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!

Researchers Advance Graphene’s Potential as Silicon Alternative

March 30, 2017

In the face of a slowing Moore’s law for silicon-based CMOS technology, researchers are on the hunt for a successor to silicon. Read more…

By Tiffany Trader

Idaho National Laboratory Set for $90M Cybersec/HPC Expansion

March 30, 2017

Idaho lawmakers this week approved a $90 million bond to fund the construction of two new Idaho National Laboratory buildings: the Cybercore Integration Center and the Collaborative Computing Center. Read more…

By Tiffany Trader

Ohio Supercomputer Center Dedicates ‘Owens’ Cluster

March 29, 2017

In a dedication ceremony held earlier today (March 29), officials from Ohio Supercomputer Center (OSC) along with state representatives gathered to celebrate the launch of OSC’s newest cluster: Read more…

By Tiffany Trader

EU Ratchets up the Race to Exascale Computing

March 29, 2017

The race to expand HPC infrastructure, including exascale machines, to advance national and regional interests ratcheted up a notch yesterday with announcement that seven European countries – Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging the Power of Big Data to Improve Customer Satisfaction & Brand Loyalty

In the dynamic world of retail, retailers must find ways to recognize and effectively respond to shopping behaviors, patterns, and trends in order to succeed. Read more…

Data-Hungry Algorithms and the Thirst for AI

March 29, 2017

At Tabor Communications’ Leverage Big Data + EnterpriseHPC Summit in Florida last week, esteemed HPC professional Jay Boisseau, chief HPC technology strategist at Dell EMC, engaged the audience with his presentation, “Big Computing, Big Data, Big Trends, Big Results.” Read more…

By Tiffany Trader

Bill Gropp – Pursuing the Next Big Thing at NCSA

March 28, 2017

About eight months ago Bill Gropp was elevated to acting director of the National Center for Supercomputing Applications (NCSA). Read more…

By John Russell

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Data-Hungry Algorithms and the Thirst for AI

March 29, 2017

At Tabor Communications’ Leverage Big Data + EnterpriseHPC Summit in Florida last week, esteemed HPC professional Jay Boisseau, chief HPC technology strategist at Dell EMC, engaged the audience with his presentation, “Big Computing, Big Data, Big Trends, Big Results.” Read more…

By Tiffany Trader

Bill Gropp – Pursuing the Next Big Thing at NCSA

March 28, 2017

About eight months ago Bill Gropp was elevated to acting director of the National Center for Supercomputing Applications (NCSA). Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Leading Solution Providers

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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