IBM’s Quantum Race to One Million Qubits

By John Russell

September 15, 2020

IBM today outlined its ambitious quantum computing technology roadmap at its virtual Quantum Summit. The eye-popping million qubit number is still far out, agrees IBM, but perhaps not that far out. Just as eye-popping is IBM’s nearer-term plan for a 1,000-plus qubit system named Condor and expected around the end of 2023.

IBM is perhaps the dominant commercial player pursuing quantum computing and it has bet big on superconducting semiconductor-based qubit technology (transmons). One huge challenge has been quantum state fragility. IBM and most everyone else have been forced to use dilution refrigerators to keep quantum processors ice cold, just a few degrees Kelvin, to escape the disruptive ‘noise’ that confounds quantum circuits. It’s one of the issues that has kept qubit counts low.

In announcing IBM’s quantum technology plans, Jay Gambetta, IBM Fellow and VP of IBM Quantum, noted his blog, “As we explore realms beyond the thousand qubit mark, today’s commercial dilution refrigerators will no longer be capable of effectively cooling and isolating such potentially large, complex devices. We’re also introducing a 10-foot-tall and 6-foot-wide “super-fridge,” internally codenamed “Goldeneye,” a dilution refrigerator larger than any commercially available today. Our team has designed this behemoth with a million-qubit system in mind—and has already begun fundamental feasibility tests.

“Ultimately, we envision a future where quantum interconnects link dilution refrigerators each holding a million qubits like the intranet links supercomputing processors, creating a massively parallel quantum computer capable of changing the world.”

That is quite a vision and today’s detailed plan seems like an important moment in quantum computing if IBM can deliver. Many issues remain – scalability, error correction/mitigation, rival qubit technologies, to name just a few. Indeed, quantum computing technology is a domain in which progress has proven devilishly difficult to predict progress. Yet IBM was surprisingly specific today as shown by the bulleted timeline here:

  • IBM Hummingbird quantum processor

    2020 – Hummingbird (65 qubits). Released to IBM Q Network members earlier this month, Hummingbird “features 8:1 readout multiplexing, meaning we combine readout signals from eight qubits into one, reducing the total amount of wiring and components required for readout and improving our ability to scale, while preserving all of the high performance features from the Falcon generation of processors,” said Gambetta.

  • 2021 – Eagle (127 qubits). Eagle features several upgrades in order to surpass the 100-qubit milestone: crucially, through-silicon vias (TSVs) and multi-level wiring provide the ability to effectively fan-out a large density of classical control signals while protecting the qubits in a separated layer in order to maintain high coherence times.
  • 2022 – Osprey (433 qubits). Design principles established for IBM’s smaller set processors “set us on a course to release a 433-qubit IBM Quantum Osprey system in 2022. “More efficient and denser controls and cryogenic infrastructure will ensure that scaling up our processors doesn’t sacrifice the performance of our individual qubits, introduce further sources of noise, or take up too large a footprint,” said Gambetta.
  • 2023 – Condor (1,000-plus). “We think of Condor as an inflection point, a milestone that marks our ability to implement error correction and scale up our devices, while simultaneously complex enough to explore potential Quantum Advantages—problems that we can solve more efficiently on a quantum computer than on the world’s best supercomputers,” said Gambetta.

Putting all of this technology to good use is, of course, the goal. The quantum community has been chasing quantum advantage – the point at which for some application, a quantum computer performs sufficiently better than a classical computer to warrant switching. While that point is still distant, progress is being demonstrated. One example is recent work by IBM rival Google on quantum chemistry (see HPCwire article, Google’s Quantum Chemistry Simulation Suggests Promising Path Forward).

Measuring the quality of quantum computer performance so as to be able to gauge progress and to be able to make comparisons between various quantum computers is another challenge. IBM has proposed the QV – Quantum Volume – benchmark which has several attributes baked in (gate error rates, decoherence times, qubit connectivity, operating software efficiency, and more). Thus far a few other quantum system makers are also using QV. Lots of qubits isn’t helpful if the quality of the system performance is poor.

IBM achieved a QV of 64 earlier this summer and has said it will be able to double the QV of its systems yearly.

Said Gambetta, “The biggest challenge facing our team today is figuring out how to control large systems of these qubits for long enough, and with few enough errors, to run the complex quantum circuits required by future quantum applications.

IBM’s 27-qubit Falcon quantum processor

“We maintain more than two dozen stable systems on the IBM Cloud for our clients and the general public to experiment on, including our 5-qubit IBM Quantum Canary processors and our 27-qubit IBM Quantum Falcon processors—on one of which we recently ran a long enough quantum circuit to declare a Quantum Volume of 64. This achievement wasn’t a matter of building more qubits; instead, we incorporated improvements to the compiler, refined the calibration of the two-qubit gates, and issued upgrades to the noise handling and readout based on tweaks to the microwave pulses. Underlying all of that is hardware with world-leading device metrics fabricated with unique processes to allow for reliable yield.”

Given the heightened attention from government (i.e. spending) on quantum computing and the rapid fleshing out of a larger quantum computing ecosystem (s/w tools, consultants, DOE testbeds, et al), it will be interesting to track how IBM performs against its own goals.

Link to IBM blog: https://www.ibm.com/blogs/research/2020/09/ibm-quantum-roadmap/

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!

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 latest weapon in the AI battle with GPU maker Nvidia and clou Read more…

ISC 2024 Student Cluster Competition

May 16, 2024

The 2024 ISC 2024 competition welcomed 19 virtual (remote) and eight in-person teams. The in-person teams participated in the conference venue and, while the virtual teams competed using the Bridges-2 supercomputers at t Read more…

Grace Hopper Gets Busy with Science 

May 16, 2024

Nvidia’s new Grace Hopper Superchip (GH200) processor has landed in nine new worldwide systems. The GH200 is a recently announced chip from Nvidia that eliminates the PCI bus from the CPU/GPU communications pathway.  Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of the last panels at ISC 2024 — the discussion was fascinat Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can uncover patterns, generate insights, and make predictions that 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 Top500 list of the fastest supercomputers in the world. At s Read more…

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…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can un 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…

ISC 2024 Keynote: High-precision Computing Will Be a Foundation for AI Models

May 15, 2024

Some scientific computing applications cannot sacrifice accuracy and will always require high-precision computing. Therefore, conventional high-performance c Read more…

Shutterstock 493860193

Linux Foundation Announces the Launch of the High-Performance Software Foundation

May 14, 2024

The Linux Foundation, the nonprofit organization enabling mass innovation through open source, is excited to announce the launch of the High-Performance Softw Read more…

ISC 2024: Hyperion Research Predicts HPC Market Rebound after Flat 2023

May 13, 2024

First, the top line: the overall HPC market was flat in 2023 at roughly $37 billion, bogged down by supply chain issues and slowed acceptance of some larger sys Read more…

Top 500: Aurora Breaks into Exascale, but Can’t Get to the Frontier of HPC

May 13, 2024

The 63rd installment of the TOP500 list is available today in coordination with the kickoff of ISC 2024 in Hamburg, Germany. Once again, the Frontier system at Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. 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…

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…

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…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... 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…

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…

Leading Solution Providers

Contributors

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel 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…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b 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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire