlines appeared in newspapers across the country describing Phoenix residents hurling rocks at driverless vehicles…from Waymo!

The Lyft-Aptiv “driverless” effort prominently features two drivers – a safety driver and co-pilot – and you can easily “hail” one of these vehicles using the Lyft app after opting in to accept the “driverless” option. Ironically, the driverless Lyft-Aptiv has two “drivers.”

Don’t expect to get a Lyft-Aptiv vehicle running from the airport to downtown or the strip and back. The Lyft-Aptiv test vehicles are only operating within the city – presumably to better apprehend urban vehicle-human-infrastructure interactions. In fact, the vehicles will not operate on private property – i.e. the driveways etc. surrounding hotels – so the “driverless” experience is actually quite limited.

Still the presence of these “driverless” vehicles in Las Vegas highlights the tension between adding more individual passenger transportation alternatives vs. truly shared, multi-passenger propositions. There are many options in Las Vegas.

The Deuce and the Monorail are just two examples of multi-passenger transportation options that operate daily. The Deuce bus on the strip stops at every casino, but only a small proportion of CES attendees are likely to use the bus or are even aware it exists. Fares are $6 for a two-hour pass, $8 for a 24-hour pass and $20 for a three-day pass. The Monorail is $5 for a single ticket, $13 for a 24-hour pass and $29 for a three-day pass.

(For those of you renting cars in Las Vegas there may be some surprises. You can still drink for free in Las Vegas IF you are gambling – and you can still smoke in the casinos – but a free parking spot is becoming increasingly rare.)

Interesting and promising though robotaxis may be, the more immediate opportunity in 2019 lies in micro transit and the market participants are lining up. Micro transit leaders include Scoop, Chariot, Ridecell, Vulog, Bestmile, Moia, May Mobility and many others.

For cities, the goal is clear: more passengers inside fewer vehicles. Las Vegas is the perfect example of circumstances running in the opposite direction: more individual passengers in more vehicles.

For years, Las Vegas cab drivers would crab and complain about the growing number of taxi medallions authorized by the city making it that much more difficult for cabbies to make a living. Then along came Uber and Lyft and now it seems that everyone is a cab driver.

The democratization of professional driving contributes to the dubious quality of Vegas driving – but business is booming. There’s so much business to go around that cab drivers don’t even bother complaining.

Still, look for micro transit to take a bigger bite out of transportation in 2019. Your first glimpse of this emerging new reality will be on display at CES 2019 in Las Vegas. See you there.

Roger C. Lanctot is Director, Automotive Connected Mobility in the Global Automotive Practice at Strategy Analytics. Roger will keynote the Consumer Telematics Show on January 7 at Planet Hollywood. More details about Strategy Analytics can be found here:

https://www.strategyanalytics.com/access-services/automotive#.VuGdXfkrKUk


2018 Semiconductor Year in Review

2018 Semiconductor Year in Review
by Scotten Jones on 01-04-2019 at 12:00 pm

Strong Overall Market Growth but a Slowdown Looms
After six years of single digit percentage growth in the overall semiconductor market, 2017 saw almost 22% growth and 2018 year-to-date is up roughly 17% (based on numbers published by the world semiconductor trade statistics). The big growth driver the last two years has been surging memory prices driven by high bit demand and tight supply. With additional memory capacity coming on-line, memory supply is expected to ease in 2019 removing the biggest driver of growth. Depending on whose forecast you believe the overall semiconductor market for 2019 may show single digit percentage growth or a single digit percentage decline.

Leading Edge Logic Down to Three Companies
Entering 2018 three foundries; GLOBALFOUNDRIES (GF), Samsung and TSMC were all pursuing 7nm processes and Intel was pursuing 10nm (with density similar to foundry 7nm processes). Around mid-year GF announced a “pivot” leaving only three companies pursuing the leading edge. With Intel now rumored to be exiting the foundry business there are only two foundry sources of leading-edge logic. With the exit of GF from the leading-edge, Samsung is reportedly seeing a significant increase in requests for their 7nm PDK from companies concerned about being sole sourced at TSMC.

Process Delays at Intel
In 2007 Intel introduced their 45nm process, the world’s first production process with high-K metal gates (HKMG), In 2009 Intel introduced 32nm and then in 2011 their 22nm process, the world’s first production FinFET process. 14nm was originally expected in 2013 but didn’t ramp until 2014 due to yield issues. After the 14nm delay expectations for intel reset to a 3-year cadence and 10nm was expected in 2017. Intel did ship a few 10nm parts at the end of 2017, but production is now expected to be late 2019 once again due to yield issues. Intel’s 10nm has slightly denser logic than the first-generation foundry 7nm processes and Intel is paying the price for the aggressive shrink they attempted. Both Samsung and TSMC went from 16nm/14nm to 10nm and then 7nm while Intel went from 14nm to their “10nm” process in a single step, a 2.7x density increase. There has been a lot of speculation that in order to fix the 10nm yield issues Intel will relax the density specifications, I continue to believe the process that is due to ramp up next year will have the same density previously announced (this is also what Intel is saying).

Intel is now reportedly exiting the custom foundry business. Frankly I never took Intel seriously in foundry, they have always introduced their microprocessor processes a year or more before they offered a foundry version at the same node, if they were serious about foundry the foundry process would have come out at the same time. I do not however see Intel abandoning their own internal manufacturing as some have speculated. Intel has started equipping their moth-balled Fab 42 as the lead 7nm production fab and they recently announced fab expansions in Oregon, Israel and Ireland.

Intel is currently working on 7nm due in 2020. Intel 7nm is targeted as a 2.4x shrink from their 10nm process. Based on the announcements and rumors surrounding Samsung’s 5nm process due in 2019, 4nm process in 2020 and 3nm process in 2021 and TSMC’s 5nm process due in 2019 and 3nm process forecast for around 2021, these processes will be relatively modest shrinks and we expect that if Intel achieves the target shrink their 7nm process will be as dense or denser than the foundry 3nm processes. The question is can they hit their 2020 target. Intel has commented on a conference call that they believe by introducing EUV at 7nm they think the 2.4x shrink is achievable. My concern is a 2.4x shrink will be really pushing a lot of device limits and I would not be surprised to see 7nm delayed. Even if Intel is delayed to 2021 or even 2022 they will once again have competitive density with the foundries.

A lot of people resent Intel for their many years of process leadership and perceived arrogance. Lost in this resentment is an appreciation of all the technology development Intel has driven that have become standard in the industry. I personally am concerned that Intel losing their way at the leading edge could leave a technology leadership void and I am not convinced either Samsung or TSMC are prepared to take on the role of industry technology driver.

EUV Entering Production
Samsung’s 7nm process with an estimated 7 EUV masks entered “production” mid-year and is expected to ramp up over the course of 2019. We estimate Samsung is using an average dose of 50mJ/Cm[SUP]2[/SUP] and they have announced they are not using a pellicle and achieving 1,500 wafer per day. TSMC is expected to ramp their 7FFP process with an estimated 6 EUV masks in 2019. Reports out of TSMC are that this process is ready to go. Both Samsung and TSMC are expected to enter risk production with 5nm processes in 2019 with 11 to 14 EUV masks. There is still a lot of work to do on EUV, photoresist will likely need to transition from the current chemically amplified resists (CAR) to inorganic resists, pellicles are needed, further throughput improvements and a greater understanding and mitigation of stochastics issues, but the era of EUV has clearly begun.

3D NAND Growth
Since 2014 when Samsung introduced 24-layer 3D NAND to production, we have seen 32, 48 and 64 layers enter production with 96-layers currently ramping. 3D NAND is delivering on Moore’s law with increased density and bit cost reduction. The rate of density improvement and bit cost reduction has slowed from the peak 2D NAND years but is continuing and there is a path for continued improvement into the mid to late 2020s. 2018 saw 3D NAND bit shipments exceed 2D NAND bit shipments and by 2020 some forecasters expect 3D NAND to represent 90% of all NAND bits shipped. We expect to see 128-layer 3D NAND in late 2019 or early 2020 and with string stacking there is a path all the way to 512-layers. We do see issues with bit cost beyond 384-layers with our current forecast showing an increase in bit cost beyond that number of layers, but 3D NAND offers a scaling path for many more years.

DRAM Scaling Slows
Of the three main semiconductor product groups: DRAM, Logic and, NAND, DRAM is facing the most difficult scaling path. DRAM capacitor scaling has hit a wall. DRAM capacitors must achieve an acceptable capacitance for bit retention. The capacitance depends on film thickness, film k value and capacitor area. Capacitor area has been increased by going to 3D capacitor structures, but the height of the current cylinder structures is at the mechanical limit for stability. Film thickness has been reduced as much as possible within leakage constraints. There are many options for higher k films, but leakage issues have to-date limited the options. DRAM scaling has recently focused on improving the density and performance of the peripheral circuitry. Today FinFETs and HKMG are on the horizon for further DRAM periphery improvements. DRAM capacitor – capacitance values have also been reduced to values undreamed of a few year ago. At IEDM this year Imec presented work on a new higher-k dielectric material that shows promise to break the capacitor scaling bottleneck. The new Strontium Titanate based material offers a higher-k value with acceptable leakage if the film is made thick enough. The thicker film would require a change from the current cylinder capacitor structure to a pillar structure to accommodate the increased thickness, but the potential is there for increased capacitance in the same area. This is the kind of breakthrough needed for DRAM scaling to get back on track. I plan to write more about this technology in the near future.

Conclusion
In spite of slower growth expected for 2019 the industry continues to move forward on technology scaling across all three major product segments. The long term outlook for the semiconductor market and underlying technologies remains strong.


Apple as Apex of chip industry portends weaker 2019

Apple as Apex of chip industry portends weaker 2019
by Robert Maire on 01-04-2019 at 7:00 am

On the first day of trading in the new year Apple just announced, after the close, that revenues will be lower than previously expected coming in at $84B versus the expected range of $89B to $93B and analyst estimates of the current quarter at $91.5B. Ugly….. The blame was laid squarely on China as slowing sales and trade tensions took a their toll. This is down roughly 7% from where the company thought revenues would be just 60 days ago. A bit of an embarrassment….

We have been talking for a long time about the China risk in tech and pointed out that companies in China were paying employees to buy smart phones from Chinese companies rather than Apple due to the tensions between the two countries.

This should come as little surprise as things have been slowing for a while and the Santa Claus “pop” in the stocks had no basis in reality, just wishful thinking (which didn’t last long…).

The real problem is that Apple is the driver of the vast majority of the semiconductor ecosystem and the impact of the Apple China slowdown hitting the already reeling chip industry will only exacerbate the problem.

Apple is the primary driver of TSMC and the bleeding edge of Moore’s law as TSMC follows Apple’s yearly processor demands. Obviously communications chips as well as memory, both DRAM and NAND will be negatively impacted.

As the de facto Moore’s law driver and one of the biggest consumers of chips Apple is the at the Apex of the semiconductor food chain.

Its likely that the trickle down of Apple’s China Chop could be worse for Apple’s suppliers and the Chip industry than for Apple itself.

Some investors and analysts had been suggesting a quick bounce back from this cyclical downturn but we have remained concerned over Chinese “cloud” hanging over the industry. While not a full blown hurricane from a trade war we are none the less seeing the weather worsen quickly.

The Apple news will not only drive tech stocks and the broader market down but will also make it that much harder and longer for the industry to recover. For those hoping that trade negotiations will result in success in 90 days, we wouldn’t hold your breath. Even if we do get some type of a deal that leaders can brag about, much of the damage has already been done as Apple sales will likely never recover to prior rates in China now that the company has been tarnished as the face of American tech dominance to be punished. The governments can sign whatever deal they want but getting Chinese buyers fired up again for Apple, will not be as easy as a signature.

Very long trickle down impact
The trickle down impact list is too long to enumerate here but is pretty obvious. We are most concerned about the memory portion of the chip industry as it is hyper sensitive to the delicate balance between supply and demand and a whole lot of demand just went away. Memory pricing tends to be non-linear as small imbalances can cause large swings and the memory market tends to trade like a commodity market.

On the other end of the spectrum, we don’t think that the slow down will change the cadence of new processors and technology at the bleeding edge of Moore’s law that Apple drives. Apple will still expect and demand that TSMC keep up its pace and spending so that it can roll out an ever faster Iphone every fall. The only difference is that TSMC will make slightly fewer chips but probably needs all the same new tools to keep up.

Communications chips are somewhere in the middle where technology improvements needed to get to 5G probably overwhelm near term market softness as all participants will keep their foot on the gas to get a slice of the 5G pie (just at a lower volume….). Intel is obviously impacted given their exposure to Apple.

Memory could be bad for all of 2019….
On Christmas day there was a report out of Korea that Samsung was looking at further cuts in their memory fab plans. This Apple news will likely make them cut their plans even faster than before.

Further Samsung Memory Cuts

LRCX and AMAT will be hit harder than KLAC & ASML
Given the huge memory and Samsung exposure of Lam and to a slightly lesser extent Applied, they will bear the brunt of further slowing of the memory industry caused by Apple.

In general, equipment, and those companies that make equipment more related to capacity rather than technology will bear the brunt of the trickle down.

KLA and ASML are more tuned to Moore’s Law and logic devices and less exposed to memory which has already been hard hit.

To be clear, everyone in the semiconductor ecosystem will be hurt, just some more than others

Micron, the stock, is still very cheap, and getting cheaper
Perhaps Micron saw the writing on the wall better than Apple did and put the brakes on spending and expectations a bit earlier. On a relative basis the stock is very cheap but the news is very bad.
We want to be buyers at these levels but catching falling spears is not our sport…..

Equipment stocks
We have been negative on the stocks for a while and we think LRCX could test our $125 target and AMAT could easily test $30 again.

We don’t see a lot of positive data points in the near term and its going to be very hard if not impossible for semiconductor companies to fight the tape and put out positive expectations on their quarterly calls coming up in a few weeks especially in light of this negative Apple news and pronouncements on China.

On the other hand there is also not a lot more negative news other than the failure of trade negotiations and imposition of more tariffs leading to a bigger trade war…..then it would be a nuclear winter for all tech stocks and the overall market, not just the Apple food chain


Disturbances in the AI Force

Disturbances in the AI Force
by Bernard Murphy on 01-03-2019 at 7:00 am

In the normal evolution of specialized hardware IP functions, initial implementations start in academic research or R&D in big semiconductor companies, motivating new ventures specializing in functions of that type, who then either build critical mass to make it as a chip or IP supplier (such as Mobileye – intially) or get sucked into a larger chip or IP supplier (such as Intel or ARM or Synopsys). That was where hardware functions ultimately settled, and many still do.

But recently the gravitational pull of mega-companies has distorted this normally straightforward evolution. In cloud services this list includes Amazon, Microsoft, Baidu and others. In smartphones you have Samsung, Huawei and Apple – yep, Huawei is ahead of Apple in smartphone shipments and is gunning to be #1. These companies, neither semiconductor nor IP, are big enough to do whatever they want to grab market share. What they do to further their goals in competition with the other giants can have major impact on the evolution path for IP suppliers.

Talking to Kurt Shuler, VP Marketing at Arteris IP, I got some insight into how this is changing for AI IP. Arteris IP started working with Cambricon, a Beijing-based startup in fabless AI IP/devices, some time ago. Based on that work Arteris IP built the FlexNoc AI package I wrote about recently. Cambricon is a very interesting company for a number of reasons. One is that they took one of those “gee, why didn’t we think of that?” approaches to designing a platform for neural net (NN) implementations. They developed an optimized instruction set architecture (ISA) based on analysis of multiple NN benchmarks. Then they leveraged this into a design win with Huawei/HiSilicon. This company is attracting attention; including their current series B round, they have raised $200M to date.

The deal with Huawei/HiSilicon led to the IP appearing in the Huawei Kirin 970 smartphone chipset. But Huawei/HiSilicon decided to build their own neural processing unit for the Kirin 980, now in production (also apparently the first 7nm product in production). In other words, this piece of technology was so important to Huawei, they decided to ditch their IP supplier and make their own. Weep not for Cambricon though. They’re already on their next rev and squarely targeting the datacenter AI training applications for which NVIDIA is so well known.

On the cloud side, consider Baidu who are effectively the Google of China. Just like Google, they have also been working intensively on AI, for many of the same reasons such as image search and autonomous driving but also for some reasons closer to Chinese government interests such as intelligent video surveillance. Baidu started in AI working with FPGAs and (apparently) licensing IP. More recently they too developed their own AI chip, Kunlun, in 14nm and seem set to continue on this path.

As a reminder, these high-end AI systems depend on highly custom 2D-architectures of many NN-dedicated processors connected in specialized configurations such as grids or tori, with memories/caches embedded within this structure, along with other distributed services to accelerate common functions like weight updates. In these architectures, the network (NoC) connecting all of these functions becomes critical to meeting performance and other goals, which is why Arteris IP is so involved with these companies.

Another interesting aspect of the Baidu direction is that they are targeting their AI devices and corresponding software to a pretty wide range of applications. One application is certainly NN training in the datacenter, potentially replacing NVIDIA and a counter to the Google TPU. A recurring theme and perhaps a wakeup call for suppliers who thought they had a lock on sockets. But they are also planning use for inference in the datacenter, a new one on me. Apparently, a lot of this is still happening in the datacenter despite enthusiasm for moving AI to the edge, perhaps especially for IoT devices in China where IoT is taking off arguably faster than anywhere else. And Baidu have big aspirations for automotive and home automation. Which means they want an architecture they can scale across this range. Reminds me of what NXP is doing with their eIQ software.

So more big companies investing in their own AI hardware, for very logical reasons. They feel they have to manage the architecture to meet their own plans across a diverse range of applications. It also can’t have escaped your attention that virtually every company I have talked about here is Chinese. A lot of money is going into AI in China, internally in big companies and from venture funds. Another company in this class is Lynxi, also targeting an architecture for both training and inferencing in the datacenter. Lynxi are apparently are backed by serious funding though details seem difficult to find.

Overall, more big companies are building their own AI chips and more small companies are popping up in this area. And a lot more of this activity is visible in China. A disturbance in the force indeed. Arteris IP is closely involved with many of these companies, from Cambricon to Huawei/HiSilicon to Baidu to emerging companies like Lynxi, offering their network on chip (NoC) solutions with the AI package allowing for architecture tuning to the special needs of high-end NN designs. Check it out HERE.


Samsung vs TSMC 7nm Update

Samsung vs TSMC 7nm Update
by Daniel Nenni on 01-02-2019 at 7:00 am

The semiconductor foundry business has gone through a dynamic transformation over the last 30 years. In the beginning the foundries were several process nodes behind the IDMs with little hope of catching up. Today the foundries are leading the process development race at 10nm – 7nm, and will continue to do so, absolutely.

If you look at the foundry landscape, TSMC has the advantage because they are TSMC, the trusted foundry partner with the most mature and complete ecosystem bar none. TSMC is also a process technology leader and fierce competitor.

The market for Samsung Foundry as I see it is three-fold:

  • They are not TSMC. Capacity is not an issue with Samsung and it is always good to have foundry options. TSMC and Samsung are the only two leading edge foundries left so this is a much bigger point than most imagine.
  • Technology. Leading edge fabless companies look for the best technology that will also meet their time to market requirements. Samsung was ahead of TSMC at 14nm and they did quite well at that node. At 10nm and 7nm Samsung was a bit behind TSMC but Samsung 7nm had EUV before TSMC so some fabless companies are now leading with Samsung.
  • Pricing. Samsung has the best wafer pricing the industry has ever seen. Being the largest memory manufacturer does have its advantages and wafer pricing is one of them.To catch up with the latest on foundry process technology I talked to Scotten Jones, internationally recognized semiconductor expert and founder of IC Knowledge, a technology consulting company that models the economics of semiconductors. Scott has been writing for SemiWiki since 2014, his blogs are on the IC Knowledge landing page. Here are Scott’s latest thoughts on TSMC versus Samsung at 7nm:
    • Contacted Poly Pitch (CPP) – both TSMC and Samsung claim a CPP of 54nm for 7nm but for both of them I believe their actual CPP for cells is 57nm.
    • Metal 2 pitch (M2P) – Samsung is 36nm and TSMC is 40nm.
    • Tracks – Samsung minimum cell track height is 6.75 and TSMC is 6.0.
    • Diffusion break – TSMC optical process (7FF) is double diffusion break (DDB) and they are reported to be going to single diffusion break (SDB) for their EUV process (7FFP). Samsung 7nm has a 1[SUP]st[/SUP] generation process (I believe this is 7LPE) and it is DDB, they also have a second generation process (I believe this is 7LPP) that is also DDB. At VLSIT this year they talked about a 3[SUP]rd[/SUP] generation process with SDB. It is hard to know what this really is, at 10nm their second generation process was actually their 8nm process so this could be their 5nm process or it could really be a third generation 7nm process.
    • Transistor density – the minimum cell logic density for TSMC 7FF is slightly better than Samsung 7LPE or 7LPP. TSMC EUV 7FFP is slightly better than Samsung “3[SUP]rd[/SUP] generation” 7nm.
    • SRAM cell size – I think the SRAM cell size is the same for all three Samsung generations (I have a number for the 3[SUP]rd[/SUP] generation process) and both TSMC generations (I have a number for 7FF) but I am not positive. Samsung has a slightly smaller SRAM cell.

    According to Scott, overall, the two processes are similar in density with TSMC leading in the ramp-up and likely yield and I agree, absolutely.


Let The AI Benchmark Wars Begin!

Let The AI Benchmark Wars Begin!
by Michael Gschwind on 01-01-2019 at 7:00 am

Why benchmark competition enables breakthrough innovation in AI. Two years ago I inadvertently started a war. And I couldn’t be happier with the outcome. While wars fought on the battle field of human misery and death never have winners, this “war” is different. It is a competition of human ingenuity to create new technologies that will benefit mankind by accelerating innovation underpinning advances in AI solutions to benefit an already massive and still growing worldwide user base.

It all started two years ago, as I was preparing for the launch of “PowerAI”, a new type of software distribution that would take AI research in the form of Neural Network training out of the research labs across the world and in the hand of everyday users looking to create AI-powered solutions. PowerAI was designed to be the “Red Hat” of AI, a software distro that curates a rapidly improving technology on the cusp of greatness to provide stability, continuity and support. To mark the launch, I wanted to create a memorable milestone for the upcoming launch of our PowerAI product.

PowerMLDL” had been making great strides with an agile release cycle for early adopters that would make users forget the oldest, most solid – and staid – computer brand IBM was behind it. I had created the abbreviation MLDL (for Machine Learning and Deep Learning) because “AI” still had the bitter taste of defeat it acquired when “Artificial Intelligence” had been overhyped and ultimately failed to deliver on its promise in the 80s. Then as now, the most promising technology were “Neural Networks”, a computing structure loosely modeled after the human brain as a set of “neurons”, simple highly interconnected computing units.

But much had changed since Neural Networks and with them the term “AI” had fallen in disrepute: advances in computer hardware and the needs to process a veritable data deluge created by an ever more connected world answered both the “how” and “why” for rebooting “Artificial Intelligence”. And, marketing opined, the name AI was quickly rehabilitating itself along with the technical field.

As we stood to launch our PowerAI distro for Artificial Intelligence together with IBM’s first accelerated AI server “Minsky” (or, “IBM Power 822LC for HPC” in corporate branding), we needed to capture the imagination of what these new products made possible. The value of the new products was integration, ease of use and speed to solution brought to the technical innovations contributed to open source AI frameworks developed by researchers from many companies.

But how to express this benefit? One day as we were reviewing training times and working with our applied AI research colleagues at the IBM TJ Watson Research Center to improve training times for a range of Watson applications, an idea took hold: with the new server and software, we were on the cusp of training a network to recognize images from the most complete image database (“ImageNet”) available to date in less than two hours.

What if “Alexnet”, the most neural network of the day and winner of a prestigious image recognition contest, could be trained in under an hour? We set out to conquer the one hour time. With a focus on innovation and optimization, Alexnet could be trained in under an hour in late summer, and we published “Deep Learning Training in under an hour” in a blog detailing our results in October 2016.

And so, the AI benchmark war started. At IBM, we had started a project to federate many Minsky servers to train a newer, more complex network in even less time using a technology we called DDL – “Distributed Deep Learning”. But before we could publish our results , Facebook published their own blog about “Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour”.

The Facebook team demonstrated many great ideas, but were not able to release their code to the public. Thus, in another first, PowerAI made Distributed Deep Learning available to a broad user community with even better training performance. Since then, some of the most prestigious companies in technology have added their illustrious names to the growing list of new AI training records: UC Berkeley, Tencent, Sony, and Google, to name but a few.

In the course of this competition, the training time for Alexnet went from 6 hours in 2015 to 4 minutes, and for the much more complex ResNet50 (another winner of the image classification competition) from 29 hours to 2.2 minutes. These advances in training speed are particularly important because they enable AI developers and data scientists to create better solutions – despite many advances, AI and neural networks are by no means a mature technology. Not least because a “constructive theory” of neural networks – that is, how to construct a network to accomplish a well-defined task such as recognizing cancerous tissue from a biopsy sample – has eluded practitioners, and so defining new networks to accomplish a task is as much an act of artisanship as of engineering. Something that requires sketches, tests, trials and errors – and to enable that, speed in testing new ideas by training new networks.

And so this AI benchmark “war” is a war without victims, but many victors – everybody who is benefiting from advances in AI technology, from enhanced face recognition to secure data on your phone, to better recommendations for movies, books and restaurants, to enhanced security and better data management, and assistive technologies for road safety and medical diagnosis.

As AI evolves, many of us have recognized that image recognition has served us well in this competition for creativity and innovation until now, but we need to be more inclusive of the wide raneg of AI application domains, as we propel forward the performance and capabilities of AI solutions. With the recent “MLPerf” initiative to create an industry-wide AI performance benchmark standard, we are creating a better competition to propel human ingenuity even further to advance the boundaries of what is possible with AI.