Tag Archives: D-Wave Systems

More investment money for Canada’s D-Wave Systems (quantum computing)

A Feb. 2, 2015 news item on Nanotechnology Now features D-Wave Systems (located in the Vancouver region, Canada) and its recent funding bonanza of $28M dollars,

Harris & Harris Group, Inc. (Nasdaq:TINY), an investor in transformative companies enabled by disruptive science, notes the announcement by portfolio company, D-Wave Systems, Inc., that it has closed $29 million (CAD) in funding from a large institutional investor, among others. This funding will be used to accelerate development of D-Wave’s quantum hardware and software and expand the software application ecosystem. This investment brings total funding in D-Wave to $174 million (CAD), with approximately $62 million (CAD) raised in 2014. Harris & Harris Group’s total investment in D-Wave is approximately $5.8 million (USD). D-Wave’s announcement also includes highlights of 2014, a year of strong growth and advancement for D-Wave.

A Jan. 29, 2015 D-Wave news release provides more details about the new investment and D-Wave’s 2014 triumphs,

D-Wave Systems Inc., the world’s first quantum computing company, today announced that it has closed $29 million in funding from a large institutional investor, among others. This funding will be used to accelerate development of D-Wave’s quantum hardware and software and expand the software application ecosystem. This investment brings total funding in D-Wave to $174 million (CAD), with approximately $62 million raised in 2014.

“The investment is a testament to the progress D-Wave continues to make as the leader in quantum computing systems,” said Vern Brownell, CEO of D-Wave. “The funding we received in 2014 will advance our quantum hardware and software development, as well as our work on leading edge applications of our systems. By making quantum computing available to more organizations, we’re driving our goal of finding solutions to the most complex optimization and machine learning applications in national defense, computing, research and finance.”

The funding follows a year of strong growth and advancement for D-Wave. Highlights include:

•    Significant progress made towards the release of the next D-Wave quantum system featuring a 1000 qubit processor, which is currently undergoing testing in D-Wave’s labs.
•    The company’s patent portfolio grew to over 150 issued patents worldwide, with 11 new U.S. patents being granted in 2014, covering aspects of D-Wave’s processor technology, systems and techniques for solving computational problems using D-Wave’s technology.
•    D-Wave Professional Services launched, providing quantum computing experts to collaborate directly with customers, and deliver training classes on the usage and programming of the D-Wave system to a number of national laboratories, businesses and universities.
•    Partnerships were established with DNA-SEQ and 1QBit, companies that are developing quantum software applications in the spheres of medicine and finance, respectively.
•    Research throughout the year continued to validate D-Wave’s work, including a study showing further evidence of quantum entanglement by D-Wave and USC  [University of Southern California] scientists, published in Physical Review X this past May.

Since 2011, some of the most prestigious organizations in the world, including Lockheed Martin, NASA, Google, USC and the Universities Space Research Association (USRA), have partnered with D-Wave to use their quantum computing systems. In 2015, these partners will continue to work with the D-Wave computer, conducting pioneering research in machine learning, optimization, and space exploration.

D-Wave, which already employs over 120 people, plans to expand hiring with the additional funding. Key areas of growth include research, processor and systems development and software engineering.

Harris & Harris Group offers a description of D-Wave which mentions nanotechnology and hosts a couple of explanatory videos,

D-Wave Systems develops an adiabatic quantum computer (QC).

Status
Privately Held

The Market
Electronics – High Performance Computing

The Problem
Traditional or “classical computers” are constrained by the sequential character of data processing that makes the solving of non-polynomial (NP)-hard problems difficult or potentially impossible in reasonable timeframes. These types of computationally intense problems are commonly observed in software verifications, scheduling and logistics planning, integer programming, bioinformatics and financial portfolio optimization.

D-Wave’s Solution
D-Wave develops quantum computers that are capable of processing data quantum mechanical properties of matter. This leverage of quantum mechanics enables the identification of solutions to some non-polynomial (NP)-hard problems in a reasonable timeframe, instead of the exponential time needed for any classical digital computer. D-Wave sold and installed its first quantum computing system to a commercial customer in 2011.

Nanotechnology Factor
To function properly, D-wave processor requires tight control and manipulation of quantum mechanical phenomena. This control and manipulation is achieved by creating integrated circuits based on Josephson Junctions and other superconducting circuitry. By picking superconductors, D-wave managed to combine quantum mechanical behavior with macroscopic dimensions needed for hi-yield design and manufacturing.

It seems D-Wave has made some research and funding strides since I last wrote about the company in a Jan. 19, 2012 posting, although there is no mention of quantum computer sales.

IBM weighs in with plans for a 7nm computer chip

On the heels of Intel’s announcement about a deal utilizing their 14nm low-power manufacturing process and speculations about a 10nm computer chip (my July 9, 2014 posting), IBM makes an announcement about a 7nm chip as per this July 10, 2014 news item on Azonano,

IBM today [July 10, 2014] announced it is investing $3 billion over the next 5 years in two broad research and early stage development programs to push the limits of chip technology needed to meet the emerging demands of cloud computing and Big Data systems. These investments will push IBM’s semiconductor innovations from today’s breakthroughs into the advanced technology leadership required for the future.

A very comprehensive July 10, 2014 news release lays out the company’s plans for this $3B investment representing 10% of IBM’s total research budget,

The first research program is aimed at so-called “7 nanometer and beyond” silicon technology that will address serious physical challenges that are threatening current semiconductor scaling techniques and will impede the ability to manufacture such chips. The second is focused on developing alternative technologies for post-silicon era chips using entirely different approaches, which IBM scientists and other experts say are required because of the physical limitations of silicon based semiconductors.

Cloud and big data applications are placing new challenges on systems, just as the underlying chip technology is facing numerous significant physical scaling limits.  Bandwidth to memory, high speed communication and device power consumption are becoming increasingly challenging and critical.

The teams will comprise IBM Research scientists and engineers from Albany and Yorktown, New York; Almaden, California; and Europe. In particular, IBM will be investing significantly in emerging areas of research that are already underway at IBM such as carbon nanoelectronics, silicon photonics, new memory technologies, and architectures that support quantum and cognitive computing. [emphasis mine]

These teams will focus on providing orders of magnitude improvement in system level performance and energy efficient computing. In addition, IBM will continue to invest in the nanosciences and quantum computing–two areas of fundamental science where IBM has remained a pioneer for over three decades.

7 nanometer technology and beyond

IBM Researchers and other semiconductor experts predict that while challenging, semiconductors show promise to scale from today’s 22 nanometers down to 14 and then 10 nanometers in the next several years.  However, scaling to 7 nanometers and perhaps below, by the end of the decade will require significant investment and innovation in semiconductor architectures as well as invention of new tools and techniques for manufacturing.

“The question is not if we will introduce 7 nanometer technology into manufacturing, but rather how, when, and at what cost?” said John Kelly, senior vice president, IBM Research. “IBM engineers and scientists, along with our partners, are well suited for this challenge and are already working on the materials science and device engineering required to meet the demands of the emerging system requirements for cloud, big data, and cognitive systems. This new investment will ensure that we produce the necessary innovations to meet these challenges.”

“Scaling to 7nm and below is a terrific challenge, calling for deep physics competencies in processing nano materials affinities and characteristics. IBM is one of a very few companies who has repeatedly demonstrated this level of science and engineering expertise,” said Richard Doherty, technology research director, The Envisioneering Group.

Bridge to a “Post-Silicon” Era

Silicon transistors, tiny switches that carry information on a chip, have been made smaller year after year, but they are approaching a point of physical limitation. Their increasingly small dimensions, now reaching the nanoscale, will prohibit any gains in performance due to the nature of silicon and the laws of physics. Within a few more generations, classical scaling and shrinkage will no longer yield the sizable benefits of lower power, lower cost and higher speed processors that the industry has become accustomed to.

With virtually all electronic equipment today built on complementary metal–oxide–semiconductor (CMOS) technology, there is an urgent need for new materials and circuit architecture designs compatible with this engineering process as the technology industry nears physical scalability limits of the silicon transistor.

Beyond 7 nanometers, the challenges dramatically increase, requiring a new kind of material to power systems of the future, and new computing platforms to solve problems that are unsolvable or difficult to solve today. Potential alternatives include new materials such as carbon nanotubes, and non-traditional computational approaches such as neuromorphic computing, cognitive computing, machine learning techniques, and the science behind quantum computing.

As the leader in advanced schemes that point beyond traditional silicon-based computing, IBM holds over 500 patents for technologies that will drive advancements at 7nm and beyond silicon — more than twice the nearest competitor. These continued investments will accelerate the invention and introduction into product development for IBM’s highly differentiated computing systems for cloud, and big data analytics.

Several exploratory research breakthroughs that could lead to major advancements in delivering dramatically smaller, faster and more powerful computer chips, include quantum computing, neurosynaptic computing, silicon photonics, carbon nanotubes, III-V technologies, low power transistors and graphene:

Quantum Computing

The most basic piece of information that a typical computer understands is a bit. Much like a light that can be switched on or off, a bit can have only one of two values: “1” or “0.” Described as superposition, this special property of qubits enables quantum computers to weed through millions of solutions all at once, while desktop PCs would have to consider them one at a time.

IBM is a world leader in superconducting qubit-based quantum computing science and is a pioneer in the field of experimental and theoretical quantum information, fields that are still in the category of fundamental science – but one that, in the long term, may allow the solution of problems that are today either impossible or impractical to solve using conventional machines. The team recently demonstrated the first experimental realization of parity check with three superconducting qubits, an essential building block for one type of quantum computer.

Neurosynaptic Computing

Bringing together nanoscience, neuroscience, and supercomputing, IBM and university partners have developed an end-to-end ecosystem including a novel non-von Neumann architecture, a new programming language, as well as applications. This novel technology allows for computing systems that emulate the brain’s computing efficiency, size and power usage. IBM’s long-term goal is to build a neurosynaptic system with ten billion neurons and a hundred trillion synapses, all while consuming only one kilowatt of power and occupying less than two liters of volume.

Silicon Photonics

IBM has been a pioneer in the area of CMOS integrated silicon photonics for over 12 years, a technology that integrates functions for optical communications on a silicon chip, and the IBM team has recently designed and fabricated the world’s first monolithic silicon photonics based transceiver with wavelength division multiplexing.  Such transceivers will use light to transmit data between different components in a computing system at high data rates, low cost, and in an energetically efficient manner.

Silicon nanophotonics takes advantage of pulses of light for communication rather than traditional copper wiring and provides a super highway for large volumes of data to move at rapid speeds between computer chips in servers, large datacenters, and supercomputers, thus alleviating the limitations of congested data traffic and high-cost traditional interconnects.

Businesses are entering a new era of computing that requires systems to process and analyze, in real-time, huge volumes of information known as Big Data. Silicon nanophotonics technology provides answers to Big Data challenges by seamlessly connecting various parts of large systems, whether few centimeters or few kilometers apart from each other, and move terabytes of data via pulses of light through optical fibers.

III-V technologies

IBM researchers have demonstrated the world’s highest transconductance on a self-aligned III-V channel metal-oxide semiconductor (MOS) field-effect transistors (FETs) device structure that is compatible with CMOS scaling. These materials and structural innovation are expected to pave path for technology scaling at 7nm and beyond.  With more than an order of magnitude higher electron mobility than silicon, integrating III-V materials into CMOS enables higher performance at lower power density, allowing for an extension to power/performance scaling to meet the demands of cloud computing and big data systems.

Carbon Nanotubes

IBM Researchers are working in the area of carbon nanotube (CNT) electronics and exploring whether CNTs can replace silicon beyond the 7 nm node.  As part of its activities for developing carbon nanotube based CMOS VLSI circuits, IBM recently demonstrated — for the first time in the world — 2-way CMOS NAND gates using 50 nm gate length carbon nanotube transistors.

IBM also has demonstrated the capability for purifying carbon nanotubes to 99.99 percent, the highest (verified) purities demonstrated to date, and transistors at 10 nm channel length that show no degradation due to scaling–this is unmatched by any other material system to date.

Carbon nanotubes are single atomic sheets of carbon rolled up into a tube. The carbon nanotubes form the core of a transistor device that will work in a fashion similar to the current silicon transistor, but will be better performing. They could be used to replace the transistors in chips that power data-crunching servers, high performing computers and ultra fast smart phones.

Carbon nanotube transistors can operate as excellent switches at molecular dimensions of less than ten nanometers – the equivalent to 10,000 times thinner than a strand of human hair and less than half the size of the leading silicon technology. Comprehensive modeling of the electronic circuits suggests that about a five to ten times improvement in performance compared to silicon circuits is possible.

Graphene

Graphene is pure carbon in the form of a one atomic layer thick sheet.  It is an excellent conductor of heat and electricity, and it is also remarkably strong and flexible.  Electrons can move in graphene about ten times faster than in commonly used semiconductor materials such as silicon and silicon germanium. Its characteristics offer the possibility to build faster switching transistors than are possible with conventional semiconductors, particularly for applications in the handheld wireless communications business where it will be a more efficient switch than those currently used.

Recently in 2013, IBM demonstrated the world’s first graphene based integrated circuit receiver front end for wireless communications. The circuit consisted of a 2-stage amplifier and a down converter operating at 4.3 GHz.

Next Generation Low Power Transistors

In addition to new materials like CNTs, new architectures and innovative device concepts are required to boost future system performance. Power dissipation is a fundamental challenge for nanoelectronic circuits. To explain the challenge, consider a leaky water faucet — even after closing the valve as far as possible water continues to drip — this is similar to today’s transistor, in that energy is constantly “leaking” or being lost or wasted in the off-state.

A potential alternative to today’s power hungry silicon field effect transistors are so-called steep slope devices. They could operate at much lower voltage and thus dissipate significantly less power. IBM scientists are researching tunnel field effect transistors (TFETs). In this special type of transistors the quantum-mechanical effect of band-to-band tunneling is used to drive the current flow through the transistor. TFETs could achieve a 100-fold power reduction over complementary CMOS transistors, so integrating TFETs with CMOS technology could improve low-power integrated circuits.

Recently, IBM has developed a novel method to integrate III-V nanowires and heterostructures directly on standard silicon substrates and built the first ever InAs/Si tunnel diodes and TFETs using InAs as source and Si as channel with wrap-around gate as steep slope device for low power consumption applications.

“In the next ten years computing hardware systems will be fundamentally different as our scientists and engineers push the limits of semiconductor innovations to explore the post-silicon future,” said Tom Rosamilia, senior vice president, IBM Systems and Technology Group. “IBM Research and Development teams are creating breakthrough innovations that will fuel the next era of computing systems.”

IBM’s historic contributions to silicon and semiconductor innovation include the invention and/or first implementation of: the single cell DRAM, the “Dennard scaling laws” underpinning “Moore’s Law”, chemically amplified photoresists, copper interconnect wiring, Silicon on Insulator, strained engineering, multi core microprocessors, immersion lithography, high speed silicon germanium (SiGe), High-k gate dielectrics, embedded DRAM, 3D chip stacking, and Air gap insulators.

IBM researchers also are credited with initiating the era of nano devices following the Nobel prize winning invention of the scanning tunneling microscope which enabled nano and atomic scale invention and innovation.

IBM will also continue to fund and collaborate with university researchers to explore and develop the future technologies for the semiconductor industry. In particular, IBM will continue to support and fund university research through private-public partnerships such as the NanoElectornics Research Initiative (NRI), and the Semiconductor Advanced Research Network (STARnet), and the Global Research Consortium (GRC) of the Semiconductor Research Corporation.

I highlighted ‘memory systems’ as this brings to mind HP Labs and their major investment in ‘memristive’ technologies noted in my June 26, 2014 posting,

… During a two-hour presentation held a year and a half ago, they laid out how the computer might work, its benefits, and the expectation that about 75 percent of HP Labs personnel would be dedicated to this one project. “At the end, Meg {Meg Whitman, CEO of HP Labs] turned to [Chief Financial Officer] Cathie Lesjak and said, ‘Find them more money,’” says John Sontag, the vice president of systems research at HP, who attended the meeting and is in charge of bringing the Machine to life. “People in Labs see this as a once-in-a-lifetime opportunity.”

The Machine is based on the memristor and other associated technologies.

Getting back to IBM, there’s this analysis of the $3B investment ($600M/year for five years) by Alex Konrad in a July 10, 2014 article for Forbes (Note: A link has been removed),

When IBM … announced a $3 billion commitment to even tinier semiconductor chips that no longer depended on silicon on Wednesday, the big news was that IBM’s putting a lot of money into a future for chips where Moore’s Law no longer applies. But on second glance, the move to spend billions on more experimental ideas like silicon photonics and carbon nanotubes shows that IBM’s finally shifting large portions of its research budget into more ambitious and long-term ideas.

… IBM tells Forbes the $3 billion isn’t additional money being added to its R&D spend, an area where analysts have told Forbes they’d like to see more aggressive cash commitments in the future. IBM will still spend about $6 billion a year on R&D, 6% of revenue. Ten percent of that research budget, however, now has to come from somewhere else to fuel these more ambitious chip projects.

Neal Ungerleider’s July 11, 2014 article for Fast Company focuses on the neuromorphic computing and quantum computing aspects of this $3B initiative (Note: Links have been removed),

The new R&D initiatives fall into two categories: Developing nanotech components for silicon chips for big data and cloud systems, and experimentation with “post-silicon” microchips. This will include research into quantum computers which don’t know binary code, neurosynaptic computers which mimic the behavior of living brains, carbon nanotubes, graphene tools and a variety of other technologies.

IBM’s investment is one of the largest for quantum computing to date; the company is one of the biggest researchers in the field, along with a Canadian company named D-Wave which is partnering with Google and NASA to develop quantum computer systems.

The curious can find D-Wave Systems here. There’s also a January 19, 2012 posting here which discusses the D-Wave’s situation at that time.

Final observation, these are fascinating developments especially for the insight they provide into the worries troubling HP Labs, Intel, and IBM as they jockey for position.

ETA July 14, 2014: Dexter Johnson has a July 11, 2014 posting on his Nanoclast blog (on the IEEE [Institute for Electrical and Electronics Engineers]) about the IBM announcement and which features some responses he received from IBM officials to his queries,

While this may be a matter of fascinating speculation for investors, the impact on nanotechnology development  is going to be significant. To get a better sense of what it all means, I was able to talk to some of the key figures of IBM’s push in nanotechnology research.

I conducted e-mail interviews with Tze-Chiang (T.C.) Chen, vice president science & technology, IBM Fellow at the Thomas J. Watson Research Center and Wilfried Haensch, senior manager, physics and materials for logic and communications, IBM Research.

Silicon versus Nanomaterials

First, I wanted to get a sense for how long IBM envisioned sticking with silicon and when they expected the company would permanently make the move away from CMOS to alternative nanomaterials. Unfortunately, as expected, I didn’t get solid answers, except for them to say that new manufacturing tools and techniques need to be developed now.

He goes on to ask about carbon nanotubes and graphene. Interestingly, IBM does not have a wide range of electronics applications in mind for graphene.  I encourage you to read Dexter’s posting as Dexter got answers to some very astute and pointed questions.

D-Wave Systems, a Vancouver (Canada) area company gets one step closer to quantum computing

It takes a great deal of nerve to found a startup company for any emerging technology; I’m not sure what it takes to found a startup company that produces quantum computers.

D-Wave Systems: the quantum computing company (based in the Vancouver area) recently announced they were able to employ an 84-qubit calculation in a demonstration calculating what Dexter Johnson at the Nanoclast blog for the IEEE (Institute of Electrical and Electronics Engineers) called ‘notoriously difficult’ Ramsey numbers.

Here’s a brief description of the demonstration (excerpted from the Jan. 12, 2012 article by Bob Yirka for phsyorg.com),

In the research at D-Wave, those involved worked to run a just recently discovered quantum algorithm on an actual quantum computer; in this case, to solve for a two-color Ramsey number, R(m,2), where m= 4, 5, 6, 7 and 8, also known as the “Party Problem” because it’s use can be explained by posing a problem experienced by many party planners, i.e. how to invite the minimum number of guests where one group knows a certain number of others, and another group doesn’t, forcing just the right amount of mingling. Because increasing the number of different kinds of guests increases the difficulty of finding the answer, modern computers aren’t able to find R(5,5) much less anything higher. …

Quantum algorithms take advantage of such facilities [ability to take advantage of quantum mechanics capabilities which allow superconducting circuits to recognize 1 or 0 as current traveling in opposite directions or the existence of both states simultaneously] and allow for the execution of “instructions” far faster than conventional computers ever could. In the demonstration by the D-Wave team, the computer solved for a R(8,2) Ramsey number in just 270 milliseconds using 84 qubits, though just 28 of them were used in actual computation as the rest were delegated to correcting errors. Also, for those that are curious, the answer is 8.

While Yirka goes on to applaud the accomplishment, he notes that it may not be very useful. I think that’s always an issue with the early stages of an emerging technology; it may not prove to have any practical applications now or in the future.

Dexter in his Jan. 12, 2012 blog posting about D-Wave Systems and their recent announcement speaks as someone with lengthy experience dealing with emerging technologies (he provides a little history first [I have removed links from the excerpt, please see the posting for those]),

After erring on the side of caution—if not doubt—when IEEE Spectrum [magazine] cited D-Wave Systems as one of its “Big Losers” two years ago,  it seems that there was a reversal of opinion within this publication back in June of last year when Spectrum covered D-Wave’s first big sale of a quantum computer with an article and then a podcast interview of the company’s CTO.

In the job of covering nanotechnology, one develops—sometimes—a bit more hopeful perspective on the potential of emerging technologies. Basic research that may lead to applications such as quantum computers get more easily pushed up in the development cycle than perhaps they should. So, I have been following the developments of D-Wave for at least the last seven years with a bit more credence than Spectrum had offered the company earlier.

While it may seem that D-Wave is on irreversible upward technological slope, one problem indicated … is that capital may be beginning to dry up.

If so, it would seem almost ironic that after years of not selling anything and attracting a lot of capital, D-Wave would make a $10-million sale and then not be able to get any more funding.

Here’s an excerpt from an interview that Brian Wang had with Geordie Rose, D-Wave’s Chief Technical Officer, for The Next Big Future blog (mentioned in Dexter’s piece) which brings the conundrum Dexter notes into high relief (from Wang’s Dec. 29, 2011 post),

The next 18 months will be a critical period for Dwave systems [sic]. Raising private money has become far more difficult in the current economic conditions. If Dwave were profitable, then they could IPO. If Dwave were not able to become profitable and IPO and could not raise private capital, then there would be the risk of having to shutdown.

According to Wang’s post, D-Wave managed the feat with the Ramsey number two years ago. There was no mention of what they are currently managing to do with their quantum computer.

This is the piece I mentioned yesterday (Jan. 18, 2012) in my posting about the recently released report, Science and Engineering Indicators 2012, from the US National Science Board (NSB) in the context of the government initiative, Startup America, and what I thought was a failure to address the issue of a startup trying to become profitable.

ETA Jan. 22, 2012: Dexter Johnson, Nanoclast blog at the IEEE (Institute of Electrical and Electronics Engineers) mentions the problem in a different context of a recent US initiative to support startup companies through a public/private partnership consortium called the Advanced Manufacturing Partnership (AMP), from his Jan. 20, 2012 posting,

My concern is that a small company that has spun itself out from a university, developed some advanced prototypes, lined up their market, and picked their management group still need by some estimates somewhere in the neighborhood of $10 to $30 million to scale up to being an industrial manufacturer of a product.

Dexter’s concern is that AMP funds available for disbursement will only support a limited number of companies as they scale up.

This contrasts with the Canadian situation where it almost none of our smaller companies can get sufficient funds to scale up when they most need it, e.g., D-Wave System’s current situation.