Tag Archives: Qualcomm

7nm (nanometre) chip shakeup

From time to time I check out the latest on attempts to shrink computer chips. In my July 11, 2014 posting I noted IBM’s announcement about developing a 7nm computer chip and later in my July 15, 2015 posting I noted IBM’s announcement of a working 7nm chip (from a July 9, 2015 IBM news release , “The breakthrough, accomplished in partnership with GLOBALFOUNDRIES and Samsung at SUNY Polytechnic Institute’s Colleges of Nanoscale Science and Engineering (SUNY Poly CNSE), could result in the ability to place more than 20 billion tiny switches — transistors — on the fingernail-sized chips that power everything from smartphones to spacecraft.”

I’m not sure what happened to the IBM/Global Foundries/Samsung partnership but Global Foundries recently announced that it will no longer be working on 7nm chips. From an August 27, 2018 Global Foundries news release,

GLOBALFOUNDRIES [GF] today announced an important step in its transformation, continuing the trajectory launched with the appointment of Tom Caulfield as CEO earlier this year. In line with the strategic direction Caulfield has articulated, GF is reshaping its technology portfolio to intensify its focus on delivering truly differentiated offerings for clients in high-growth markets.

GF is realigning its leading-edge FinFET roadmap to serve the next wave of clients that will adopt the technology in the coming years. The company will shift development resources to make its 14/12nm FinFET platform more relevant to these clients, delivering a range of innovative IP and features including RF, embedded memory, low power and more. To support this transition, GF is putting its 7nm FinFET program on hold indefinitely [emphasis mine] and restructuring its research and development teams to support its enhanced portfolio initiatives. This will require a workforce reduction, however a significant number of top technologists will be redeployed on 14/12nm FinFET derivatives and other differentiated offerings.

I tried to find a definition for FinFet but the reference to a MOSFET and in-gate transistors was too much incomprehensible information packed into a tight space, see the FinFET Wikipedia entry for more, if you dare.

Getting back to the 7nm chip issue, Samuel K. Moore (I don’t think he’s related to the Moore of Moore’s law) wrote an Aug. 28, 2018 posting on the Nanoclast blog (on the IEEE [Institute of Electronics and Electrical Engineers] website) which provides some insight (Note: Links have been removed),

In a major shift in strategy, GlobalFoundries is halting its development of next-generation chipmaking processes. It had planned to move to the so-called 7-nm node, then begin to use extreme-ultraviolet lithography (EUV) to make that process cheaper. From there, it planned to develop even more advanced lithography that would allow for 5- and 3-nanometer nodes. Despite having installed at least one EUV machine at its Fab 8 facility in Malta, N.Y., all those plans are now on indefinite hold, the company announced Monday.

The move leaves only three companies reaching for the highest rungs of the Moore’s Law ladder: Intel, Samsung, and TSMC.

It’s a huge turnabout for GlobalFoundries. …

GlobalFoundries rationale for the move is that there are not enough customers that need bleeding-edge 7-nm processes to make it profitable. “While the leading edge gets most of the headlines, fewer customers can afford the transition to 7 nm and finer geometries,” said Samuel Wang, research vice president at Gartner, in a GlobalFoundries press release.

“The vast majority of today’s fabless [emphasis mine] customers are looking to get more value out of each technology generation to leverage the substantial investments required to design into each technology node,” explained GlobalFoundries CEO Tom Caulfield in a press release. “Essentially, these nodes are transitioning to design platforms serving multiple waves of applications, giving each node greater longevity. This industry dynamic has resulted in fewer fabless clients designing into the outer limits of Moore’s Law. We are shifting our resources and focus by doubling down on our investments in differentiated technologies across our entire portfolio that are most relevant to our clients in growing market segments.”

(The dynamic Caulfield describes is something the U.S. Defense Advanced Research Agency is working to disrupt with its $1.5-billion Electronics Resurgence Initiative. Darpa’s [DARPA] partners are trying to collapse the cost of design and allow older process nodes to keep improving by using 3D technology.)

Fabless manufacturing is where the fabrication is outsourced and the manufacturing company of record is focused on other matters according to the Fabless manufacturing Wikipedia entry.

Roland Moore-Colyer (I don’t think he’s related to Moore of Moore’s law either) has written August 28, 2018 article for theinquirer.net which also explores this latest news from Global Foundries (Note: Links have been removed),

EVER PREPPED A SPREAD for a party to then have less than half the people you were expecting show up? That’s probably how GlobalFoundries [sic] feels at the moment.

The chip manufacturer, which was once part of AMD, had a fabrication process geared up for 7-nanometre chips which its customers – including AMD and Qualcomm – were expected to adopt.

But AMD has confirmed that it’s decided to move its 7nm GPU production to TSMC, and Intel is still stuck trying to make chips based on 10nm fabrication.

Arguably, this could mark a stymieing of innovation and cutting-edge designs for chips in the near future. But with processors like AMD’s Threadripper 2990WX overclocked to run at 6GHz across all its 32 cores, in the real-world PC fans have no need to worry about consumer chips running out of puff anytime soon. µ

That’s all folks.

Maybe that’s not all

Steve Blank in a Sept. 10, 2018 posting on the Nanoclast blog (on the IEEE [Institute of Electrical and Electronics Engineers] website) provides some provocative commentary on the Global Foundries announcement (Note: A link has been removed),

For most of our lives, the idea that computers and technology would get better, faster, and cheaper every year was as assured as the sun rising every morning. The story “GlobalFoundries Halts 7-nm Chip Development”  doesn’t sound like the end of that era, but for you and anyone who uses an electronic device, it most certainly is.

Technology innovation is going to take a different direction.

This story just goes on and on

There was a new development according to a Sept. 12, 2018 posting on the Nanoclast blog by, again, Samuel K. Moore (Note Links have been removed),

At an event today [sept. 12, 2018], Apple executives said that the new iPhone Xs and Xs Max will contain the first smartphone processor to be made using 7 nm manufacturing technology, the most advanced process node. Huawei made the same claim, to less fanfare, late last month and it’s unclear who really deserves the accolades. If anybody does, it’s TSMC, which manufactures both chips.

TSMC went into volume production with 7-nm tech in April, and rival Samsung is moving toward commercial 7-nm production later this year or in early 2019. GlobalFoundries recently abandoned its attempts to develop a 7 nm process, reasoning that the multibillion-dollar investment would never pay for itself. And Intel announced delays in its move to its next manufacturing technology, which it calls a 10-nm node but which may be equivalent to others’ 7-nm technology.

There’s a certain ‘soap opera’ quality to this with all the twists and turns.

Humans can distinguish molecular differences by touch

Yesterday, in my December 18, 2017 post about medieval textiles, I posed the question, “How did medieval artisans create nanoscale and microscale gilding when they couldn’t see it?” I realized afterwards that an answer to that question might be in this December 13, 2017 news item on ScienceDaily,

How sensitive is the human sense of touch? Sensitive enough to feel the difference between surfaces that differ by just a single layer of molecules, a team of researchers at the University of California San Diego has shown.

“This is the greatest tactile sensitivity that has ever been shown in humans,” said Darren Lipomi, a professor of nanoengineering and member of the Center for Wearable Sensors at the UC San Diego Jacobs School of Engineering, who led the interdisciplinary project with V. S. Ramachandran, director of the Center for Brain and Cognition and distinguished professor in the Department of Psychology at UC San Diego.

So perhaps those medieval artisans were able to feel the difference before it could be seen in the textiles they were producing?

Getting back to the matter at hand, a December 13, 2017 University of California at San Diego (UCSD) news release (also on EurekAlert) by Liezel Labios offers more detail about the work,

Humans can easily feel the difference between many everyday surfaces such as glass, metal, wood and plastic. That’s because these surfaces have different textures or draw heat away from the finger at different rates. But UC San Diego researchers wondered, if they kept all these large-scale effects equal and changed only the topmost layer of molecules, could humans still detect the difference using their sense of touch? And if so, how?

Researchers say this fundamental knowledge will be useful for developing electronic skin, prosthetics that can feel, advanced haptic technology for virtual and augmented reality and more.

Unsophisticated haptic technologies exist in the form of rumble packs in video game controllers or smartphones that shake, Lipomi added. “But reproducing realistic tactile sensations is difficult because we don’t yet fully understand the basic ways in which materials interact with the sense of touch.”

“Today’s technologies allow us to see and hear what’s happening, but we can’t feel it,” said Cody Carpenter, a nanoengineering Ph.D. student at UC San Diego and co-first author of the study. “We have state-of-the-art speakers, phones and high-resolution screens that are visually and aurally engaging, but what’s missing is the sense of touch. Adding that ingredient is a driving force behind this work.”

This study is the first to combine materials science and psychophysics to understand how humans perceive touch. “Receptors processing sensations from our skin are phylogenetically the most ancient, but far from being primitive they have had time to evolve extraordinarily subtle strategies for discerning surfaces—whether a lover’s caress or a tickle or the raw tactile feel of metal, wood, paper, etc. This study is one of the first to demonstrate the range of sophistication and exquisite sensitivity of tactile sensations. It paves the way, perhaps, for a whole new approach to tactile psychophysics,” Ramachandran said.

Super-Sensitive Touch

In a paper published in Materials Horizons, UC San Diego researchers tested whether human subjects could distinguish—by dragging or tapping a finger across the surface—between smooth silicon wafers that differed only in their single topmost layer of molecules. One surface was a single oxidized layer made mostly of oxygen atoms. The other was a single Teflon-like layer made of fluorine and carbon atoms. Both surfaces looked identical and felt similar enough that some subjects could not differentiate between them at all.

According to the researchers, human subjects can feel these differences because of a phenomenon known as stick-slip friction, which is the jerking motion that occurs when two objects at rest start to slide against each other. This phenomenon is responsible for the musical notes played by running a wet finger along the rim of a wine glass, the sound of a squeaky door hinge or the noise of a stopping train. In this case, each surface has a different stick-slip frequency due to the identity of the molecules in the topmost layer.

In one test, 15 subjects were tasked with feeling three surfaces and identifying the one surface that differed from the other two. Subjects correctly identified the differences 71 percent of the time.

In another test, subjects were given three different strips of silicon wafer, each strip containing a different sequence of 8 patches of oxidized and Teflon-like surfaces. Each sequence represented an 8-digit string of 0s and 1s, which encoded for a particular letter in the ASCII alphabet. Subjects were asked to “read” these sequences by dragging a finger from one end of the strip to the other and noting which patches in the sequence were the oxidized surfaces and which were the Teflon-like surfaces. In this experiment, 10 out of 11 subjects decoded the bits needed to spell the word “Lab” (with the correct upper and lowercase letters) more than 50 percent of the time. Subjects spent an average of 4.5 minutes to decode each letter.

“A human may be slower than a nanobit per second in terms of reading digital information, but this experiment shows a potentially neat way to do chemical communications using our sense of touch instead of sight,” Lipomi said.

Basic Model of Touch

The researchers also found that these surfaces can be differentiated depending on how fast the finger drags and how much force it applies across the surface. The researchers modeled the touch experiments using a “mock finger,” a finger-like device made of an organic polymer that’s connected by a spring to a force sensor. The mock finger was dragged across the different surfaces using multiple combinations of force and swiping velocity. The researchers plotted the data and found that the surfaces could be distinguished given certain combinations of velocity and force. Meanwhile, other combinations made the surfaces indistinguishable from each other.

“Our results reveal a remarkable human ability to quickly home in on the right combinations of forces and swiping velocities required to feel the difference between these surfaces. They don’t need to reconstruct an entire matrix of data points one by one as we did in our experiments,” Lipomi said.

“It’s also interesting that the mock finger device, which doesn’t have anything resembling the hundreds of nerves in our skin, has just one force sensor and is still able to get the information needed to feel the difference in these surfaces. This tells us it’s not just the mechanoreceptors in the skin, but receptors in the ligaments, knuckles, wrist, elbow and shoulder that could be enabling humans to sense minute differences using touch,” he added.

This work was supported by member companies of the Center for Wearable Sensors at UC San Diego: Samsung, Dexcom, Sabic, Cubic, Qualcomm and Honda.

For those who prefer their news by video,

Here’s a link to and a citation for the paper,

Human ability to discriminate surface chemistry by touch by Cody W. Carpenter, Charles Dhong, Nicholas B. Root, Daniel Rodriquez, Emily E. Abdo, Kyle Skelil, Mohammad A. Alkhadra, Julian Ramírez, Vilayanur S. Ramachandran and Darren J. Lipomi. Mater. Horiz., 2018, Advance Article DOI: 10.1039/C7MH00800G

This paper is open access but you do need to have opened a free account on the website.

Aliens wreak havoc on our personal electronics

The aliens in question are subatomic particles and the havoc they wreak is low-grade according to the scientist who was presenting on the topic at the AAAS (American Association for the Advancement of Science) 2017 Annual Meeting (Feb. 16 – 20, 2017) in Boston, Massachusetts. From a Feb. 17, 2017 news item on ScienceDaily,

You may not realize it but alien subatomic particles raining down from outer space are wreaking low-grade havoc on your smartphones, computers and other personal electronic devices.

When your computer crashes and you get the dreaded blue screen or your smartphone freezes and you have to go through the time-consuming process of a reset, most likely you blame the manufacturer: Microsoft or Apple or Samsung. In many instances, however, these operational failures may be caused by the impact of electrically charged particles generated by cosmic rays that originate outside the solar system.

“This is a really big problem, but it is mostly invisible to the public,” said Bharat Bhuva, professor of electrical engineering at Vanderbilt University, in a presentation on Friday, Feb. 17 at a session titled “Cloudy with a Chance of Solar Flares: Quantifying the Risk of Space Weather” at the annual meeting of the American Association for the Advancement of Science in Boston.

A Feb. 17, 2017 Vanderbilt University news release (also on EurekAlert), which originated the news item, expands on  the theme,

When cosmic rays traveling at fractions of the speed of light strike the Earth’s atmosphere they create cascades of secondary particles including energetic neutrons, muons, pions and alpha particles. Millions of these particles strike your body each second. Despite their numbers, this subatomic torrent is imperceptible and has no known harmful effects on living organisms. However, a fraction of these particles carry enough energy to interfere with the operation of microelectronic circuitry. When they interact with integrated circuits, they may alter individual bits of data stored in memory. This is called a single-event upset or SEU.

Since it is difficult to know when and where these particles will strike and they do not do any physical damage, the malfunctions they cause are very difficult to characterize. As a result, determining the prevalence of SEUs is not easy or straightforward. “When you have a single bit flip, it could have any number of causes. It could be a software bug or a hardware flaw, for example. The only way you can determine that it is a single-event upset is by eliminating all the other possible causes,” Bhuva explained.

There have been a number of incidents that illustrate how serious the problem can be, Bhuva reported. For example, in 2003 in the town of Schaerbeek, Belgium a bit flip in an electronic voting machine added 4,096 extra votes to one candidate. The error was only detected because it gave the candidate more votes than were possible and it was traced to a single bit flip in the machine’s register. In 2008, the avionics system of a Qantus passenger jet flying from Singapore to Perth appeared to suffer from a single-event upset that caused the autopilot to disengage. As a result, the aircraft dove 690 feet in only 23 seconds, injuring about a third of the passengers seriously enough to cause the aircraft to divert to the nearest airstrip. In addition, there have been a number of unexplained glitches in airline computers – some of which experts feel must have been caused by SEUs – that have resulted in cancellation of hundreds of flights resulting in significant economic losses.

An analysis of SEU failure rates for consumer electronic devices performed by Ritesh Mastipuram and Edwin Wee at Cypress Semiconductor on a previous generation of technology shows how prevalent the problem may be. Their results were published in 2004 in Electronic Design News and provided the following estimates:

  • A simple cell phone with 500 kilobytes of memory should only have one potential error every 28 years.
  • A router farm like those used by Internet providers with only 25 gigabytes of memory may experience one potential networking error that interrupts their operation every 17 hours.
  • A person flying in an airplane at 35,000 feet (where radiation levels are considerably higher than they are at sea level) who is working on a laptop with 500 kilobytes of memory may experience one potential error every five hours.

Bhuva is a member of Vanderbilt’s Radiation Effects Research Group, which was established in 1987 and is the largest academic program in the United States that studies the effects of radiation on electronic systems. The group’s primary focus was on military and space applications. Since 2001, the group has also been analyzing radiation effects on consumer electronics in the terrestrial environment. They have studied this phenomenon in the last eight generations of computer chip technology, including the current generation that uses 3D transistors (known as FinFET) that are only 16 nanometers in size. The 16-nanometer study was funded by a group of top microelectronics companies, including Altera, ARM, AMD, Broadcom, Cisco Systems, Marvell, MediaTek, Renesas, Qualcomm, Synopsys, and TSMC

“The semiconductor manufacturers are very concerned about this problem because it is getting more serious as the size of the transistors in computer chips shrink and the power and capacity of our digital systems increase,” Bhuva said. “In addition, microelectronic circuits are everywhere and our society is becoming increasingly dependent on them.”

To determine the rate of SEUs in 16-nanometer chips, the Vanderbilt researchers took samples of the integrated circuits to the Irradiation of Chips and Electronics (ICE) House at Los Alamos National Laboratory. There they exposed them to a neutron beam and analyzed how many SEUs the chips experienced. Experts measure the failure rate of microelectronic circuits in a unit called a FIT, which stands for failure in time. One FIT is one failure per transistor in one billion hours of operation. That may seem infinitesimal but it adds up extremely quickly with billions of transistors in many of our devices and billions of electronic systems in use today (the number of smartphones alone is in the billions). Most electronic components have failure rates measured in 100’s and 1,000’s of FITs.

chart

Trends in single event upset failure rates at the individual transistor, integrated circuit and system or device level for the three most recent manufacturing technologies. (Bharat Bhuva, Radiation Effects Research Group, Vanderbilt University)

“Our study confirms that this is a serious and growing problem,” said Bhuva.“This did not come as a surprise. Through our research on radiation effects on electronic circuits developed for military and space applications, we have been anticipating such effects on electronic systems operating in the terrestrial environment.”

Although the details of the Vanderbilt studies are proprietary, Bhuva described the general trend that they have found in the last three generations of integrated circuit technology: 28-nanometer, 20-nanometer and 16-nanometer.

As transistor sizes have shrunk, they have required less and less electrical charge to represent a logical bit. So the likelihood that one bit will “flip” from 0 to 1 (or 1 to 0) when struck by an energetic particle has been increasing. This has been partially offset by the fact that as the transistors have gotten smaller they have become smaller targets so the rate at which they are struck has decreased.

More significantly, the current generation of 16-nanometer circuits have a 3D architecture that replaced the previous 2D architecture and has proven to be significantly less susceptible to SEUs. Although this improvement has been offset by the increase in the number of transistors in each chip, the failure rate at the chip level has also dropped slightly. However, the increase in the total number of transistors being used in new electronic systems has meant that the SEU failure rate at the device level has continued to rise.

Unfortunately, it is not practical to simply shield microelectronics from these energetic particles. For example, it would take more than 10 feet of concrete to keep a circuit from being zapped by energetic neutrons. However, there are ways to design computer chips to dramatically reduce their vulnerability.

For cases where reliability is absolutely critical, you can simply design the processors in triplicate and have them vote. Bhuva pointed out: “The probability that SEUs will occur in two of the circuits at the same time is vanishingly small. So if two circuits produce the same result it should be correct.” This is the approach that NASA used to maximize the reliability of spacecraft computer systems.

The good news, Bhuva said, is that the aviation, medical equipment, IT, transportation, communications, financial and power industries are all aware of the problem and are taking steps to address it. “It is only the consumer electronics sector that has been lagging behind in addressing this problem.”

The engineer’s bottom line: “This is a major problem for industry and engineers, but it isn’t something that members of the general public need to worry much about.”

That’s fascinating and I hope the consumer electronics industry catches up with this ‘alien invasion’ issue. Finally, the ‘bit flips’ made me think of the 1956 movie ‘Invasion of the Body Snatchers‘.

Robo Brain; a new robot learning project

Having covered the RoboEarth project (a European Union funded ‘internet for robots’ first mentioned here in a Feb. 14, 2011 posting [scroll down about 1/4 of the way] and again in a March 12 2013 posting about the project’s cloud engine, Rapyuta and. most recently in a Jan. 14, 2014 posting), an Aug. 25, 2014 Cornell University news release by Bill Steele (also on EurekAlert with some editorial changes) about the US Robo Brain project immediately caught my attention,

Robo Brain – a large-scale computational system that learns from publicly available Internet resources – is currently downloading and processing about 1 billion images, 120,000 YouTube videos, and 100 million how-to documents and appliance manuals. The information is being translated and stored in a robot-friendly format that robots will be able to draw on when they need it.

The news release spells out why and how researchers have created Robo Brain,

To serve as helpers in our homes, offices and factories, robots will need to understand how the world works and how the humans around them behave. Robotics researchers have been teaching them these things one at a time: How to find your keys, pour a drink, put away dishes, and when not to interrupt two people having a conversation.

This will all come in one package with Robo Brain, a giant repository of knowledge collected from the Internet and stored in a robot-friendly format that robots will be able to draw on when they need it. [emphasis mine]

“Our laptops and cell phones have access to all the information we want. If a robot encounters a situation it hasn’t seen before it can query Robo Brain in the cloud,” explained Ashutosh Saxena, assistant professor of computer science.

Saxena and colleagues at Cornell, Stanford and Brown universities and the University of California, Berkeley, started in July to download about one billion images, 120,000 YouTube videos and 100 million how-to documents and appliance manuals, along with all the training they have already given the various robots in their own laboratories. Robo Brain will process images to pick out the objects in them, and by connecting images and video with text, it will learn to recognize objects and how they are used, along with human language and behavior.

Saxena described the project at the 2014 Robotics: Science and Systems Conference, July 12-16 [2014] in Berkeley.

If a robot sees a coffee mug, it can learn from Robo Brain not only that it’s a coffee mug, but also that liquids can be poured into or out of it, that it can be grasped by the handle, and that it must be carried upright when it is full, as opposed to when it is being carried from the dishwasher to the cupboard.

The system employs what computer scientists call “structured deep learning,” where information is stored in many levels of abstraction. An easy chair is a member of the class of chairs, and going up another level, chairs are furniture. Sitting is something you can do on a chair, but a human can also sit on a stool, a bench or the lawn.

A robot’s computer brain stores what it has learned in a form mathematicians call a Markov model, which can be represented graphically as a set of points connected by lines (formally called nodes and edges). The nodes could represent objects, actions or parts of an image, and each one is assigned a probability – how much you can vary it and still be correct. In searching for knowledge, a robot’s brain makes its own chain and looks for one in the knowledge base that matches within those probability limits.

“The Robo Brain will look like a gigantic, branching graph with abilities for multidimensional queries,” said Aditya Jami, a visiting researcher at Cornell who designed the large-scale database for the brain. It might look something like a chart of relationships between Facebook friends but more on the scale of the Milky Way.

Like a human learner, Robo Brain will have teachers, thanks to crowdsourcing. The Robo Brain website will display things the brain has learned, and visitors will be able to make additions and corrections.

The “robot-friendly format” for information in the European project (RoboEarth) meant machine language but if I understand what’s written in the news release correctly, this project incorporates a mix of machine language and natural (human) language.

This is one of the times the funding sources (US National Science Foundation, two of the armed forces, businesses and a couple of not-for-profit agencies) seem particularly interesting (from the news release),

The project is supported by the National Science Foundation, the Office of Naval Research, the Army Research Office, Google, Microsoft, Qualcomm, the Alfred P. Sloan Foundation and the National Robotics Initiative, whose goal is to advance robotics to help make the United States more competitive in the world economy.

For the curious, here’s a link to the Robo Brain and RoboEarth websites.