Three insights you might have missed from theCUBE’s coverage of HPE World Quantum Day

Quantum computing, artificial intelligence and high-performance computing will play complementary roles in driving the next era of technology innovation. That is, if the industry can figure out a way to open doors and more easily enable development work beyond quantum specialists.

Speaking with theCUBE’s enterprise editor, Paul Gillin (pictured, left), as part of an AnalystANGLE segment during the HPE World Quantum Day event, Dave Vellante (right), chief analyst at theCUBE Research, explained that quantum, HPC and AI are not rivals locked in a zero-sum game for technological dominance.

“It’s really about bringing together these three powerful technologies — CPUs, GPUs and now quantum processors, or QPUs — to solve problems that couldn’t be tackled before,” Vellante said.

One remaining barrier is that the industry is mired in the “Stone Age” when it comes to developing software for quantum computing, according to Gillin. He stressed the need for a “Python for quantum” that would simplify and democratize developer access to quantum systems.

“Until that can be made more broadly available — until more people have access to quantum technology — it’s going to continue to be kind of a lab project,” Gillin said.

At the recent HPE World Quantum Day event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio, Gillin and Vellante spoke with industry experts from Oak Ridge National Lab, Argonne National Laboratory and more about how quantum computing, HPC and AI are beginning to converge — not as competing technologies, but as complementary layers shaping the next phase of enterprise innovation. (* Disclosure below.)

Here’s the analysis segment with Gillin and Vellante, part of SiliconANGLE’s and theCUBE’s coverage of the HPE World Quantum Day event:

Here are three key insights you may have missed from HPE World Quantum Day:

Insight #1: Quantum’s short-term impact will be in accelerating existing workflows.

Researchers are exploring ways that quantum computing can optimize and accelerate critical science that’s already being done with the help of supercomputers.

Rather than replacing classical systems, quantum computing is likely to enter the enterprise as a highly targeted accelerator — designed to enhance specific, complex workloads where traditional approaches fall short. Tom Beck (pictured), section head for science engagement and acting group leader for quantum-HPC at Oak Ridge National Laboratory — home to Frontier, one of the world’s most powerful supercomputers — described this interim phase in a conversation with Vellante, positioning quantum not as a replacement, but as a complementary force within hybrid compute environments.

“We’re trying to figure out how to link quantum computers to HPC so that we can download certain parts of the calculation onto HPC machines to accelerate those, but do the really hardest quantum part or something that can be accelerated by quantum on the quantum device,” Beck said. “So it’s really a game of transfer of information. How do you accelerate the flow of information between the two machines and do the hardest thing on the quantum device?”

Here’s theCUBE’s complete interview with Tom Beck:

A team at the Argonne National Laboratory is similarly working to integrate quantum computing into real-world workflows, which can help accelerate processing times for use cases in chemistry and materials science, according to Laura Schulz, project lead for quantum innovation.

“When we’re trying to simulate or study quantum mechanical effects with HPC, we’re having to build a simulation,” Schulz told theCUBE. “Quantum computing allows researchers to study quantum mechanical effects” directly.

This supports a balance of work where quantum mechanics is relied upon to solve a portion of a problem and its results are fed back into classical simulations running on supercomputers for the rest of the work. 

Here’s theCUBE’s complete interview with Laura Schulz:

Insight #2: Researchers are working to solve the engineering challenges that hinder mainstream adoption.

Quantum offers a significant boost in processing power over supercomputing, which makes it especially useful for complex problems that require scale, such as tracking how neutrinos behave in stars.

Commercial applications in areas such as logistics and drug research are already within reach — modern lasers and MRI machines rely on quantum science — but physical and engineering constraints continue to slow broader adoption, according to Kristi Beck, director of the Livermore Center for Quantum Science at Lawrence Livermore National Laboratory.

“The applications in pharmacology come from the anticipated benefit that we have for many of the chemistry problems that, ultimately, are what underpin how we understand drug interactions,” Beck told theCUBE. “But I’d say those are further off due to the complexity of those problems, although they are ones where we would expect to see a better win than we do in the logistical ones.”

Here’s theCUBE’s complete interview with Kristi Beck:

Back at Oak Ridge National Laboratory, researchers are working with quantum vendors, universities and labs to understand how to make quantum more accessible. This means evaluating requirements at every level of the tech stack in order to create a middleware layer that can handle the unique intricacies of quantum mechanics, according to Amir Shehata, HPC systems engineer, Quantum-HPC Group, at Oak Ridge National Laboratory. Qubits, the basic unit of information in quantum computing, offer a particularly thorny challenge.

“If you’re working with superconducting, the qubits have shorter life cycles and they degrade fast, so you have tighter timing that you have to deal with,” Shehata explained. “And if you’re working with neutral atoms or another type of slower modality, then there’s different timing constraints there. So your software stack that you’re developing has to handle all these different types of requirements that are being thrown at you from the hardware side.”

A new software infrastructure to enable quantum computing will actually rely on familiar technology, such as GPUs, Shehata added.

Here’s theCUBE’s complete interview with Amir Shehata:

Insight #3: Maximizing the potential of quantum computing will mean solving the right job at the right time.

Since qubits can exist in multiple states simultaneously and be linked via entanglement, quantum computers can simultaneously consider all solutions to a potential problem. This opens up possibilities to more efficiently solve challenges that would take today’s supercomputers years to consider.

Quantum computers are best suited for complex mathematical equations that require a high degree of accuracy, according to Mikael Johansson, manager for quantum technologies at CSC, the Finnish IT Center for Science.

“Take just the green transition as an example; we could design better catalysts and develop next-generation batteries and magnets that are very central, of course, to modern society,” Johansson explained.

Here’s theCUBE’s complete interview with Mikael Johansson:

But that doesn’t mean quantum computers will replace supercomputers, according to Dieter Kranzlmüller, chairman of the board at the Leibniz Supercomputing Centre. Both have a job to do.

“This means, in essence, that we are sending jobs to the supercomputer and the system decides whether it’s done on the supercomputer or whether it’s kind of given to the quantum computer,” Kranzlmüller told theCUBE. “I think that’s the important thing about why we do integration and why we believe we should combine both of these things together.”

Here’s theCUBE’s complete interview with Dieter Kranzlmüller:

https://www.youtube.com/watch?v=waNoc6NpNq0 

Still, progress depends on broader participation. The Pawsey Supercomputing Research Centre in Perth, Australia, operates an initiative called Setonix-Q. Its aim is to give Australian researchers the tools and guidance to experiment with quantum mechanics, according to Pascal Elahi, quantum supercomputing research lead at Pawsey.

“We want to expand access not just to quantum computing researchers, but to people who want to solve a problem,” Elahi told theCUBE.

Here’s theCUBE’s complete interview with Pascal Elahi:

Catch up on our complete coverage of HPE World Quantum Day:

(* Disclosure: TheCUBE is a paid media partner for the HPE World Quantum Day event. Neither HPE, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE