D-Wave Breaks New Ground in Quantum Simulation

By John Russell

July 16, 2018

Last Friday D-Wave scientists and colleagues published work in Science which they say represents the first fulfillment of Richard Feynman’s 1982 notion that simulating physical systems could be done most effectively on quantum computers. In this instance, the project was the simulation of a quantum magnetism problem called the transverse field Ising model (TFIM) that has potential practical application in materials science research.

Using a standard D-Wave 2,048-quibit processor, the researchers simulated interacting Ising spins on 3D cubic lattices up to dimensions of 8x8x8. In some sense, the lattice represents an imaginary ‘substance’ comprised solely of magnetic moments; put another way, you are simulating correlated electron systems.

As the authors explain, “By tuning the amount of disorder within the lattice and varying the effective transverse magnetic field, we demonstrate phase transitions between a paramagnetic (PM), an ordered anti-ferromagnetic (AFM), and a spin-glass (SG) phase. The experimental results compare well with theory for this particular SG problem, thus validating the use of a probabilistic quantum computer to simulate materials physics. This represents an important step forward in the realization of integrated quantum circuits at a scale that is relevant for condensed matter research.”

In essence they fiddled with the simulation dials to watch how nature would unfold under different conditions. Using D-Wave’s quantum annealing technology meant, in effect, that each simulation evolved just as it would naturally. D-Wave’s usual programming tools were used.

An illustration of one particular 8x8x8 cubic lattice studied in Science, July 13, 2018. Red and blue spheres represent two possible states of magnetic moments. Silver bars represent antiferromagnetic interactions that favor alternating (blue-red) ordering of the moments. Gold bars represent randomly added ferromagnetic interactions that favor uniform (blue-blue or red-red) ordering. These latter interactions serve to disorder antiferromagnetic (alternating) ordering of the moments.
Source: D-Wave; Science

At least one observer calls the research ground-breaking. “Characterization of the phase behavior of a genuinely new material not found in nature by a precisely controlled quantum computer used as a simulator…[is] the first truly useful application of a quantum computer. [I]t shows us how to explore the behavior of novel system designs without having to completely understand them first, as we must to write a useful digital simulation code,” said Ned Allen, chief scientist and corporate senior fellow at Lockheed Martin – admittedly a D-Wave customer – in the official announcement.

D-Wave CEO Vern Brownell told HPCwire, “One of the slight nuances here is in order to do this type of modeling you actually have to take advantage of the quantum mechanical effects of the machine. If you were to simulate this on a classical machine like a large HPC cluster, the only way to do that is to simulate the quantum mechanics and there are ways to do that; Monte Carlo simulation is probably the most common way of doing that. That’s incredibly intensive computationally. The advantage that this machine has is actually leveraging those quantum mechanical effects to do a more efficient modeling.”

D-Wave, of course, has been in the thick of the race to develop quantum computers. Its approach – quantum annealing – has advocates and skeptics. Unlike a traditional gate model, D-Wave system architecture relies on the tendency of quantum systems to find low-energy states. Here’s the company’s summary for its most current machine:

  • A lattice of 2,000 tiny superconducting devices, known as qubits, is chilled close to absolute zero to harness quantum effects.
  • A user models a problem into a search for the “lowest energy point in a vast landscape”.
  • The processor considers all possibilities simultaneously to determine the lowest energy and the values that produce it.
  • Multiple solutions are returned to the user, scaled to show optimal answers.

In last week’s paper (Phase transitions in a programmable quantum spin glass simulator), researchers emphasized, “[The] structure of the magnetic system studied was vastly different from the physical layout of qubits within the QPU.”

D-Wave System

Said Brownell, “There are certainly many ways you can build a quantum computer. You can build quantum annealers [like] we build. You can build a gate model, which is what most of the other large companies are trying to build. Then there’s a topological model which Microsoft is trying to build. They’re all quantum computers. The differences are the relative exposure or susceptibility to error. The gate model to quantum computing is the most susceptible to errors, so you’ll need tens of thousands of qubits to simulate one logical qubit and there’s a huge overhead to that. That’s why gate model computers are 5- or 10- or 15 years away from being able to do useful applications. Certainly very far away from the scale of being able to do anything like what we have demonstrated here. Maybe a decade away.”

No doubt D-Wave’s rivals would disagree. To a significant extent D-Wave has always been a small player jostling with giants. It’s often received faint praise designed to spotlight perceived weaknesses of its quantum annealing technology. That hasn’t stopped the Canada-based quantum computing pioneer from punching above its weight in terms of actually selling systems (Lockheed and NASA, for example). The company is perhaps understandably sensitive to criticism.

Brownell points to a report from Jülich Supercomputing Center, Germany, presented at a D-Wave User meeting last April. “They use IBM’s and our system and have done a comparison. On a scale of 1-to-9 – what they call the quantum technology readiness (QTR, detailed at end of article) – we are at  level 8 and they have IBM at 5 along with Google and pretty much everybody else in quantum computing. It’s good to see these reports. There’s a lot of talk from the other folks and a lot of bluster about what their quantum computers can do, but here they have to expose their quantum computers to third party scrutiny and people can now make fair comparisons.”

Source: Jülich; D-Wave

The first D-Wave system was a 128-qubit machine introduced in 2010 with larger systems introduced roughly every two years. The current state of the art is the D-Wave 2000Q, announced in September 2016 and officially launched in early 2017. While a new machine is not expected soon, Brownell promises more important news towards the end of the summer, likely a large-scale cloud program and new tools. He also said another landmark paper is in the works.

Given the tremendous noise surrounding quantum computing currently Brownell is determined that D-Wave not be lost in the din. Earlier this month, D-Wave hired Jennifer Houston as SVP, marketing. “We had effectively no marketing or very little marketing going on,” said Brownell. A year ago, the company hired Alan Baratz as SVP of software and applications. Previously president of JavaSoft (Sun Microsystems), Baratz is charged with ecosystem development and presumably we will see the fruits of his efforts in the cloud/tool rollout.

Last week’s paper, though important, doesn’t mean quantum computing of any sort is suddenly ready for real-world materials science applications. Brownell agreed, “It’s certainly scientifically relevant to materials science research but you would have to work with very deep scientists in order to take advantage of this capability. [But] it is the start of the ability to use a quantum computer to do something useful.”

Jülich Quantum Computing Technology Readiness Level (source: Forschungszentum Jülich)

A quantum computing technology is at QTRL1 when the theoretical framework for quantum computing (annealing) is formulated. Theoretical studies of the basic properties of the quantum computing (annealing) devices move towards applied research and development. The technology reaches QTRL2 once the basic device principles have been studied and applications or technologically relevant algorithms are formulated. QTRL2 quantum computing technology is speculative, as there are little to no experimental results supporting the theoretical studies.

Fabricated imperfect physical qubits, the basic building blocks of quantum computing devices, are at QTRL3. Laboratory studies aim to validate theoretical predictions of qubit properties. Theoretical and laboratory studies are required to determine whether these basic elements of the quantum computing technology are ready to proceed further through the development process.

During QTRL4, multi-qubit systems are fabricated and classical devices for qubit manipulation are developed. Both components of the quantum computing technology are tested with one another. QTRL5 quantum computing technology comprises components integrated in a small quantum processor without error correction. Quantum computing devices labeled as QTRL5 must undergo rigorous testing including running of various algorithms for benchmarking. Components integrated in a small quantum processor with error correction are at QTRL6. Rigorous testing and running algorithms is repeated for the QTRL6 quantum computing technology.

QTRL7 quantum computing technology is a prototype quantum computer (annealer) solving small but user-relevant problems. The prototype is demonstrated in a user environment. A scalable version of a quantum computer (annealer) completed and qualified through test and demonstration is at QTRL8. Once quantum computers (annealers) exceed the computational power of classical computers for general (specific) problems the quantum computing technology can be labeled with QTRL9.

Link to paper: http://science.sciencemag.org/content/361/6398/162

Link to release: https://www.dwavesys.com/press-releases/d-wave-demonstrates-large-scale-programmable-quantum-simulation

Subscribe to HPCwire's Weekly Update!

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

Quantum Watchers – Terrific Interview with Caltech’s John Preskill by CERN

July 17, 2024

In case you missed it, there's a fascinating interview with John Preskill, the prominent Caltech physicist and pioneering quantum computing researcher that was recently posted by CERN’s department of experimental physi Read more…

Aurora AI-Driven Atmosphere Model is 5,000x Faster Than Traditional Systems

July 16, 2024

While the onset of human-driven climate change brings with it many horrors, the increase in the frequency and strength of storms poses an enormous threat to communities across the globe. As climate change is warming ocea Read more…

Researchers Say Memory Bandwidth and NVLink Speeds in Hopper Not So Simple

July 15, 2024

Researchers measured the real-world bandwidth of Nvidia's Grace Hopper superchip, with the chip-to-chip interconnect results falling well short of theoretical claims. A paper published on July 10 by researchers in the U. Read more…

Belt-Tightening in Store for Most Federal FY25 Science Budets

July 15, 2024

If it’s summer, it’s federal budgeting time, not to mention an election year as well. There’s an excellent summary of the curent state of FY25 efforts reported in AIP’s policy FYI: Science Policy News. Belt-tight Read more…

Peter Shor Wins IEEE 2025 Shannon Award

July 15, 2024

Peter Shor, the MIT mathematician whose ‘Shor’s algorithm’ sent shivers of fear through the encryption community and helped galvanize ongoing efforts to build quantum computers, has been named the 2025 winner of th Read more…

Weekly Wire Roundup: July 8-July 12, 2024

July 12, 2024

HPC news can get pretty sleepy in June and July, but this week saw a bump in activity midweek as Americans realized they still had work to do after the previous holiday weekend. The world outside the United States also s Read more…

Aurora AI-Driven Atmosphere Model is 5,000x Faster Than Traditional Systems

July 16, 2024

While the onset of human-driven climate change brings with it many horrors, the increase in the frequency and strength of storms poses an enormous threat to com Read more…

Shutterstock 1886124835

Researchers Say Memory Bandwidth and NVLink Speeds in Hopper Not So Simple

July 15, 2024

Researchers measured the real-world bandwidth of Nvidia's Grace Hopper superchip, with the chip-to-chip interconnect results falling well short of theoretical c Read more…

Shutterstock 2203611339

NSF Issues Next Solicitation and More Detail on National Quantum Virtual Laboratory

July 10, 2024

After percolating for roughly a year, NSF has issued the next solicitation for the National Quantum Virtual Lab program — this one focused on design and imple Read more…

NCSA’s SEAS Team Keeps APACE of AlphaFold2

July 9, 2024

High-performance computing (HPC) can often be challenging for researchers to use because it requires expertise in working with large datasets, scaling the softw Read more…

Anders Jensen on Europe’s Plan for AI-optimized Supercomputers, Welcoming the UK, and More

July 8, 2024

The recent ISC24 conference in Hamburg showcased LUMI and other leadership-class supercomputers co-funded by the EuroHPC Joint Undertaking (JU), including three Read more…

Generative AI to Account for 1.5% of World’s Power Consumption by 2029

July 8, 2024

Generative AI will take on a larger chunk of the world's power consumption to keep up with the hefty hardware requirements to run applications. "AI chips repres Read more…

US Senators Propose $32 Billion in Annual AI Spending, but Critics Remain Unconvinced

July 5, 2024

Senate leader, Chuck Schumer, and three colleagues want the US government to spend at least $32 billion annually by 2026 for non-defense related AI systems.  T Read more…

Point and Click HPC: High-Performance Desktops

July 3, 2024

Recently, an interesting paper appeared on Arvix called Use Cases for High-Performance Research Desktops. To be clear, the term desktop in this context does not Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Everyone Except Nvidia Forms Ultra Accelerator Link (UALink) Consortium

May 30, 2024

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…


Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs

June 30, 2024

Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst fir Read more…

AMD Clears Up Messy GPU Roadmap, Upgrades Chips Annually

June 3, 2024

In the world of AI, there's a desperate search for an alternative to Nvidia's GPUs, and AMD is stepping up to the plate. AMD detailed its updated GPU roadmap, w Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Intel’s Next-gen Falcon Shores Coming Out in Late 2025 

April 30, 2024

It's a long wait for customers hanging on for Intel's next-generation GPU, Falcon Shores, which will be released in late 2025.  "Then we have a rich, a very Read more…

Leading Solution Providers


Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

IonQ Plots Path to Commercial (Quantum) Advantage

July 2, 2024

IonQ, the trapped ion quantum computing specialist, delivered a progress report last week firming up 2024/25 product goals and reviewing its technology roadmap. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

  • arrow
  • Click Here for More Headlines
  • arrow