Supercomputing Vet Champions Quantum Cause

By Nicole Hemsoth

May 13, 2013

Update: D-Wave system coming from Google and NASA … Read More

Supercomputing veteran Bo Ewald has been neck-deep in bleeding edge system development since his twelve-year stint at Cray Research back in the mid-1980s, which was followed by his tenure at large organizations like SGI and startups, including Scale Eight Corporation and Linux Networx.

As we reported earlier this month, Ewald is stepping into yet another new role, this time at the helm of the first quantum computing company, D-Wave Systems. During our recent conversation, Ewald confirmed his belief that quantum computers will be at the heart of a new wave of computing—at least for a certain set of specific optimization, machine learning and pattern recognition problems.

“This is the early days, almost like when the first Cray 1 or Thinking Machines systems came out,” Ewald reminisced. The same skepticism, scientific and business practicality questions, and the same promise exists, he argues.

D-Wave has been in development for 14 years, and has finally arrived at a commercialization opportunity to pitch from its new office in Palo Alto. With a recognizable name like Ewald front and center, it’s clear the company sees opportunities outside of its one public customer, Lockheed Martin. Ewald said he researched heavily to validate the commercial viability and will lead D-Wave’s charge into defense and intelligence, research, and other potential markets. The catch, of course, is that organizations need to have a spare $10 million or more and the right physics and math pros to tap into the programmatic possibilities.

Like the historical systems mentioned above, the company’s flagship system, the D-Wave One, was greeted with equal parts intense skepticism and excitement. With some highly publicized demos and a customer case under their belt, D-Wave thinks it can find a solid market for its 128-qubit processor-based technology, which comes wrapped in its own cryogenic and quantum-balanced unit pictured left.

The company will face a lengthy battle against perception that these quantum computers are fringe or merely experimental. However, some researchers, including Dr. Catherine McGeoch, Beitzel Professor in the Computer Science department at Amherst College, are validating performance claims. For a particular range of applications, quantum vastly outpaced conventional computing. And their work at the USC-Lockheed Martin Center for Quantum Computing continues to offer some serious credibility for, again, a certain class of optimization problems.

As with all early-stage innovations in computer science, there is a major programming and software ecosystem gap. Ewald says this is really no different than what happened with GPUs. He argues that if one thinks about the code and partitioning problems that were present with those accelerators before the software tooling was there in spades, the same story will play out. At this point, mathematicians and physicists can construct their problems numerically using the handful of tools at their disposal and then map them onto the quantum machine.

“We’re on the edge of something revolutionary,” he explained. “This is far different than traditional scientific computing and high performance computing, which is numerically intensive—it’s about crunching a lot of numbers.”

For a range of optimization problems, however, where calculating using the standard set of ones and zeros results in incredibly slow and complex equations, quantum computing relies on “mapping an optimization problem onto the quantum computer so it can instantaneously, once it reaches the quantum state, give you a better solution than the one you started with. With multiple iterations, it will arrive at the best possible answer.”

To put optimization problems into a “normal” context, imagine the following, very common scenario. There is a massive snowstorm in Chicago, which has caused grounding of an unprecedented number of flights. Airlines need to be able to quickly figure out the very best possible solution to moving planes and crews around to adapt. A few iterations on the D-Wave One, says Ewald, and there it is.

Sounds almost too good to be true. Well, there are some catches—the simplest to see is the mere complexity of the quantum process. Further, there’s the programming for these select optimization, machine learning, and pattern recognition problems.

Take a look at the photo on the left to see the inner workings of one D-Wave’s deep freeze boxes. Outside of using atoms rather than bits to solve some of the most perplexing problems in computer science, there are other elements that make D-Wave’s technology noteworthy. While Ewald couldn’t discuss details, he said the real challenge that all the years of R&D have been tackling lies in getting the qubits—the quantum bits—to engage in a way where they become entangled. At this point, the system will move to a lower energy state but there are tough hurdles to create those conditions.

The qubits need to exist at near absolute zero in terms of temperature, vibration and magnetism must be eliminated, and it must operate in a perfect vacuum. That’s a tall order, but Ewald said that the science is there and the applications are real. D-Wave has managed to create this environment to the point where they can get up to 500 qubits into a quantum state.

But theory aside, who will be installing a multi-million dollar ($10 million and up) D-Wave One in the next few years, especially at a time of crunched budgets?  Perhaps the best advertising mechanism the company has lies in its work with Lockheed Martin.  While they haven’t been overt about what problems they’re using their D-Wave setup for, the USC-Lockheed Martin Center for Quantum Computing has been very vocal about their belief in the future of quantum computing.

Lockheed took care to stress the importance of optimization problem solving–finding the best possible answer in a sea of possible answers–which means that’s where their interests likely lie. Government, intelligence and industrial uses remains unclear, but Ewald says that new uses and use cases for these systems will emerge in all areas typically reserved for HPC, including financial services, oil and gas, life sciences–the usual suspects.

“This type of computer is not intended for surfing the internet, but it does solve this narrow but important type of problem really, really fast,” said Dr. Catherine McGeoch. “There are degrees of what it can do. If you want it to solve the exact problem it’s built to solve, at the problem sizes I tested, it’s thousands of times faster than anything I’m aware of. If you want it to solve more general problems of that size, I would say it competes – it does as well as some of the best things I’ve looked at. At this point it’s merely above average but shows a promising scaling trajectory.”

For now, D-Wave stands alone in an emerging market, in much the same way Cray was the monolith at the beginning of the era it kicked off. Ewald is in the unique position of having been at the forefront of one disruptive event in technology, while rounding out his long career leading another such transition.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

China’s TianHe-2A will Use Proprietary Accelerator and Boast 94 Petaflops Peak

September 25, 2017

The details of China’s upgrade to TianHe-2 (MilkyWay-2) – now TianHe-2A – were revealed last week at the Third International High Performance Computing Forum (IHPCF2017) in China. The TianHe-2A will use a proprieta Read more…

By John Russell

SC17 Preview: Invited Talk Lineup Includes Gordon Bell, Paul Messina and Many Others

September 25, 2017

With the addition of esteemed supercomputing pioneer Gordon Bell to its invited talk lineup, SC17 now boasts a total of 12 invited talks on its agenda. As SC explains, "Invited Talks are a premier component of the SC Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue’s max capacity and doubling 2016 attendee numbers), the one Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Prepares Customers for Success with the HPC Software Portfolio

High performance computing (HPC) software is key to harnessing the full power of HPC environments. Development and management tools enable IT departments to streamline installation and maintenance of their systems as well as create, optimize, and run their HPC applications. Read more…

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art of “The Grand Hotel Of The West,” contrasted nicely with Read more…

By Arno Kolster

China’s TianHe-2A will Use Proprietary Accelerator and Boast 94 Petaflops Peak

September 25, 2017

The details of China’s upgrade to TianHe-2 (MilkyWay-2) – now TianHe-2A – were revealed last week at the Third International High Performance Computing Fo Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art o Read more…

By Arno Kolster

Stanford University and UberCloud Achieve Breakthrough in Living Heart Simulations

September 21, 2017

Cardiac arrhythmia can be an undesirable and potentially lethal side effect of drugs. During this condition, the electrical activity of the heart turns chaotic, Read more…

By Wolfgang Gentzsch, UberCloud, and Francisco Sahli, Stanford University

PNNL’s Center for Advanced Tech Evaluation Seeks Wider HPC Community Ties

September 21, 2017

Two years ago the Department of Energy established the Center for Advanced Technology Evaluation (CENATE) at Pacific Northwest National Laboratory (PNNL). CENAT Read more…

By John Russell

Exascale Computing Project Names Doug Kothe as Director

September 20, 2017

The Department of Energy’s Exascale Computing Project (ECP) has named Doug Kothe as its new director effective October 1. He replaces Paul Messina, who is stepping down after two years to return to Argonne National Laboratory. Kothe is a 32-year veteran of DOE’s National Laboratory System. Read more…

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blu Read more…

By Merle Giles

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakthrough Science at the Exascale” at the ACM Europe Conference in Barcelona. In conjunction with her presentation, Yelick agreed to a short Q&A discussion with HPCwire. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Leading Solution Providers

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

  • arrow
  • Click Here for More Headlines
  • arrow
Share This