NVIDIA wants to repeat the CUDA success with Quantum Computing


In July 2022, NVIDIA announced the launch of its open, unified computing platform “QODA” (Quantum Optimized Device Architecture) to accelerate breakthroughs in quantum research and development in various fields including AI, HPC, health, finance and others.

With this, NVIDIA wants to make quantum computing more accessible by creating a coherent hybrid quantum-classical programming model. Its platform is currently used by the most powerful computers and quantum processors, improving scientific productivity and enabling greater scale in quantum research.

Accelerating quantum computing research

Contemporary quantum computers are programmed in equivalent assembly code, which has an extremely steep learning curve for researchers who are not already quantum engineers integrating quantum computing into their workflows. NVIDIA seeks to remove this barrier to entry by enabling the programming of hybrid quantum systems in a model familiar to scientific computing designers and interoperable with the best of today’s classical computing applications.

NVIDIA revealed that this enables the development of the first quantum-accelerated applications by enabling incremental quantum acceleration for scientific computing applications where it makes sense, while using the best of classical resources within the same applications.

The team found that QODA is the only unified platform that allows quantum computing to be added to the existing applications. It allows experts in HPC and AI domains to easily add quantum computing to existing applications, much like one would normally do classical computing.

Big bets on quantum computing

NVIDIA founder Jensen Huang founded the company in 1993 with the belief that the personal computer would one day become a consumer device for gaming and multimedia enjoyment. By 2022, the company’s work on AI will transform $100 trillion in industries – from gaming to healthcare to transportation – and profoundly impact society.

Now NVIDIA seems to be chasing the dreams of quantum computing.

NVIDIA said it has developed the tools to democratize new computing technologies and empower researchers and developers for decades. “Quantum computing holds promise for solving some of the most important challenges of our time. We see a great need for a unified platform to enable useful quantum computing.”

However, this brings us to the question, would this have an impact on the GPU business? “No. We are at the forefront and will continue to push the boundaries of what is possible in computing,” says Team NVIDIA, noting that hybrid quantum-classical computing will be around for decades to come.

Tim Costa, director of HPC and quantum computing products at NVIDIA, said that there will be scientific breakthroughs in the near future with hybrid solutions that combine classical computing and quantum computing. He said QODA would revolutionize quantum computing by giving developers a powerful and productive programming model.

How QODA works

QODA enables scientific developers to integrate quantum computing acceleration directly into their existing applications. It also allows them to fully develop hybrid applications, assembling the best classical and quantum resources for the tasks they are best suited for.

NVIDIA envisions algorithms and applications that benefit from both GPU and QPU processing. QODA would enable the efficient interoperability of these computational accelerators. Areas that would likely require classical parallel processing along with quantum co-processing include machine learning, financial portfolio optimization, and novel quantum chemistry algorithms and frameworks.

The team revealed that experts in HPC and AI domains can use today’s quantum processors and simulate future quantum machines with NVIDIA DGX systems and a large installed base of NVIDIA GPUs available in scientific supercomputing centers and public clouds.

However, this brings us to the question, would NVIDIA launch its quantum processors or QPUs? “No. We’re not,” the team says, explaining that they’re trying to empower the ecosystem with a programming model that allows them to easily add quantum computing to the existing applications.

Quantum computing versus hybrid quantum-classical computing

For those who don’t know, quantum computing runs entire applications on computer systems with quantum processing units (QPUs) and takes advantage of the potential performance benefits for specific types of problems. Most industry experts recognize that current quantum technology is limited in practical application due to challenges in scale, noise, reliability and cost.

On the other hand, hybrid classical quantum computing synthesizes existing applications that can now successfully add quantum architectures with GPU-accelerated classical computing architectures. GPU acceleration can help simulate QPU systems for early algorithm research and work with hardware QPUs to offload or otherwise distribute parts of a larger application where GPUs are a more appropriate compute element.


Illustrating the benefits, NVIDIA revealed that QODA connects quantum hardware manufacturers with a vast new class of developers who can now easily integrate quantum computing into their applications.

At the same time, hardware manufacturers could contribute different types of quantum processors. Software makers, on the other hand, might be able to code and develop applications for a variety of hybrid quantum systems in the same languages ​​and with the same tools as today’s leading scientific computing applications.

Analogous to the time when CUDA opened up a new kind of hardware and programming paradigm, we expect software developers to help develop an ecosystem of hybrid quantum applications running on top of QODA in application areas such as pharmaceuticals, energy, finance, logistics and more.”



As the company tries to boost the quantum technology ecosystem, another question arises: will QODA cannibalize CUDA or other parts of its business?

The team replies that interoperability is a key design priority. They emphasize that “QODA will work with CUDA, standard language concurrency, OpenACC, OpenMP and more”. Additionally, they stated that this would enable domain scientists to phase in quantum acceleration while adding programming platform support across GPU/CPU and hard/simulated QPUs.

What will NVIDIA get out of it?

NVIDIA said its existing customers are already using NVIDIA GPUs and highly specialized software — NVIDIA cuQuantum — to design custom quantum circuits. With QODA, developers can now build complete quantum applications that are simulated with NVIDIA cuQuantum on GPU-accelerated supercomputers.

Additionally, NVIDIA revealed that many types of organizations are currently investing in quantum approaches, with investments coming from government agencies, education institutions, and industry.

NVIDIA believes that partnerships across ecosystems and the democratization of software and hardware innovation would help increase the number of hardware, software, and ISVs working on quantum solutions.

Strengthening the quantum computing partner ecosystem

The company recently partnered with quantum hardware vendors. These include IQM Quantum Computers, Pasqal, Quantinuum, Quantum Brilliance and Xanadu; software vendors QC Ware and Zapata; and supercomputing centers – Forschungszentrum Jülich, Lawrence Berkeley National Laboratory (JUNIQ) and Oak Ridge National Laboratory.

Alex Chernoguzov, chief engineer at Quantinuum, said it has partnered with NVIDIA to enable users of Quantinnum’s H-series quantum processors, powered by Honeywell, to program the next generation of hybrid quantum-classical applications with QODA and to develop. He further revealed that the partnership brings together the most powerful classical computers with their world-class quantum processors.

Zapata CTO Yudong Cao said that QODA would enable HPC developers to accelerate their existing applications by providing an efficient way to program quantum and classical resources in a consolidated environment. He further explained that short-term applications in chemistry, drug discovery, materials science and more could be seamlessly integrated with quantum computing.

Kristel Michielsen said QODA would help bring quantum computing closer to the HPC and AI communities. “It’ll speed up the way they do things without them having to do all the low-level programming, so it makes their lives a lot easier,” she adds, explaining that many researchers would use QODA to do it to try hybrid quantum-classical computers – in the coming year and beyond.


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