NVIDIA CUDA Quantum
The platform for hybrid quantum-classical computing.
To do algorithm research and build applications for future quantum advantage, a bridging technology is needed to enable dynamic workflows across disparate system architectures. With a unified and open programming model, NVIDIA CUDA Quantum is a first-of-its-kind, open-source platform for integrating and programming quantum processing units (QPUs), GPUs, and CPUs in one system. NVIDIA CUDA Quantum enables GPU-accelerated system scalability and performance across heterogeneous QPU, CPU, GPU, and emulated quantum system elements.
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Key Benefits
Flexible and Scalable
Supports hybrid deployments via emulation on a single GPU up to NVIDIA DGX SuperPOD™and with multiple QPU partner backends
Open Platform
Connects to any type of QPU backend, allowing accessibility to all users
High Performing
287X speedup in end-to-end Variational Quantum Eigensolver (VQE) performance with 20 qubits and dramatically improved scaling compared to Pythonic frameworks
Easily Integrated
Interoperates with modern GPU-accelerated applications
Productive
Streamlines hybrid quantum-classical development with a unified environment, improving productivity and scalability in quantum algorithm research
A Range of Features
- Kernel-based programming model extending C++ and Python for hybrid quantum-classical systems
- Native support for GPU hybrid compute, enabling GPU pre- and post-processing and classical optimizations
- System-level compiler toolchain featuring split compilation with NVQ++ compiler for quantum kernels, lowering to Multi-Level Intermediate Representation (MLIR) and Quantum Intermediate Representation (QIR)
- Initial NVQ++ benchmark shows 287X improvement in end-to-end VQE performance with 20 qubits and dramatically improved scaling with system size compared to standard Pythonic implementation
- Standard library of quantum algorithmic primitives
- Interoperable with partner QPUs as well as simulated QPUs using the cuQuantum GPU platform; partnering with QPU builders across many different qubit types
Integrated Quantum Processors
NVIDIA CUDA Quantum enables straightforward execution of hybrid code on many different types of quantum processors, simulated or physical. Researchers can leverage the cuQuantum-accelerated simulation backend as well as QPUs from our partners or connect their own simulator or quantum processor. The image shows the variational quantum eigensolver running on both cuQuantum and Quantinuum’s H1 trapped ion QPU. Switching between the two is as simple as changing a compiler flag.
Quantum Computing Partners
Explore More Resources
- CUDA Quantum Press Release: NVIDIA Announces Hybrid Quantum-Classical Computing Platform
- NVIDIA Special Address at Q2B: Defining the Quantum Accelerated Supercomputing Platform
- Blog: Merge Ahead: Researcher Takes Software Bridge to Quantum Computing
- Blog: Introducing CUDA Quantum: The Platform for Hybrid Quantum-Classical Computing
- Explainer: What is a QPU?