The Department of Energy's Oak Ridge National Laboratory, NVIDIA, and HPE will seek to open new insights into quantum computing and identify potential strategies toward the integration of quantum, artificial intelligence and high-performance computing for scientific discovery.
"Maintaining America's leadership in high-performance computing requires us to build the bridge to the next era of computing: accelerated quantum supercomputing," said U.S. Secretary of Energy Chris Wright. "The deep collaboration between our national laboratories, startups and industry partners like NVIDIA is central to this mission - and NVIDIA NVQLink provides the critical technology to unite world-class GPU supercomputers with emerging quantum processors, creating the powerful systems we need to solve the scientific challenges of our time."
At ORNL's Oak Ridge Leadership Computing Facility (OLCF), lab researchers will leverage NVIDIA NVQLink and NVIDIA CUDA-Q programming tools - designed to integrate classical computing clusters with quantum processors for performing control tasks like quantum error correction and the running hybrid quantum-classical algorithms. NVIDIA CUDA-Q also allows running GPU-accelerated simulations mimicking actual quantum hardware. These are crucial tools fora novel testbed that will explore and compare these advanced technologies side by side.
The platforms will run on an NVIDIA GB200 NVL72 system built by HPE that will be installed in early 2026 at the OLCF data center, also home to Frontier, the world's first exascale supercomputer.
"Our partnerships at ORNL with NVIDIA and HPE usher in a new era of hybrid computing," said ORNL Director Stephen Streiffer. "We look forward to taking these steps toward quantum acceleration of HPC."
Quantum initiative continues to push quantum computing capabilities
Quantum computing relies on quantum bits, or qubits, to store information. Qubits, unlike the binary bits used in classical computing, can exist in more than one state simultaneously via quantum superposition, which allows combinations of physical values to be encoded on a single object.
Researchers theorize that ability could lead to faster, more efficient ways to solve complex scientific problems that so far have defied traditional approaches - even at exascale, which offers computing speeds faster than a quintillion calculations per second, and for emerging AI models.
"We believe the future of scientific computing lies in finding ways to harmonize these three computing platforms and draw on the unique strengths of each approach," said Georgia Tourassi, director of ORNL's Computing and Computational Sciences Directorate, which oversees the OLCF.
High-resolution digital simulations on a quantum computer could help crack computationally expensive fundamental questions in physics, chemistry, materials science and more.
The primary obstacle to reaching that quantum computing has been the relatively high error rate caused by the delicate nature of qubits. Various solutions remain in development. The final technology for quantum computing also has yet to be settled, with various systems employing neutral atoms, trapped ions, superconductors and other materials.
As a first step, ORNL's machine will maneuver around some of those roadblocks by combining classical technology, such as the traditional GPUs and CPUs that power most supercomputers, with hybrid computing platforms through CUDA-Q that uses NVIDIA technology to both connect with quantum processors as well as emulate their quantum operations without the noise from degrading qubits. The platform will combine HPE's integration expertise and NVIDIA's hardware innovation to advance state-of-the-art AI research while enabling the investigation of iterative, low-latency decoding that quantum error correction requires.
Because the platform won't be tied to a single quantum computing protocol, researchers can adapt approaches as needed to apply those operations across the widest array of technologies and work in tandem with other machines, from the Frontier supercomputer to ORNL's recently acquired Quantum Brilliance and IQM quantum computers.
We believe the future of scientific computing lies in finding ways to harmonize these three computing platforms and draw on the unique strengths of each approach.
Quantum, HPC comparisons could help harmonize technologies
"We'll be able to run operations that help us leverage these platforms and look for strategies to make the best possible use of quantum and classical technology," said Amir Shehata, an ORNL software engineer and lead author of a recent study on quantum-HPC convergence. "The results from an actual quantum computer and the quantum emulator or from Frontier can be studied and we can make modifications, such as introducing artificial noise on the quantum emulator, using that to predict the noise in results from an actual quantum computer and potentially training an AI model to correct those errors.
"The convergence we're seeking to build is a harmony, not one technology replacing the other. We want to ultimately combine all of these approaches in a form that gets the best possible results, independent of the computing platform, that can be used as widely as possible for the greatest overall benefit."
Initial testing has begun at a secure, direct liquid cooling HPE manufacturing factory, where teams from ORNL and NVIDIA are running early workloads to validate the system's performance and stability. These tests will be critical steps toward establishing a trusted platform for quantum error correction research, with an emphasis on scaling routines for decoding errors and reducing bottlenecks in hybrid computing workflows.
"The OLCF has built a 20-year legacy of excellence in high-performance computing," said Ashley Barker, the OLCF's program director. "This partnership is just one more step toward delivering a system that leverages these platforms to better serve our user community and science in general."
Previous collaboration between ORNL and NVIDIA led to the launch in 2009 of Titan, the first major supercomputer to employ the now-familiar hybrid architecture that combines GPUs and CPUs. Further collaboration led to the Summit supercomputer powered by NVIDIA V100 Tensor Core GPUs in collaboration with IBM. Collaboration with HPE led to the launch of Frontier, the first computer to break the exascale barrier in 2022.
The OLCF is a DOE Office of Science user facility.
In celebration of the International Year of Quantum Science and Technology in 2025, ORNL continues to empower the pursuit of quantum innovation, advancing world-leading scientific discovery to enable a quantum revolution that promises to transform a vast range of technologies critical to American competitiveness. Click here to learn more about quantum science at ORNL.
UT-Battelle manages ORNL for DOE's Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE's Office of Science is working to address some of the most pressing challenges of our time. For more information, visit energy.gov/science . - Matt Lakin
