IBM Expands Quantum Computing Network

By Tiffany Trader

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qubits isn’t enough, there needs to be an engaged ecosystem of partners. As part of its strategy to transition from quantum science to what IBM calls quantum-readiness, Big Blue held the first IBM Q Summit in Palo Alto, California, today (April 5), welcoming a group of startups into its quantum network.

“Membership in the network will enable these startups to run experiments and algorithms on IBM quantum computers via cloud-based access,” explained Jeff Welser, director, IBM Research – Almaden, in a blog post. “Additionally, these startup members will have the opportunity to collaborate with IBM researchers and technical SMEs on potential applications, as well as other IBM Q Network organizations.”

The Q Network was launched in December in partnership with both industry and academic and government clients, including JP Morgan Chase, Daimler, Samsung, JSR, Barclays, Keio University, Honda, Oak Ridge National Lab, University of Oxford, University of Melbourne, Hitachi Metals and Nagase. Now IBM has brought in these eight industry-leading startups: Cambridge Quantum Computing (CQC), 1QBit, QC Ware, Q-CTRL, Zapata Computing, Strangeworks, QxBranch, and Quantum Benchmark. (Additional info at end of article.)

Quantum was a major topic of the inaugural IBM Think conference held in Las Vegas last month, where a number of featured speakers shared an optimistic timeline for establishing production usable applications.

Arvind Krishna, senior vice president, Hybrid Cloud, and director of IBM Research, said he believes IBM will show a practical quantum advantage within five years and it will have built capable machines for that purpose in three-to-five years.

Krishna hailed a coming era of practical quantum computing. “Quantum computers will help us solve problems that classical computers never could, in areas such as materials, medicines, transportation logistics, and financial risk,” he said during a keynote address.

IBM has been focused on making the engineering more stable and robust to enable a broader set of users, outside the physics laboratory. “To exploit and win at quantum, you actually have to have a real quantum computer,” said Krishna.

The community ecosystem is where IBM is distinguishing itself in the tight landscape of quantum competitors, that includes Google, Intel, Microsoft, early pioneer in quantum annealing D-Wave, and Berkeley-based startup Rigetti.

IBM has a set of three prototype quantum computers, real quantum devices not simulators, made available through its cloud network, which in just two years has seen 80,000 users run more than 3 million remote executions. There are 5-qubit and 16-qubit quantum systems available to anyone with an internet connection via IBM’s Q Experience platform, and a larger 20-qubit machine for select Q Network partners. IBM has also successfully built an operational prototype 50-qubit processor that will be made available in the next generation IBM Q systems.

As IBM grows its Q Network partner ecosystem, participating organizations will have various levels of cloud-based access to quantum expertise and resources. This means that not all members will get time on the biggest Q System, but startups in the quantum computing space will get “deeper access to APIs and advanced quantum software tools, libraries and applications, as well as consultation on emerging quantum technologies and applications from IBM scientists, engineers and consultants,” according to Welser.

The goal of the Q Network is to advance practical applications for business and science and ultimately usher in the commercial quantum era. “We will emerge from this transitional era and enter the era of quantum advantage when we run the first commercial application. It’s not about arbitrary tests or quantum supremacy, it’s very practical,” said Anthony Annunziata, associate director, IBM Q, at last month’s event. “When we can do practical things, we will have achieved the practical era.”

By making the machines available to a broader community, IBM is seeding the development of a software and user ecosystem. Annunziata stressed the importance of educating and preparing users across organizations for the coming of quantum computing. “It doesn’t matter how much we can abstract away,” he said, “quantum computing is just different. It takes a different mindset and skill set to program a quantum computer, especially to take advantage of it.”

There are two different ways of programming the IBM Q network machines: a graphical interface with drag-and-drop operations and an open-source software developer kit called QISKit. QISKit, as IBM’s Talia Gershon enthusiastically explained in her keynote talk, makes it possible to entangle two qubits with two lines of code.

Talia Gershon presenting at IBM Think 2018

Gershon, senior manager, AI Challenges and Quantum Experiences at IBM, holds that having fundamentally new ways of doing computation will open up a new paradigm in how we approach problems, but first we have to stop “thinking too classically.”

“Thinking too classically, as my colleague Jay Gambetta says, means you’re trying to apply linear classical logical thinking to understand something quantum and it doesn’t work,” said Gershon. “Thinking too classically is a real problem that hinders progress so how do we get people to change the way they think? Well we start in the classroom. When Einstein first discovered relativity I’m sure nobody intuitively got it and understood why was important and today it’s in every modern physics classroom in the world.

“Within five years the same thing will happen with quantum computing. Not only will physics departments offer quantum information classes but computer science departments will offer a quantum track. Electrical engineering departments will teach students about quantum circuits and microwave signal processing and chemistry classes will teach students not only how to simulate molecules on a classical machine but also on a quantum computer.”


Descriptions of the eight startups selected by IBM to be part of the Q Network:

•  Zapata Computing – Based in Cambridge, Mass., Zapata Computing is a quantum software, applications and services company developing algorithms for chemistry, machine learning, security, and error correction.

• Strangeworks – Based in Austin, Texas, and founded by William Hurley, Strangeworks is a quantum computing software company designing and delivering tools for software developers and systems management for IT Administrators and CIOs.

• QxBranch – Headquartered in Washington, D.C., QxBranch delivers advanced data analytics for finance, insurance, energy, and security customers worldwide. QxBranch is developing tools and applications enabled by quantum computing with a focus on machine learning and risk analytics.

• Quantum Benchmark – Quantum Benchmark is a venture-backed software company led by a team of the top research scientists and engineers in quantum computing, with headquarters in Kitchener-Waterloo, Canada. Quantum Benchmark provides solutions that enable error characterization, error mitigation, error correction and performance validation for quantum computing hardware.

• QC Ware – Based in Palo Alto, Calif., QC Ware develops hardware-agnostic enterprise software solutions running on quantum computers. QC Ware’s investors include Airbus Ventures, DE Shaw Ventures and Alchemist, and it has relationships with NASA and other government agencies. QC Ware won a NSF grant, and its customers include Fortune 500 industrial and technology companies.

• Q-CTRL – This Sydney, Australia-based startup’s hardware agnostic platform – Black Opal – gives users the ability to design and deploy the most effective controls to suppress errors in their quantum hardware before they accumulate. Q-CTRL is backed by Main Sequence Ventures and Horizons Ventures.

• Cambridge Quantum Computing (CQC) – Established in 2014 in the UK, CQC combines expertise in quantum information processing, quantum technologies, artificial intelligence, quantum chemistry, optimization and pattern recognition. CQC designs solutions such as a proprietary platform agnostic compiler that will allow developers and users to benefit from quantum computing even in its earliest forms. CQC also has a growing focus in quantum technologies that relate to encryption and security.

 1QBit – Headquartered in Vancouver, Canada, and founded in 2012, 1Qbit develops general purpose algorithms for quantum computing hardware. The company’s hardware-agnostic platforms and services are designed to enable the development of applications which scale alongside the advances in both classical and quantum computers. 1QBit is backed by Fujitsu Limited, CME Ventures, Accenture, Allianz and The Royal Bank of Scotland.

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!

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

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

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

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