NVIDIA announced the world’s first unified computing platform at Q2B conference in Tokyo. The programming platform will help speed quantum research and development breakthroughs across AI, HPC, health, finance, and tech research.
NVIDIA announced the world’s first unified computing platform at Q2B conference in Tokyo. The programming platform will help speed quantum research and development breakthroughs across AI, HPC, health, finance, and tech research.
NVIDIA Quantum Optimized Device Architecture (QODA) simplifies and streamlines hybrid quantum-classical computing development by overcoming roadblocks in the quantum computing field. QODA creates an open, unified environment across some of the most powerful computers and quantum processors, improving scientific productivity and delivering a greater scale in quantum research.
What is Quantum Computing?
According to NVIDIA’s Dion Harris blog post, Quantum computing is a sophisticated approach to making parallel calculations, using the physics that governs subatomic particles to replace the more simplistic transistors in today’s computers.
Quantum computers calculate using qubits, computing units that can be on, off, or any value between, instead of the bits in traditional computers that are either on or off, one or zero. The qubit’s ability to live in the in-between state — called superposition — adds a powerful capability to the computing equation, making quantum computers superior for some kinds of math.
Computers today use eight bits to represent any number between 0 and 255, making calculations one at a time. A quantum computer can simultaneously use eight qubits to represent every number between 0 and 255. Processing is computed simultaneously rather than sequentially, delivering results in seconds.
Using qubits, quantum computers could race through calculations in minutes that would take classical computers hundreds or thousands of years if they could even finish them.
HPC and AI domain experts can use QODA to easily add quantum computing to existing applications, leveraging both today’s quantum processors as well as simulated future quantum machines using NVIDIA DGX systems and a large installed base of NVIDIA GPUs available in scientific supercomputing centers and public clouds.
According to NVIDIA’s Tim Costa, director of HPC and Quantum Computing Products:
“Scientific breakthroughs can occur in the near term with hybrid solutions combining classical computing and quantum computing. QODA will revolutionize quantum computing by giving developers a powerful and productive programming model.”
NVIDIA cuQuantum SDK
During the GTC keynote earlier this year, NVIDIA announced the cuQuantum SDK to speed quantum circuit simulations running on GPUs. Early work suggests cuQuantum will be able to deliver orders of magnitude speedups.
NVIDIA and Caltech accelerated a state-of-the-art quantum circuit simulator with cuQuantum running on NVIDIA A100 Tensor Core GPUs. It generated a sample from a full-circuit simulation of the Google Sycamore circuit in 9.3 minutes on Selene, a task that 18 months ago experts thought would take days using millions of CPU cores.
Leading quantum organizations are already using NVIDIA GPUs and NVIDIA cuQuantum software development kit (SDK) to accelerate the development of individual quantum circuit simulations on GPUs. QODA extends NVIDIA’s quantum research
efforts by leveraging cuQuantum’s simulation environments.
NVIDIA also announced QODA collaborations with quantum hardware providers IQM Quantum Computers, Pasqal, Quantinuum, Quantum Brilliance, and Xanadu; software providers QC Ware and Zapata Computing; and supercomputing centers Forschungszentrum Jülich, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory.
Enter the QPU and hybrid systems
NVIDIA’s Tim Costa has posted a blog focused on quantum, QODA, and hybrid classical-quantum systems, highlighted by a discussion with Kristel Michielsen from Jülich Unified Infrastructure for Quantum Computing (JUNIQ).
Michielsen, who leads the quantum program at the Jülich Supercomputing Center near Cologne, explained:
“We can’t go on with today’s classical computers alone because they consume so much energy, and they can’t solve some problems. But paired with quantum computers that won’t consume as much energy, I believe there may be the potential to solve some of our most complex problems.”
Tim explains that quantum processors, aka QPUs, harness the properties of quantum mechanics and are ideally suited to simulating processes at the atomic level, enabling fundamental advances in chemistry and materials science, affecting everything from more efficient batteries to more effective drugs.
Although several prototype quantum computers are available, they are still in the infancy stage and do not support the power or dependability to tackle commercially relevant jobs. Researchers are linking classical HPC systems with quantum computers to address this issue. Michielsen says it “will give us the best of both worlds.” Jülich and other researchers are building those systems today.
Check out Tim’s full blog post on Jülich Quantum.
With the quantum computing industry currently dominated by a few key players, NVIDIA QODA could create a new class of developers capable of leveraging open and interoperable standards across various hardware and software platforms.
Learn more about NVIDIA QODA.
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