NVIDIA CUDA-Q brings quantum computing to today's supercomputers

O NVIDIA CUDA-Q arrives as a bridge that unites quantum and classical computing, offering a synergy between both parts. By integrating these domains, companies and institutions have diverse work possibilities, expanding the horizons of research and its applications. Its ability to deliver advanced performance and its flexibility in choosing Quantum Processing Units (QPUs) make it a great tool for driving innovation in areas dependent on high-performance computing. Understand better about the platform and its applications.

Benefits of CUDA-Q

O NVIDIA CUDA-Q (acronym for Compute Unified Device Architecture for Quantum, in Portuguese, Unified Computing Device Architecture for Quantum) offers a series of benefits at the intersection between quantum computing and supercomputing. Its most notable feature is the tight integration between the two computing domains. This integration allows companies and institutions to make the most of the potential of quantum computing in conjunction with classical computing, opening up new possibilities for research and application.

This technology demonstrates advanced performance, being able to deliver high-quality results in a variety of applications, from chemical simulations to optimization problems. This efficiency is very important for driving innovation and progress in fields that rely heavily on high-performance computing.

One of the strengths of quantum computing with NVIDIA CUDA-Q is its flexibility e agnosticism in relation to QPU. This means that organizations have the freedom to choose the quantum processing units that best suit their specific needs, without being locked into a single hardware option. This flexibility is essential in a field as dynamic as quantum computing.

Furthermore, supporting the developer community is a crucial aspect for a quantum computer with NVIDIA CUDA-Q. As a open source platform, it encourages collaboration and community development by enabling developers to access the tools and resources needed to explore and expand the horizons of quantum computing alongside classical computing.

Finally, the platform NVIDIA CUDA-Q it also enables innovative solutions by enabling the combination of quantum computing with artificial intelligence. This integration paves the way for innovative approaches that can address challenges such as qubits — used in QPUs, which we will explain below — noisy and develop efficient algorithms. This synergy between different areas of computing drives continuous advancement at the frontier of research and practical application of quantum computing.

Our collaboration with ORCA and NVIDIA allowed us to create a unique environment and build a new classical quantum hybrid system at PSNC. Easy and open integration and programming of multiple QPUs and GPUs efficiently managed by user-centric services is essential for developers and users. This close collaboration paves the way for a new generation of quantum-accelerated supercomputers for many innovative application areas, not tomorrow, but today.

Said Krzysztof Kurowski, CTO and Deputy Director of PSNC

What are QPUs?

As QPUs, or Quantum Processing Units, are essential components of quantum computers. While classical processors, like those found in traditional computers, use bits To process information, quantum computers use qubits, which are units of quantum information.

Um quibit can exist in multiple states simultaneously, thanks to a quantum phenomenon called superposition. This means that while a classical bit can be in a state of 0 or 1 at a given time, a qubit can be in a superposition of these states, representing 0, 1 or any combination of the two at the same time. This gives quantum computers an exponentially greater capacity for processing information compared to classical computers.

They are responsible for manipulating and operating these qubits by applying quantum operations, such as quantum gates and measurements, to perform calculations and process information in a quantum way. Additionally, QPUs need to be extremely accurate and stable, as qubits are susceptible to environmental interference, such as noise and temperature.

QPUs are the heart of quantum computers and play a fundamental role in carrying out quantum tasks and algorithms. Companies and research institutions around the world, like NVIDIA itself, are investing in developing and improving QPUs to drive the advancement of quantum computing and explore its potential in a wide range of applications, from chemical simulations to cryptography and artificial intelligence.

Applications and advantages

Quantum Processing Units present a wide range of applications and advantages that promise to revolutionize computing and science. We can start by citing the quantum simulations, where QPUs are used to model complex quantum systems, such as molecules and materials. This could lead to advances in understanding chemical and physical processes, as well as the discovery of new materials with unique properties, including high-temperature superconductors.

Another important application is optimization, in which QPUs have the potential to solve complex optimization problems in a much more efficient than classical computers. This is relevant in many areas, from logistics and planning to finance and electronic circuit design.

In the context of information security, QPUs have a dual role. On the one hand, they can be used to break many of the encryption systems currently in use. On the other hand, QPUs can also be used to develop quantum cryptography methods that are theoretically tamper-proof, offering a new data security paradigm.

Combining QPUs with quantum machine learning algorithms has the potential to drive advances in the field of artificial intelligence, especially in problems involving large volumes of data and computational complexity — this is a very current aspect.

In areas such as medicine and biology, QPUs can be used to simulate and understand complex biological processes, such as protein folding and the interaction of drugs with cellular receptors. These simulations can contribute to the development of more effective medicines and personalized treatments. And also in the financial sector, where QPUs can be applied to optimize investment portfolios, model complex financial risks and identify patterns in large sets of market data.

Supercomputers benefited

Supercomputers benefiting from the integration of the NVIDIA CUDA-Q platform are located in leading research centers around the world. O Jülich Supercomputing Center (JSC) in Germany operates the supercomputer JUPITER, which will now be complemented with a Quantum Processing Unit (QPU) supplied by IQM Quantum Computers. This QPU will be driven by the NVIDIA GH200 Grace Hopper Superchip. This partnership will enable JSC researchers to develop and execute quantum applications, especially in chemical simulations and optimization problems, while also serving as an example of how classical supercomputers can be accelerated by quantum computing.

In Japan, the National Institute of Advanced Industrial Science and Technology (AIST) is advancing its quantum computing initiative with supercomputer ABCI-Q. Integrating a QPU provided by QuEra and powered by the NVIDIA Hopper architecture, this system will open up new research opportunities. AIST researchers will be able to explore quantum applications in artificial intelligence, energy and biology, using rubidium atoms as laser-controlled qubits to perform complex calculations.

Finally, the Poznan Supercomputing and Networking Center (PSNC) in Poland is taking an innovative approach with two photonic QPUs from ORCA Computing, connected to a new supercomputer partition accelerated by the CUDA-Q platform. This setup will allow researchers to explore a wide range of applications, from biology and chemistry to machine learning. Using quantum photonics systems, these QPUs offer a distributed, scalable and modular approach to quantum computing using standard telecommunications components.

These supercomputers represent significant advances in the integration of quantum and classical technologies, pushing the frontier of research in high-performance computing. These supercomputers are still using superchips NVIDIA Grace Hopper to accelerate scientific research. Together, these systems deliver 200 exaflops, or 200 quintillion calculations per second, of energy-efficient AI processing power.

AI is accelerating climate change research, accelerating drug discovery, and leading to breakthroughs in dozens of other fields. Systems powered by NVIDIA Grace Hopper are becoming an essential part of HPC for their ability to transform industries while driving better energy efficiency.

Ian Buck, Vice President of Hypercale and HPC at NVIDIA

O Isambard-AI e Isambard 3 from the University of Bristol in the UK, along with systems in the US such as those at Los Alamos National Laboratory and the Texas Advanced Computing Center, are joining a growing trend of NVIDIA's Arm-based supercomputers, taking advantage of Grace CPU Superchips and the Grace Hopper Platform. This movement reflects the global acceleration in the construction of AI-based supercomputers, driven by recognition of the strategic and cultural importance of superior AI — also known as sovereign AI.

By integrating GPU and CPU architectures based on Arm with interconnection technology NVIDIA NVLink-C2C, GH200 is leading this change, enabling scientific centers to move from system installation to practical research in a short period of time (according to the brand, ranging from years to months). The Isambard-AI project exemplifies this advancement, with the initial phase already demonstrating high efficiency, and the arrival of more Grace Hopper Superchips is expected to lead to a significant increase in supercomputer performance.

Conclusion

The introduction of NVIDIA CUDA-Q marks a significant moment in the convergence between quantum and classical computing, offering a flexible and powerful platform that drives innovation across a wide range of fields. By closely integrating these two domains, companies and institutions now have access to a new set of research and application possibilities, expanding the horizons of high-performance computing.

With its ability to deliver advanced performance, QPU agnosticism, and support for the developer community, CUDA-Q emerges as a essential tool to catalyze progress in both quantum computing and artificial intelligence, fueling a new era of technological innovation. Let's follow along to see what else the tool will provide us!

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With information from: NVIDIA [1] e [2]

reviewed by Glaucon Vital in 13 / 5 / 24.