Accelerating the future of scientific discovery.
Quantum computing is a new model of computing that can impact applications across industries, including drug discovery, chemistry, finance, energy, and more. To prepare for a quantum-accelerated future, governments, universities, and industries are investing in hardware, software, and algorithm development—and NVIDIA’s cutting-edge hardware and software platforms are helping them supercharge their quantum computing work.
To apply quantum computing to more useful domains, we need to develop better algorithms, as well as design the next generation of quantum processors (QPUs). To do this, we need to simulate the quantum processors of the future.
Useful quantum computing will be hybrid, with QPUs working in concert with CPUs and GPUs to solve problems. To achieve this, we need to integrate quantum computing into scientific computing and AI software and workflows.
Accelerated computing and AI are essential to unlocking the potential of quantum computing. We need to build quantum-integrated computers and supercomputers in order for quantum computers to benefit from accelerated computing and AI, as well as for supercomputers to be accelerated by the quantum computers of the future.
NVIDIA Quantum Cloud provides the entire quantum computing ecosystem with access to the world’s most powerful quantum computing platform, including quantum researchers, developers, enterprise end users, supercomputing centers, and startups building QPUs.
Quantum Cloud APIs can run CUDA-Q jobs on a range of NVIDIA GPU systems, enabling universal cloud quantum computing access for any application.
Quantum-accelerated applications won't run exclusively on a quantum resource but will be hybrid quantum and classical in nature. To transition from algorithm development by quantum physicists to application development by domain scientists, a development platform is needed that delivers high performance, interoperates with today's applications and programming paradigms, and is familiar and approachable to domain scientists.
With a unified programming model, NVIDIA® CUDA-Q is a first-of-its-kind platform for hybrid quantum-classical computers, enabling integration and programming of QPUs, quantum emulation, GPUs, and CPUs in one system. CUDA-Q is built for performance, is open source, and provides high-level language to develop and run hybrid quantum-classical applications.
NVIDIA cuQuantum is an SDK for accelerating quantum circuit simulation. Built to accelerate all circuit simulation frameworks and integrated into Cirq, Qiskit, Pennylane, and more, cuQuantum allows researchers to simulate ideal or noisy qubits with scale and performance.
cuQuantum offers a range of methods for emulating quantum computers. cuStateVec and cuTensorNet each offer alternative approaches for simulation quantum circuits at varying qubit count and depths. Each of these libraries offers APIs for quantum simulators, enabling researchers to easily leverage the performance and scale that the NVIDIA quantum platform provides, without being a GPU expert.
The cuQuantum Appliance is a Docker container consisting of leading community frameworks accelerated by cuQuantum and optimized for the NVIDIA platform.
The stack includes Cirq qsim and Qiskit Aer simulators along with cuQuantum. The cuQuantum Appliance enables up to almost a two-orders-of-magnitude speedup for multi-node simulations with no code changes, in addition to excellent strong and weak scaling across multiple GPUs and multiple nodes.
NVIDIA cuQuantum Appliance is available in the NVIDIA NGC™ catalog.
NVIDIA DGX™ Quantum is an integrated system and reference architecture for quantum-classical computing, built in partnership with Quantum Machines.
Combining NVIDIA Grace Hopper™ Superchips with the OPX Control System from Quantum Machines, DGX Quantum offers submicrosecond latency between the quantum control system and the GPU, delivering real-time, GPU-accelerated quantum error correction, calibration, and control.
DGX Quantum is QPU-agnostic and scales with both quantum and classical compute requirements, from a few to thousands of qubits and from a single GPU to a quantum-accelerated supercomputer.
Quantum computers threaten to break today’s public-key encryption mechanisms. To ensure the security and authenticity of the world’s sensitive data, it’s now critically important that organizations migrate to algorithms that can withstand a quantum computing attack. This new quantum-safe encryption is known as post-quantum cryptography (PQC).
NVIDIA cuPQC accelerates the leading PQC algorithms, advancing data security against quantum computer threats.
To grow a quantum-ready workforce, NVIDIA is teaming up with academic institutions to bring CUDA-Q into college classrooms through self-paced, online modules, complete with interactive coding exercises and videos. These CUDA-Q lessons will help students build and optimize quantum algorithms using both simulators and quantum hardware. Students will gain the skills needed to complete research projects and develop hybrid quantum-classical applications.
NVIDIA Quantum is enabling the entire quantum ecosystem—and some of the most important research happening today. From quantum computing startups to some of the largest companies in the world, academic labs and supercomputing centers to Fortune 500 companies, we’re proud to help our partners develop and leverage quantum.
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